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Energies, Volume 14, Issue 2 (January-2 2021) – 264 articles

Cover Story (view full-size image): In this work, the findings of different 2030 scenarios, considering various socio-economic and techno-economic determinants of possible future energy system development, identify numerous modification and reduction potentials of the electricity demand due to societal commitment and energy community penetration. View this paper
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30 pages, 8987 KiB  
Article
Energy Flexibility as Additional Energy Source in Multi-Energy Systems with District Cooling
by Alice Mugnini, Gianluca Coccia, Fabio Polonara and Alessia Arteconi
Energies 2021, 14(2), 519; https://doi.org/10.3390/en14020519 - 19 Jan 2021
Cited by 7 | Viewed by 3093
Abstract
The integration of multi-energy systems to meet the energy demand of buildings represents one of the most promising solutions for improving the energy performance of the sector. The energy flexibility provided by the building is paramount to allowing optimal management of the different [...] Read more.
The integration of multi-energy systems to meet the energy demand of buildings represents one of the most promising solutions for improving the energy performance of the sector. The energy flexibility provided by the building is paramount to allowing optimal management of the different available resources. The objective of this work is to highlight the effectiveness of exploiting building energy flexibility provided by thermostatically controlled loads (TCLs) in order to manage multi-energy systems (MES) through model predictive control (MPC), such that energy flexibility can be regarded as an additional energy source in MESs. Considering the growing demand for space cooling, a case study in which the MPC is used to satisfy the cooling demand of a reference building is tested. The multi-energy sources include electricity from the power grid and photovoltaic modules (both of which are used to feed a variable-load heat pump), and a district cooling network. To evaluate the varying contributions of energy flexibility in resource management, different objective functions—namely, the minimization of the withdrawal of energy from the grid, of the total energy cost and of the total primary energy consumption—are tested in the MPC. The results highlight that using energy flexibility as an additional energy source makes it possible to achieve improvements in the energy performance of an MES building based on the objective function implemented, i.e., a reduction of 53% for the use of electricity taken from the grid, a 43% cost reduction, and a 17% primary energy reduction. This paper also reflects on the impact that the individual optimization of a building with a multi-energy system could have on other users sharing the same energy sources. Full article
(This article belongs to the Special Issue Refrigeration, Air Conditioning and Heat Pumps: Energy and Environmental Issues II)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Scheme of an MPC controller used to exploit MESs in buildings.</p> Full article ">Figure 2
<p>Scheme of the proposed MPC for exploiting MESs in buildings.</p> Full article ">Figure 3
<p>Third-order RC network building model.</p> Full article ">Figure 4
<p>Schematic of the cooling system.</p> Full article ">Figure 5
<p>Daily cooling power profile from DC (for the single building).</p> Full article ">Figure 6
<p>Focus on a portion of users connected to DC: the user on the left is the building controlled using the MPC, while the user on the right represents a neighboring building.</p> Full article ">Figure 7
<p>Scheme of MPC controller applied to the case study.</p> Full article ">Figure 8
<p>TRNSYS model layout.</p> Full article ">Figure 9
<p>Energy sources used to cover the weekly cooling demand of the building compared to the availability profiles with RBC: (<b>a</b>) DC; (<b>b</b>) PV.</p> Full article ">Figure 10
<p>Energy sources used to cover the weekly cooling demand of the building compared to the availability profiles with MPC (OFG, PH of 18 h): (<b>a</b>) DC; (<b>b</b>) PV.</p> Full article ">Figure 11
<p>Electricity from the power grid (G) used to cover the weekly cooling demand of the building. Comparison between RBC and MPC (OFG, PH of 18 h).</p> Full article ">Figure 12
<p>Comparison between actual indoor air temperature (<span class="html-italic">T</span><sub>air</sub>) and its prediction in the MPC with OF<sub>G</sub> and <span class="html-italic">PH</span> of 18 h.</p> Full article ">Figure 13
<p>Energy sources used to cover the weekly cooling demand of the building compared to the availability profiles with MPC (OF<sub>C</sub>, <span class="html-italic">PH</span> of 18 h): (<b>a</b>) DC; (<b>b</b>) PV.</p> Full article ">Figure 14
<p>Comparison between actual indoor air temperature (<span class="html-italic">T</span><sub>air</sub>) and its prediction in the MPC with OF<sub>C</sub> and <span class="html-italic">PH</span> of 18 h.</p> Full article ">Figure 15
<p>Cost composition, comparison between RBC (<b>a</b>) and MPC (OF<sub>C</sub>, <span class="html-italic">PH</span> of 18 h) (<b>b</b>).</p> Full article ">Figure 16
<p>Energy sources used to cover the weekly cooling demand of the building compared to the availability profiles with MPC (OF<sub>P</sub>, <span class="html-italic">PH</span> of 18 h): (<b>a</b>) DC; (<b>b</b>) PV.</p> Full article ">Figure 17
<p>Comparison between actual indoor air temperature (<math display="inline"><semantics> <mrow> <msub> <mi>T</mi> <mrow> <mi>air</mi> </mrow> </msub> </mrow> </semantics></math>) and its prediction in the MPC with OF<sub>P</sub> and <span class="html-italic">PH</span> of 18 h.</p> Full article ">Figure 18
<p>Primary energy use per source: (<b>a</b>) RBC; (<b>b</b>) MPC (OF<sub>P</sub>, <span class="html-italic">PH</span> of 18 h).</p> Full article ">Figure 19
<p>Seasonal thermal demand satisfaction divided by energy sources: (<b>a</b>) RBC; (<b>b</b>) MPC with OF<sub>G</sub>; (<b>c</b>) MPC with OF<sub>C</sub>; (<b>d</b>) MPC with OF<sub>P</sub>. Results obtained with a <span class="html-italic">PH</span> of 18 h.</p> Full article ">Figure 20
<p>Comparisons among OF<sub>G</sub>, OF<sub>C</sub> and OF<sub>P</sub> in the MPC for the whole cooling season (<span class="html-italic">PH</span> = 18 h) in terms of percentage variation, compared to RBC, of: (<b>a</b>) thermal demand composition; (<b>b</b>) seasonal values of the three optimized quantities percentage reduction.</p> Full article ">Figure 21
<p>Comparison between RBC, OF<sub>G</sub>, OF<sub>C</sub> and OF<sub>P</sub> in the MPC for the whole cooling season (<span class="html-italic">PH</span> = 18 h) in terms of: (<b>a</b>) total cooling demand; (<b>b</b>) use of DC; (<b>c</b>) use of PV; (<b>d</b>) use of G; (<b>e</b>) cost and (<b>f</b>) primary energy consumption.</p> Full article ">Figure 21 Cont.
<p>Comparison between RBC, OF<sub>G</sub>, OF<sub>C</sub> and OF<sub>P</sub> in the MPC for the whole cooling season (<span class="html-italic">PH</span> = 18 h) in terms of: (<b>a</b>) total cooling demand; (<b>b</b>) use of DC; (<b>c</b>) use of PV; (<b>d</b>) use of G; (<b>e</b>) cost and (<b>f</b>) primary energy consumption.</p> Full article ">Figure 22
<p>Duration curve for (<b>a</b>) the indoor air temperature and (<b>b</b>) cooling power from DC used by the neighboring building. Comparison between RBC, MPC with OF<sub>G</sub>, OF<sub>C</sub> and OF<sub>P</sub> (<span class="html-italic">PH</span> = 18 h) and user disconnection from the DC network (OFF).</p> Full article ">
22 pages, 43361 KiB  
Article
The LVRT Control Scheme for PMSG-Based Wind Turbine Generator Based on the Coordinated Control of Rotor Overspeed and Supercapacitor Energy Storage
by Xiangwu Yan, Linlin Yang and Tiecheng Li
Energies 2021, 14(2), 518; https://doi.org/10.3390/en14020518 - 19 Jan 2021
Cited by 20 | Viewed by 4106
Abstract
With the increasing penetration level of wind turbine generators (WTGs) integrated into the power system, the WTGs are enforced to aid network and fulfill the low voltage ride through (LVRT) requirements during faults. To enhance LVRT capability of permanent magnet synchronous generator (PMSG)-based [...] Read more.
With the increasing penetration level of wind turbine generators (WTGs) integrated into the power system, the WTGs are enforced to aid network and fulfill the low voltage ride through (LVRT) requirements during faults. To enhance LVRT capability of permanent magnet synchronous generator (PMSG)-based WTG connected to the grid, this paper presents a novel coordinated control scheme named overspeed-while-storing control for PMSG-based WTG. The proposed control scheme purely regulates the rotor speed to reduce the input power of the machine-side converter (MSC) during slight voltage sags. Contrarily, when the severe voltage sag occurs, the coordinated control scheme sets the rotor speed at the upper-limit to decrease the input power of the MSC at the greatest extent, while the surplus power is absorbed by the supercapacitor energy storage (SCES) so as to reduce its maximum capacity. Moreover, the specific capacity configuration scheme of SCES is detailed in this paper. The effectiveness of the overspeed-while-storing control in enhancing the LVRT capability is validated under different levels of voltage sags and different fault types in MATLAB/Simulink. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The grid codes of China.</p> Full article ">Figure 2
<p>The technical principle of low voltage ride through (LVRT).</p> Full article ">Figure 3
<p>The input power curve of the permanent magnet synchronous generator (PMSG).</p> Full article ">Figure 4
<p>Actual curve and fitting curve of λ-Cp.</p> Full article ">Figure 5
<p>The control strategy of the machine-side converter (MSC): (<b>a</b>) the outer loop control and (<b>b</b>) the inner loop control.</p> Full article ">Figure 6
<p>The control strategy of the bidirectional DC–DC converter.</p> Full article ">Figure 7
<p>The bidirectional DC–DC working mode: (<b>a</b>) buck mode and (<b>b</b>) boost mode</p> Full article ">Figure 8
<p>The flow chart of the two coordination control schemes.</p> Full article ">Figure 9
<p>The control strategy of the grid-side converter (GSC): (<b>a</b>) the outer loop control and (<b>b</b>) the inner loop control.</p> Full article ">Figure 10
<p>The simplified modeling of the grid-connected wind system.</p> Full article ">Figure 11
<p>The simulation results of the rotor overspeed control scheme.</p> Full article ">Figure 11 Cont.
<p>The simulation results of the rotor overspeed control scheme.</p> Full article ">Figure 12
<p>The simulation results of the supercapacitor energy storage (SCES) control scheme.</p> Full article ">Figure 12 Cont.
<p>The simulation results of the supercapacitor energy storage (SCES) control scheme.</p> Full article ">Figure 13
<p>The simulation results of the overspeed-while-storing control.</p> Full article ">Figure 13 Cont.
<p>The simulation results of the overspeed-while-storing control.</p> Full article ">Figure 14
<p>The simulation results of the overspeed-while-storing control under a single line-to-ground fault.</p> Full article ">Figure 14 Cont.
<p>The simulation results of the overspeed-while-storing control under a single line-to-ground fault.</p> Full article ">Figure 15
<p>The simulation results of the overspeed-while-storing control under the double line-to-ground fault.</p> Full article ">Figure 15 Cont.
<p>The simulation results of the overspeed-while-storing control under the double line-to-ground fault.</p> Full article ">Figure 15 Cont.
<p>The simulation results of the overspeed-while-storing control under the double line-to-ground fault.</p> Full article ">Figure 16
<p>The simulation results comparison between the conventional control and the overspeed-while-storing control.</p> Full article ">Figure 16 Cont.
<p>The simulation results comparison between the conventional control and the overspeed-while-storing control.</p> Full article ">
16 pages, 4796 KiB  
Article
A Novel Data-Driven Modeling and Control Design Method for Autonomous Vehicles
by Dániel Fényes, Balázs Németh and Péter Gáspár
Energies 2021, 14(2), 517; https://doi.org/10.3390/en14020517 - 19 Jan 2021
Cited by 18 | Viewed by 4955
Abstract
This paper presents a novel modeling method for the control design of autonomous vehicle systems. The goal of the method is to provide a control-oriented model in a predefined Linear Parameter Varying (LPV) structure. The scheduling variables of the LPV model [...] Read more.
This paper presents a novel modeling method for the control design of autonomous vehicle systems. The goal of the method is to provide a control-oriented model in a predefined Linear Parameter Varying (LPV) structure. The scheduling variables of the LPV model through machine-learning-based methods using a big dataset are selected. Moreover, the LPV model parameters through an optimization algorithm are computed, with which accurate fitting on the dataset is achieved. The proposed method is illustrated on the nonlinear modeling of the lateral vehicle dynamics. The resulting LPV-based vehicle model is used for the control design of path following functionality of autonomous vehicles. The effectiveness of the modeling and control design methods through comprehensive simulation examples based on a high-fidelity simulation software are illustrated. Full article
(This article belongs to the Special Issue Control Design for Electric Vehicles)
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Figure 1

Figure 1
<p>Methodological process for modeling, control design, and evaluation.</p> Full article ">Figure 2
<p>Illustration of the error functions and their resolution.</p> Full article ">Figure 3
<p>Resolution of the scheduling variables.</p> Full article ">Figure 4
<p>Evaluation of the optimized model.</p> Full article ">Figure 5
<p>Augmented plant.</p> Full article ">Figure 6
<p>Structure of control system.</p> Full article ">Figure 7
<p>Positions of the vehicles during the simulations.</p> Full article ">Figure 8
<p>Velocity profile and lateral acceleration of the vehicle.</p> Full article ">Figure 9
<p>Scheduling parameters and tracking of yaw-rate.</p> Full article ">Figure 10
<p>Interventions of the vehicles.</p> Full article ">
32 pages, 657 KiB  
Article
Modelling Bidding Behaviour on German Photovoltaic Auctions
by Enikő Kácsor
Energies 2021, 14(2), 516; https://doi.org/10.3390/en14020516 - 19 Jan 2021
Cited by 3 | Viewed by 3373
Abstract
In this article renewable energy support allocation through different types of auctions are assessed. The applied methodological framework is auction theory, based on the rules governing the German photovoltaic (PV) Feed-in Premium (FIP) auctions. The work focuses on bidding strategies based on an [...] Read more.
In this article renewable energy support allocation through different types of auctions are assessed. The applied methodological framework is auction theory, based on the rules governing the German photovoltaic (PV) Feed-in Premium (FIP) auctions. The work focuses on bidding strategies based on an extended levelised cost of electricity (LCOE) methodology, comparing two different set of rules: uniform price and pay-as-bid. When calculating the optimal bids an iteration is developed to find the Nash-equilibrium optimal bidding strategy. When searching for the bid function, not only strictly monotone functions, but also monotone functions are considered, extending the framework typically applied in auction theory modelling. The results suggest that the PV support allocation in the German auction system would be more cost efficient using the uniform pricing rule, since many participants bid above their true valuation in the pay-as-bid auction Nash-equilibrium. Thus from a cost minimising perspective, the application of uniform pricing rule would be a better policy decision. Full article
(This article belongs to the Special Issue Transition of Renewable Energy Policy: What Energy Markets Can and Cannot Solve)
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Figure 1

Figure 1
<p>Renewable shares in the electricity (RES-E), transport (RES-T) and heating and cooling (RES-H&amp;C) sectors, source: own figure based on Eurostat data.</p> Full article ">Figure 2
<p>Assumed generation profiles of a day in the different times of the year, source: <span class="html-small-caps">eemm</span> data.</p> Full article ">Figure 3
<p>Own LCOE estimation referencing values from the literature, source: Fraunhofer, 2018; Fraunhofer, 2015; Lazard, 2017; IEA, 2017; Irena, 2018; <span class="html-small-caps">eemm</span> data.</p> Full article ">Figure 4
<p>Critical investment costs for different WACC and OPEX values, source: own figure.</p> Full article ">Figure 5
<p>Empirical distribution of <math display="inline"><semantics> <mrow> <mi>L</mi> <mi>C</mi> <mi>O</mi> <msup> <mi>E</mi> <mo>′</mo> </msup> </mrow> </semantics></math> calculated from the simulated 10,000 investment costs, source: own figure.</p> Full article ">Figure 6
<p>The optimal bidfunction assuming <math display="inline"><semantics> <msub> <mi>F</mi> <mn>1</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure 7
<p>The optimal bid function assuming <math display="inline"><semantics> <msub> <mi>F</mi> <mn>2</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure 8
<p>The optimal bid function assuming <math display="inline"><semantics> <msub> <mi>F</mi> <mn>3</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure 9
<p>The optimal bid function assuming <math display="inline"><semantics> <msub> <mi>F</mi> <mn>4</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure 10
<p>Optimal bids for given valuations assuming <math display="inline"><semantics> <msub> <mi>F</mi> <mn>3</mn> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>F</mi> <mn>4</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure 11
<p>Bid distribution function assuming bid function <math display="inline"><semantics> <msub> <mi>f</mi> <mi>N</mi> </msub> </semantics></math>, source: own figure.</p> Full article ">Figure 12
<p>Optimal bid function assuming <math display="inline"><semantics> <msub> <mi>f</mi> <mi>N</mi> </msub> </semantics></math> bidding strategy from others, source: own figure.</p> Full article ">Figure 13
<p>The assumed and the optimal bids for 10,000 valuations, source: own figure.</p> Full article ">Figure A1
<p>Probability of winning in case of different bids, assuming <math display="inline"><semantics> <msub> <mi>F</mi> <mn>1</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure A2
<p>Sorted optimal bids, assuming <math display="inline"><semantics> <msub> <mi>F</mi> <mn>1</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure A3
<p>The <math display="inline"><semantics> <msub> <mi>F</mi> <mn>2</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure A4
<p>Probability of winning in case of different bids, assuming <math display="inline"><semantics> <msub> <mi>F</mi> <mn>2</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure A5
<p>Sorted optimal bids, assuming <math display="inline"><semantics> <msub> <mi>F</mi> <mn>2</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure A6
<p>The <math display="inline"><semantics> <msub> <mi>F</mi> <mn>3</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure A7
<p>Probability of winning in case of different bids, assuming <math display="inline"><semantics> <msub> <mi>F</mi> <mn>3</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure A8
<p>Sorted optimal bids, assuming <math display="inline"><semantics> <msub> <mi>F</mi> <mn>3</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure A9
<p>The <math display="inline"><semantics> <msub> <mi>F</mi> <mn>4</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure A10
<p>Probability of winning in case of different bids, assuming <math display="inline"><semantics> <msub> <mi>F</mi> <mn>4</mn> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">Figure A11
<p>Sorted optimal bids assuming <math display="inline"><semantics> <msub> <mi>f</mi> <mi>N</mi> </msub> </semantics></math> bid function, source: own figure.</p> Full article ">Figure A12
<p>Probability of winning in case of different bids, assuming <math display="inline"><semantics> <msub> <mi>F</mi> <mi>N</mi> </msub> </semantics></math> bid distribution, source: own figure.</p> Full article ">
21 pages, 8705 KiB  
Article
Cladding Profilometry Analysis of Experimental Breeder Reactor-II Metallic Fuel Pins with HT9, D9, and SS316 Cladding
by Kyle M. Paaren, Nancy Lybeck, Kun Mo, Pavel Medvedev and Douglas Porter
Energies 2021, 14(2), 515; https://doi.org/10.3390/en14020515 - 19 Jan 2021
Cited by 13 | Viewed by 2410
Abstract
BISON finite element method fuel performance simulations were conducted using an existing automated process that couples the Fuels Irradiation & Physics Database (FIPD) and the Integral Fast Reactor Materials Information System database by writing input files and comparing the BISON output to post-irradiation [...] Read more.
BISON finite element method fuel performance simulations were conducted using an existing automated process that couples the Fuels Irradiation & Physics Database (FIPD) and the Integral Fast Reactor Materials Information System database by writing input files and comparing the BISON output to post-irradiation fuel pin profilometry measurements contained within the databases. The importance of this work is to demonstrate the ability to benchmark fuel performance metallic fuel models within BISON using Experimental Breeder Reactor-II fuel pin data for a number of similar pins, while building off previous modeling efforts. Changes to the generic BISON input file include implementing pin specific axial power and flux profiles, pin specific fluences, frictional contact, and irradiation-induced volumetric swelling models for cladding. A statistical analysis of irradiation-induced volumetric swelling models for HT9, D9, and SS316 was performed for experiments X421/X421A, X441/X441A, and X486. Between these three experiments, there were 174 post-irradiation examination (PIE) profilometries used for validating the swelling models presented using a standard error of the estimate (SEE) method. Implementation of the volumetric swelling models for D9 and SS316 claddings was found to have a significant impact on the BISON profilometry simulated, where HT9 clad pins had an insignificant change due to low fluence values. BISON profilometry simulated for HT9, D9, and SS316 fuel pins agreed with PIE profilometry measurements, with assembly SEE values being 4.4 × 10−3 for X421A, 2.0 × 10−3 for X441A, and 2.8 × 10−3 for X486. D9 clad pins in X421/X421A had the highest SEE values, which is due to the BISON simulated profilometry being shifted axially. While this work accomplished its purpose to demonstrate the modeling of multiple fuel pins from the databases to help validate models, the results suggest that the continued development of metallic fuel models is necessary for qualifying new metallic fuel systems to better capture some physical performance phenomena, such as the hot pressing of U-Pu-Zr and the fuel cladding chemical interaction. Full article
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Figure 1
<p>X421 (<b>left</b>) and X421A (<b>right</b>) subassembly layout [<a href="#B4-energies-14-00515" class="html-bibr">4</a>].</p> Full article ">Figure 2
<p>X441 (<b>left</b>) and X441A (<b>right</b>) subassembly layout [<a href="#B4-energies-14-00515" class="html-bibr">4</a>].</p> Full article ">Figure 3
<p>X486 (<b>left</b>) and X486A (<b>right</b>) subassembly layout [<a href="#B4-energies-14-00515" class="html-bibr">4</a>].</p> Full article ">Figure 4
<p>DP25 Fuel fission rate density distribution (<span class="html-italic">f</span>·m<sup>−3</sup>·s<sup>−1</sup>), radial direction magnified by ×50.</p> Full article ">Figure 5
<p>DP25 X441/X441A Linear heat generation rate history.</p> Full article ">Figure 6
<p>SS316 Volume Swelling Temperature Dependence.</p> Full article ">Figure 7
<p>SS316 Volume Swelling Alpha Dependence at 755 K and Tau = 6.68.</p> Full article ">Figure 8
<p>SS316 Volume Swelling Tau Dependence at 755 K and Alpha = 0.75.</p> Full article ">Figure 9
<p>Profilometry Profile Statistical Assessment with SEE.</p> Full article ">Figure 10
<p>X421 T068 Cladding Profilometry (D9-clad, 9.3 at.% BU).</p> Full article ">Figure 11
<p>X421A T068 Cladding Profilometry (D9-clad, 16.1 at.% BU).</p> Full article ">Figure 12
<p>X421 T227 Cladding Profilometry (D9-clad, 9.4 at.% BU).</p> Full article ">Figure 13
<p>X421A T227 Cladding Profilometry (D9-clad, 16.5 at.% BU).</p> Full article ">Figure 14
<p>X441 DP21 Cladding Profilometry (HT9-clad, 4.7 at.% BU).</p> Full article ">Figure 15
<p>X441A DP21 Cladding Profilometry (HT9-clad, 9.8 at.% BU).</p> Full article ">Figure 16
<p>X441 DP25 Cladding Profilometry (HT9-clad, 4.7at.% BU).</p> Full article ">Figure 17
<p>X441A DP25 Cladding Profilometry (HT9-clad, 9.3 at.% BU).</p> Full article ">Figure 18
<p>X486 J555 Cladding Profilometry (CW316-clad, 8.8 at.% BU).</p> Full article ">Figure 19
<p>X486 J630 Cladding Profilometry (CW316-clad, 8.8 at.% BU).</p> Full article ">Figure 20
<p>X486 J630 and J651 Cladding Temperature Profile Comparison.</p> Full article ">
17 pages, 7543 KiB  
Article
Design and Analysis of a Five-Phase Permanent-Magnet Synchronous Motor for Fault-Tolerant Drive
by Muhammad H. Iftikhar, Byung-Gun Park and Ji-Won Kim
Energies 2021, 14(2), 514; https://doi.org/10.3390/en14020514 - 19 Jan 2021
Cited by 17 | Viewed by 4159
Abstract
Reliability is a fundamental requirement in electric propulsion systems, involving a particular approach in studies on system failure probabilities. An intrinsic improvement to the propulsion system involves introducing robust architectures such as fault-tolerant motor drives to these systems. Considering the potential for hardware [...] Read more.
Reliability is a fundamental requirement in electric propulsion systems, involving a particular approach in studies on system failure probabilities. An intrinsic improvement to the propulsion system involves introducing robust architectures such as fault-tolerant motor drives to these systems. Considering the potential for hardware failures, a fault-tolerant design approach will achieve reliability objectives without recourse to optimized redundancy or over-sizing the system. Provisions for planned degraded modes of operation are designed to operate the motor in fault-tolerant mode, which makes them different from the pure design redundancy approach. This article presents how a five-phase permanent-magnet synchronous motor operates under one- or two-phase faults, and how the system reconfigures post-fault motor currents to meet the torque and speed requirement of reliable operation that meets the requirements of an electric propulsion system. Full article
(This article belongs to the Special Issue Design and Analysis of Electric Machines)
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Figure 1

Figure 1
<p>The winding topology of a five-phase permanent-magnet synchronous motor.</p> Full article ">Figure 2
<p>Design representation of the five-phase PMSM: (<b>a</b>) cross-section, (<b>b</b>) winding configuration.</p> Full article ">Figure 3
<p>(<b>a</b>) Mesh distribution, Elmer; (<b>b</b>) mesh distribution, JMAG; (<b>c</b>) flux density, Elmer; (<b>d</b>) flux density, JMAG; (<b>e</b>) Joule loss density, Elmer; (<b>f</b>) Joule loss density, JMAG; (<b>g</b>) iron loss density, Elmer; (<b>h</b>) iron loss density, JMAG.</p> Full article ">Figure 4
<p>Five-phase Voltage Source Inverter (VSI) topology.</p> Full article ">Figure 5
<p>Vector space diagrams: (<b>a</b>) healthy operation; (<b>b</b>) phase A open; (<b>c</b>) phase A and C open; (<b>d</b>) phase A and B open.</p> Full article ">Figure 6
<p>Configuration of the proposed vector space diagrams: (<b>a</b>) one-phase fault; (<b>b</b>) two-phase fault.</p> Full article ">Figure 7
<p>(<b>a</b>) Torque with respect to the offset angle for a one-phase fault; (<b>b</b>) proposed solution for a one-phase fault.</p> Full article ">Figure 8
<p>(<b>a</b>) Torque with respect to the offset angle for two non-adjacent phase faults; (<b>b</b>) proposed solution for two non-adjacent phase faults.</p> Full article ">Figure 9
<p>(<b>a</b>) Torque with respect to the offset angle for two adjacent phase faults; (<b>b</b>) proposed solution for two adjacent phase faults.</p> Full article ">Figure 10
<p>A simulation model for the fault-tolerant control of the five-phase PMSM.</p> Full article ">Figure 11
<p>The current profile of a 5-phase PMSM.</p> Full article ">Figure 12
<p>Current and back-emf profiles in the case of healthy operation and one- and two-phase fault operations.</p> Full article ">Figure 13
<p>Torque and speed profiles in case of healthy and one- and two-phase fault operation.</p> Full article ">Figure 14
<p>Phase voltage profile in case of healthy operation, one-and two-phase fault operations.</p> Full article ">Figure 15
<p>FEM modeling results: (<b>a</b>) healthy operation; (<b>b</b>) a one-phase fault (A open), (<b>c</b>) a non-adjacent two-phase fault (A and C open), (<b>d</b>) two adjacent phase fault (A and B open).</p> Full article ">Figure 16
<p>Prototype: (<b>a</b>) a five-phase PMSM; (<b>b</b>) a permanent magnet rotor; (<b>c</b>) the stator of a five-phase PMSM.</p> Full article ">Figure 17
<p>Experiment test bench.</p> Full article ">Figure 18
<p>Current profiles: (<b>a</b>) a healthy operation; (<b>b</b>) a one-phase fault (A open); (<b>c</b>) a non-adjacent two-phase fault (A and C open); (<b>d</b>) an adjacent two-phase fault (A and B open).</p> Full article ">Figure 19
<p>Rotational speed profiles: (<b>a</b>) a healthy operation; (<b>b</b>) a one-phase fault (A-Open), (<b>c</b>) a non-adjacent two-phase fault (A and C open), (<b>d</b>) an adjacent two-phase fault (A and B open).</p> Full article ">
20 pages, 3817 KiB  
Article
Analysis of Various Options for Balancing Power Systems’ Peak Load
by Henryk Majchrzak and Michał Kozioł
Energies 2021, 14(2), 513; https://doi.org/10.3390/en14020513 - 19 Jan 2021
Cited by 2 | Viewed by 2187
Abstract
The balancing of the power of the Polish Power System (KSE) is a key element in ensuring the safety of electric energy supplies to end users. This article presents an analysis of the power demand in power systems (PS), with emphasis on the [...] Read more.
The balancing of the power of the Polish Power System (KSE) is a key element in ensuring the safety of electric energy supplies to end users. This article presents an analysis of the power demand in power systems (PS), with emphasis on the typical power variability both in subsequent hours of the day and on particular days and in particular months each year. The methodology for calculating the costs of electric energy undelivered to the end users and the amount of these costs for KSE is presented. Different possibilities have been analyzed for balancing power systems’ peak load and assumptions have been formulated for calculating the amount of the related costs. On this basis, a comparative analysis has been made of the possibility to balance peak load using operators’ system services, trans-border connections, and various energy storage solutions. On the basis of the obtained results, optimal tools have been proposed for market-based influence from transmission and distribution system operators on energy market participants’ behaviors in order to ensure the power systems’ operating safety and continuous energy deliveries to end users. Full article
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<p>Power demand curves on the days when the minimum and the maximum domestic demand for power in the Polish Power System (KSE) occurred in 2019 [<a href="#B2-energies-14-00513" class="html-bibr">2</a>].</p> Full article ">Figure 2
<p>Domestic power demand curves for the day with the maximum and the minimum demand in the morning peak of a working day in 2019 [<a href="#B2-energies-14-00513" class="html-bibr">2</a>].</p> Full article ">Figure 3
<p>Average monthly power demand at daily peak loads in KSE on working days in the years 2010–2019 [<a href="#B2-energies-14-00513" class="html-bibr">2</a>].</p> Full article ">Figure 4
<p>Average annual domestic power demand and the maximum values at daily peak loads on working days in the years 1980–2019 [<a href="#B2-energies-14-00513" class="html-bibr">2</a>].</p> Full article ">Figure 5
<p>Dependence of the net unit fixed cost of power balancing by system services on the services utilization time in KSE (prepared by the author).</p> Full article ">Figure 6
<p>Dependence of the net unit power balancing cost by energy storages on the time of their use in a year (prepared by the author).</p> Full article ">Figure 7
<p>Comparison of the net unit power balancing cost by selected KSE peak power sources, for different times of their utilization in a year (prepared by the author for 2020).</p> Full article ">
23 pages, 8222 KiB  
Article
Comparison of Factorial and Latin Hypercube Sampling Designs for Meta-Models of Building Heating and Cooling Loads
by Younhee Choi, Doosam Song, Sungmin Yoon and Junemo Koo
Energies 2021, 14(2), 512; https://doi.org/10.3390/en14020512 - 19 Jan 2021
Cited by 36 | Viewed by 6320
Abstract
Interest in research analyzing and predicting energy loads and consumption in the early stages of building design using meta-models has constantly increased in recent years. Generally, it requires many simulated or measured results to build meta-models, which significantly affects their accuracy. In this [...] Read more.
Interest in research analyzing and predicting energy loads and consumption in the early stages of building design using meta-models has constantly increased in recent years. Generally, it requires many simulated or measured results to build meta-models, which significantly affects their accuracy. In this study, Latin Hypercube Sampling (LHS) is proposed as an alternative to Fractional Factor Design (FFD), since it can improve the accuracy while including the nonlinear effect of design parameters with a smaller size of data. Building energy loads of an office floor with ten design parameters were selected as the meta-models’ objectives, and were developed using the two sampling methods. The accuracy of predicting the heating/cooling loads of the meta-models for alternative floor designs was compared. For the considered ranges of design parameters, window insulation (WDI) and Solar Heat Gain Coefficient (SHGC) were found to have nonlinear characteristics on cooling and heating loads. LHS showed better prediction accuracy compared to FFD, since LHS considers the nonlinear impacts for a given number of treatments. It is always a good idea to use LHS over FFD for a given number of treatments, since the existence of nonlinearity in the relation is not pre-existing information. Full article
(This article belongs to the Special Issue Data-Driven Energy-Cost Analysis of HVAC System for Buildings)
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<p>Comparison of data sampling methods: (<b>a</b>) two level full/fractional factorial design; (<b>b</b>) three level full factorial design; and (<b>c</b>) Latin hypercube sampling design.</p> Full article ">Figure 2
<p>Random sampling of Latin hypercube sampled design.</p> Full article ">Figure 3
<p>Schematics of the design points sampling method comparison and validation.</p> Full article ">Figure 4
<p>(<b>a</b>) Comparison of meta-model accuracies for heating load (RMSE). (<b>b</b>) Comparison of meta-model accuracies for cooling load (RMSE).</p> Full article ">Figure 5
<p>(<b>a</b>) Comparison of building heating load prediction accuracy for the “FFD validation set” using LHS and FFD (sampling number: 512). (<b>b</b>) Comparison of building cooling load prediction accuracy for the “FFD validation” set using LHS and FFD (sampling number: 512).</p> Full article ">Figure 6
<p>(<b>a</b>) Comparison of building heating load prediction accuracy for the “LHS validation set” using LHS and FFD (sampling number: 512). (<b>b</b>) Comparison of building cooling load prediction accuracy for the LHS validation set using LHS and FFD (sampling number: 512).</p> Full article ">Figure 6 Cont.
<p>(<b>a</b>) Comparison of building heating load prediction accuracy for the “LHS validation set” using LHS and FFD (sampling number: 512). (<b>b</b>) Comparison of building cooling load prediction accuracy for the LHS validation set using LHS and FFD (sampling number: 512).</p> Full article ">Figure 7
<p>Factor importance analysis for heating load of the meta-models using: (<b>a</b>) FFD; (<b>b</b>) LHS considering nonlinearity.</p> Full article ">Figure 8
<p>Factor importance analysis for cooling load of the meta-models using: (<b>a</b>) FFD; (<b>b</b>) LHS considering nonlinearity.</p> Full article ">Figure 9
<p>(<b>a</b>) The influence of design factor variations on building heating load. (<b>b</b>) The influence of design factor variations on building cooling load.</p> Full article ">Figure 9 Cont.
<p>(<b>a</b>) The influence of design factor variations on building heating load. (<b>b</b>) The influence of design factor variations on building cooling load.</p> Full article ">Figure 10
<p>Comparison of mean calculated WDI and SHGC.</p> Full article ">
26 pages, 38528 KiB  
Article
Experimental Feasibility Study of a Direct Contact Latent Heat Storage Using an Ester as a Bio-Based Storage Material
by Lukas Hegner, Stefan Krimmel, Rebecca Ravotti, Dominic Festini, Jörg Worlitschek and Anastasia Stamatiou
Energies 2021, 14(2), 511; https://doi.org/10.3390/en14020511 - 19 Jan 2021
Cited by 8 | Viewed by 8148
Abstract
Latent heat storage (LHS) represents a valuable technology for the integration of intermittent renewable energy sources in existing and future energy systems. Improvements in LHS can be sought by enhancing heat transfer efficiency, compactness and diminishing the environmental impact of storage systems. In [...] Read more.
Latent heat storage (LHS) represents a valuable technology for the integration of intermittent renewable energy sources in existing and future energy systems. Improvements in LHS can be sought by enhancing heat transfer efficiency, compactness and diminishing the environmental impact of storage systems. In this paper, direct contact latent heat storage (DC-LHS) using esters as phase change material (PCM) is proposed as a promising compact storage technology to achieve high performance both in terms of heat transfer and sustainability. The technology allows for the heat transfer fluid (HTF) to flow directly through the PCM, forming a large amount of small droplets and thus providing a large heat exchange surface area between the two materials. At the same time, using biobased esters as PCM, gives the technology clear ecological advantages when compared to alternative types of compact energy storage. Furthermore, no complex heat transfer enhancing structures are necessary in a DC-LHS, further reducing the environmental impact and enabling very high energy densities. In this paper, the feasibility of this concept is explored for the first time by developing and testing an experimental DC-LHS device using methyl palmitate as PCM and water as HTF. The thermal performance and stability of the material combination are analysed by different melting–solidification experiments and distinctive effects are identified and comprehensively discussed for the first time. The basic concept as well as the novel material combination are validated. The study finds the critical challenges that must be overcome in order for this highly promising technology to be successfully implemented. Full article
(This article belongs to the Section D: Energy Storage and Application)
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<p>(<b>Left</b>) Schematic of the experimental setup. From the bottom left in direction of the HTF flow one can see: the pump, the plate heat exchanger and thermostat, the three way ball valve connected to the glass tube inlet and the bypass. Following the HTF toward the glass tube, the inlet temperature can be seen being measured immediately before the nozzle. The glass tube, seen on the right in the figure represent the tank, contains the PCM and HTF. Images are taken of the process in the glass tube using a camera and a light source. The outlet temperature is measured immediately before the glass tube exit. The mass flow is measured using an ultrasonic flow meter, before the HTF flow from the glass tube is rejoined by the HTF from the bypass. (<b>Right</b>) Close up of GL45 fitting and the top of the glass tube, in this case with the short nozzle attached.</p> Full article ">Figure 2
<p>Comparison between the temperature profile of an uninsulated and an insulated melting process. The inlet temperatures are shown in yellow for the insulated case and in blue for the uninsulated case, while the outlet temperature is shown in purple for the insulated measurements and red for the uninsulated data.</p> Full article ">Figure 3
<p>Measurement of the emulsion height. In the upper section of the glass tube a multiphase flow of HTF through PCM can be seen. In the middle section the ‘bulk’ emulsion to be measured can be seen (indicated by the red arrow). A layer of HTF is visible below the ‘bulk’ emulsion.</p> Full article ">Figure 4
<p>Schematic of the system boundaries and energy flows. The arrows indicate the direction of the heat flow during a melting process with the system above room temperature.</p> Full article ">Figure 5
<p>Two sets of images showing characteristic behaviour of the nozzle immersed into the PCM (<math display="inline"><semantics> <mrow> <msub> <mi>D</mi> <mi>A</mi> </msub> <mo>=</mo> </mrow> </semantics></math> 7 <math display="inline"><semantics> <mrow> <mi mathvariant="normal">c</mi> <mi mathvariant="normal">m</mi> </mrow> </semantics></math>) in the image group on the left, and the short nozzle ending above the PCM (<math display="inline"><semantics> <mrow> <msub> <mi>D</mi> <mi>B</mi> </msub> <mo>=</mo> </mrow> </semantics></math> 8 <math display="inline"><semantics> <mrow> <mi mathvariant="normal">c</mi> <mi mathvariant="normal">m</mi> </mrow> </semantics></math>) in the image group on the right. Both image sets show (1) a schematic of the nozzle design, (2) HTF flow of 23 <math display="inline"><semantics> <mrow> <mi>kg</mi> <mo> </mo> <msup> <mi mathvariant="normal">h</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math> (at <math display="inline"><semantics> <mrow> <mn>15</mn> <mo> </mo> <mi mathvariant="normal">K</mi> </mrow> </semantics></math> above PCM melting temperature) into the PCM and (3) distinct solidification behaviour (18.2 <math display="inline"><semantics> <mrow> <mi>kg</mi> <mo> </mo> <msup> <mi mathvariant="normal">h</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>; 10 <math display="inline"><semantics> <mi mathvariant="normal">K</mi> </semantics></math> below PCM melting temperature) respectively. Limited turbulence and single channel formation can be seen with the immersed nozzle while increased turbulence, higher HTF-PCM surface area and flake formation is observed with the short nozzle.</p> Full article ">Figure 6
<p>PCM solidification along the immersed nozzle.</p> Full article ">Figure 7
<p>Data points of steady state emulsion heights recorded on the first day of the emulsion buildup investigation. The red line indicates the maximum allowable emulsion height before the experiment had to be terminated.</p> Full article ">Figure 8
<p>Images of the steady state emulsion height at 10 <math display="inline"><semantics> <mi mathvariant="normal">K</mi> </semantics></math> above PCM melting temperature, recorded on day 3 of the emulsion buildup investigation. The mass flow settings of the images from left to right: 15 <math display="inline"><semantics> <mrow> <mi>kg</mi> <mo> </mo> <msup> <mi mathvariant="normal">h</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, 18.2 <math display="inline"><semantics> <mrow> <mi>kg</mi> <mo> </mo> <msup> <mi mathvariant="normal">h</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, 20 <math display="inline"><semantics> <mrow> <mi>kg</mi> <mo> </mo> <msup> <mi mathvariant="normal">h</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, 25 <math display="inline"><semantics> <mrow> <mi>kg</mi> <mo> </mo> <msup> <mi mathvariant="normal">h</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>.</p> Full article ">Figure 9
<p>Temperature profile of Cycle 7. Inlet and outlet temperatures in <math display="inline"><semantics> <mrow> <msup> <mrow/> <mo>°</mo> </msup> <mi mathvariant="normal">C</mi> </mrow> </semantics></math> are visible in blue (on the left hand y-axis), while mass flow in kilograms per hour is shown in orange (on the right hand y-axis). Experiment run time is shown in minutes and 5 points of interest are marked in the plot. Point 1 shows first stoppage of mass flow through the system to allow the thermostat to heat up. Point 2 shows the start of the melting process. Point 3 shows some temperature fluctuations, characteristic of this setup. The PCM melts between points A and B. Point 4 and Point 5 mark the beginning and end of the solidification process.</p> Full article ">Figure 10
<p>Image sequence of Cycle 7, corresponding to the temperature profile shown in <a href="#energies-14-00511-f009" class="html-fig">Figure 9</a>. The time stamps underneath the images are in the format: t = mm:ss. The PCM in can be seen melting and resolidifying over the course of 2 h. The numbers in circles underneath some of the images correspond to the points of interest marked in <a href="#energies-14-00511-f009" class="html-fig">Figure 9</a>.</p> Full article ">Figure 11
<p>Power profiles (<math display="inline"><semantics> <msub> <mover accent="true"> <mi>Q</mi> <mo>˙</mo> </mover> <mrow> <mi>c</mi> <mi>h</mi> <mi>a</mi> <mi>r</mi> <mi>g</mi> <mi>e</mi> </mrow> </msub> </semantics></math> over time) of 3 melting (<b>left</b>) and solidification (<b>right</b>) processes of the same experimental parameters, showing the reproducibility of experiments. Melting and solidification took place at 10 <math display="inline"><semantics> <mi mathvariant="normal">K</mi> </semantics></math> above and below PCM melting temperature respectively at a mass flow of 18.2 <math display="inline"><semantics> <mrow> <mi>kg</mi> <mo> </mo> <msup> <mi mathvariant="normal">h</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>. Cycle 5, Cycle 6 and Cycle 7 are shown.</p> Full article ">Figure 12
<p>Power profiles (<math display="inline"><semantics> <msub> <mover accent="true"> <mi>Q</mi> <mo>˙</mo> </mover> <mrow> <mi>c</mi> <mi>h</mi> <mi>a</mi> <mi>r</mi> <mi>g</mi> <mi>e</mi> </mrow> </msub> </semantics></math> over time) of 3 melting and solidification processes of the same experimental parameters, showing the reporducibility of experiments. Melting and solidification took place at 5 <math display="inline"><semantics> <mi mathvariant="normal">K</mi> </semantics></math> above and below PCM melting temperature respectively at a mass flow of 18.2 <math display="inline"><semantics> <mrow> <mi>kg</mi> <mo> </mo> <msup> <mi mathvariant="normal">h</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>. Cycle 9, Cycle 10 and Cycle 11 are shown.</p> Full article ">Figure 13
<p>Load of melting (<b>left</b>) and solidification (<b>right</b>) of Cycle 7 shows the degree and rate of charge over the course of a cycle. The uncertainty of the measured value was calculated using Equation (<a href="#FD12-energies-14-00511" class="html-disp-formula">12</a>).</p> Full article ">Figure 14
<p>The power (<math display="inline"><semantics> <msub> <mover accent="true"> <mi>Q</mi> <mo>˙</mo> </mover> <mrow> <mi>c</mi> <mi>h</mi> <mi>a</mi> <mi>r</mi> <mi>g</mi> <mi>e</mi> </mrow> </msub> </semantics></math>) of Cycle 7 and Cycle 10 is shown over the load in order to compare the processes. Melting is shown on the left while solidification is shown on the right.</p> Full article ">Figure 15
<p>Images of biological contamination in the storage with: no HTF mass flow on the left, 15 <math display="inline"><semantics> <mrow> <mi>kg</mi> <mo> </mo> <mi mathvariant="normal">h</mi> </mrow> </semantics></math><sup>−1</sup> and 20 <math display="inline"><semantics> <mrow> <mi>kg</mi> <mo> </mo> <mi mathvariant="normal">h</mi> </mrow> </semantics></math><sup>−1</sup> in centre and on the right respectively.</p> Full article ">
25 pages, 12899 KiB  
Article
Fractional-Order Control of Grid-Connected Photovoltaic System Based on Synergetic and Sliding Mode Controllers
by Marcel Nicola and Claudiu-Ionel Nicola
Energies 2021, 14(2), 510; https://doi.org/10.3390/en14020510 - 19 Jan 2021
Cited by 12 | Viewed by 2784
Abstract
Starting with the problem of connecting the photovoltaic (PV) system to the main grid, this article presents the control of a grid-connected PV system using fractional-order (FO) sliding mode control (SMC) and FO-synergetic controllers. The article presents the mathematical model of a PV [...] Read more.
Starting with the problem of connecting the photovoltaic (PV) system to the main grid, this article presents the control of a grid-connected PV system using fractional-order (FO) sliding mode control (SMC) and FO-synergetic controllers. The article presents the mathematical model of a PV system connected to the main grid together with the chain of intermediate elements and their control systems. To obtain a control system with superior performance, the robustness and superior performance of an SMC-type controller for the control of the udc voltage in the DC intermediate circuit are combined with the advantages provided by the flexibility of using synergetic control for the control of currents id and iq. In addition, these control techniques are suitable for the control of nonlinear systems, and it is not necessary to linearize the controlled system around a static operating point; thus, the control system achieved is robust to parametric variations and provides the required static and dynamic performance. Further, by approaching the synthesis of these controllers using the fractional calculus for integration operators and differentiation operators, this article proposes a control system based on an FO-SMC controller combined with FO-synergetic controllers. The validation of the synthesis of the proposed control system is achieved through numerical simulations performed in Matlab/Simulink and by comparing it with a benchmark for the control of a grid-connected PV system implemented in Matlab/Simulink. Superior results of the proposed control system are obtained compared to other types of control algorithms. Full article
(This article belongs to the Special Issue Power Converter of Electric Machines, Renewable Energy Systems, and Transportation)
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<p>Block diagram of the main circuit diagram of the grid-connected PV system.</p> Full article ">Figure 2
<p>Block diagram of fractional-order sliding mode control (FO-SMC) and FO-synergetic control of the grid-connected PV system.</p> Full article ">Figure 3
<p>General scheme for cascade control of the grid-connected PV system.</p> Full article ">Figure 4
<p>Matlab/Simulink implementation block diagram for control of the grid-connected PV system using FO-SMC and FO-synergetic controllers.</p> Full article ">Figure 5
<p>Matlab/Simulink implementation block diagram for the FO-SMC controller.</p> Full article ">Figure 6
<p>Matlab/Simulink implementation block diagram for FO-synergetic controllers.</p> Full article ">Figure 7
<p>Time evolution of the irradiance and temperature signals type 1.</p> Full article ">Figure 8
<p>Time evolution of the <span class="html-italic">u<sub>dc</sub></span> for the irradiance and temperature signals type 1, at 10 kvar load: (<b>a</b>) FO-SMC/FO-SYN controllers; (<b>b</b>) classical PI controllers.</p> Full article ">Figure 8 Cont.
<p>Time evolution of the <span class="html-italic">u<sub>dc</sub></span> for the irradiance and temperature signals type 1, at 10 kvar load: (<b>a</b>) FO-SMC/FO-SYN controllers; (<b>b</b>) classical PI controllers.</p> Full article ">Figure 9
<p>Time evolution of the <span class="html-italic">u<sub>dc</sub></span> for the irradiance and temperature signals type 1, at 13 kvar load: (<b>a</b>) FO-SMC/FO-SYN controllers; (<b>b</b>) classical PI controllers.</p> Full article ">Figure 9 Cont.
<p>Time evolution of the <span class="html-italic">u<sub>dc</sub></span> for the irradiance and temperature signals type 1, at 13 kvar load: (<b>a</b>) FO-SMC/FO-SYN controllers; (<b>b</b>) classical PI controllers.</p> Full article ">Figure 10
<p>Time evolution of the <span class="html-italic">u<sub>dc</sub></span> for the irradiance and temperature signals type 1, at 7 kvar load: (<b>a</b>) FO-SMC/FO-SYN controllers; (<b>b</b>) classical PI controllers.</p> Full article ">Figure 10 Cont.
<p>Time evolution of the <span class="html-italic">u<sub>dc</sub></span> for the irradiance and temperature signals type 1, at 7 kvar load: (<b>a</b>) FO-SMC/FO-SYN controllers; (<b>b</b>) classical PI controllers.</p> Full article ">Figure 11
<p>Time evolution of the <span class="html-italic">u<sub>dc</sub></span> for the irradiance and temperature signals type 1, at 10 kvar load for a step variation of <span class="html-italic">u<sub>dcref</sub></span> from 500 to 550 V: (<b>a</b>) FO-SMC/FO-SYN controllers; (<b>b</b>) classical PI controllers.</p> Full article ">Figure 12
<p>Time evolution of the <span class="html-italic">i<sub>d</sub></span> and <span class="html-italic">i<sub>q</sub></span> currents.</p> Full article ">Figure 13
<p>Time evolutions of the power <span class="html-italic">P<sub>mean</sub></span> and voltage <span class="html-italic">U<sub>mean</sub></span> of the PV, duty cycle of the DC-DC converter, and modulation index of the DC-AC converter.</p> Full article ">Figure 14
<p>Time evolution of the voltage <span class="html-italic">u<sub>ab</sub></span> of the voltage source converter (VSC) controller.</p> Full article ">Figure 15
<p>Time evolution of the voltage <span class="html-italic">u<sub>a</sub></span> and current <span class="html-italic">i<sub>a</sub></span> of the main grid.</p> Full article ">Figure 16
<p>Time evolution of the power flow P between PV system and main grid.</p> Full article ">Figure 17
<p>Time evolution of the irradiance and temperature signals type 2.</p> Full article ">Figure 18
<p>Time evolution of the <span class="html-italic">u<sub>dc</sub></span> for the irradiance and temperature signals type 2, at 10 kvar load with FO-SMC/FO-SYN controllers.</p> Full article ">Figure 19
<p>Time evolution of the <span class="html-italic">u<sub>dc</sub></span> for the irradiance and temperature signals type 2, at 13 kvar load with FO-SMC/FO-SYN controllers.</p> Full article ">Figure 20
<p>Time evolution of the <span class="html-italic">u<sub>dc</sub></span> for the irradiance and temperature signals type 2, at 7 kvar load with FO-SMC/FO-SYN controllers.</p> Full article ">
25 pages, 12531 KiB  
Article
Renovation of Public Lighting Systems in Cultural Landscapes: Lighting and Energy Performance and Their Impact on Nightscapes
by Lodovica Valetti, Francesca Floris and Anna Pellegrino
Energies 2021, 14(2), 509; https://doi.org/10.3390/en14020509 - 19 Jan 2021
Cited by 21 | Viewed by 3908
Abstract
The technological innovation in the field of lighting and the need to reduce energy consumption connected to public lighting are leading many municipalities to undertake the renewal of public lighting systems, by replacing the existing luminaires with LED technologies. This renovation process is [...] Read more.
The technological innovation in the field of lighting and the need to reduce energy consumption connected to public lighting are leading many municipalities to undertake the renewal of public lighting systems, by replacing the existing luminaires with LED technologies. This renovation process is usually aimed at increasing energy efficiency and reducing maintenance costs, whist improving the lighting performance. To achieve these results, the new luminaires are often characterised by a luminous flux distribution much more downward oriented, which may remarkably influence and alter the perception of the night image of the sites. In this study the implications of the renovation of public lighting systems in terms of lighting and energy performance as well as the effects relating to the alteration of the night image, in historical contexts characterized by significant landscape value, are analysed. Results, along with demonstrating the positive effect that more sustainable and energy efficient lighting systems may have on the lighting performance and energy consumptions of public lighting systems, evidences the impact they may have on the alteration of the nocturnal image. Full article
(This article belongs to the Special Issue Smart City Lighting Systems)
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<p>(<b>a</b>) Mont Saint Michel, France, day image. (Credits: Wikipedia—Luca Deboli—originally posted to Flickr as Lun de Miel 443, CC BY 2.0). (<b>b</b>) Mont Saint Michel, France, night image. Lighting project: Light Cibles, Louis et Emmanuel Clair, 2006. (Credits: Wikipedia—Benh Lieu Song—own work, CC BY 2.5).</p> Full article ">Figure 2
<p>(<b>a</b>) View of Montepescali from the highway 1; (<b>b</b>) View of Montepescali from the Grosseto-Siena railway line. (Credits: Francesca Floris).</p> Full article ">Figure 3
<p>(<b>a</b>) Construction phases; (<b>b</b>) Identification of the main historical buildings.</p> Full article ">Figure 4
<p>Significant internal and external observation points.</p> Full article ">Figure 5
<p>(<b>a</b>) day and (<b>b</b>) night photographs taken from the external point of view E1. (<b>c</b>) day and (<b>d</b>) night photographs taken from the external point of view E2. (Credits: Francesca Floris).</p> Full article ">Figure 6
<p>(<b>a</b>) day and (<b>b</b>) night photographs taken from the internal point of view I1. (Credits: Francesca Floris).</p> Full article ">Figure 7
<p>Comparison of the measured and simulated average luminance values from the external viewpoint <b>E1</b>. (<b>a</b>) Measured luminance distribution; (<b>b</b>) simulation output.</p> Full article ">Figure 8
<p>Comparison of the measured and simulated average luminance values from the internal viewpoint <b>I1</b>. (<b>a</b>) Measured luminance distribution; (<b>b</b>) simulation output.</p> Full article ">Figure 9
<p>Road lighting classes (ex-ante and ex-post).</p> Full article ">Figure 10
<p>Observation point E1 (simulation performed using Dialux EVO software): (<b>a</b>) render of the ex-ante condition; (<b>b</b>) false colour render of the ex-ante luminance distribution. In evidence the analysed vertical surfaces and the corresponding average luminance values; (<b>c</b>) render of the ex-post condition; (<b>d</b>) false colour render of the ex-post luminance distribution. In evidence the analysed vertical surfaces, the corresponding average luminance values and the Relative Differences (RD) between the average luminance of the ex-ante and the ex-post installations.</p> Full article ">Figure 11
<p>Observation point E2 (simulation performed using Dialux EVO software): (<b>a</b>) render of the ex-ante condition; (<b>b</b>) false colour render of the ex-ante luminance distribution. In evidence the analysed vertical surfaces and the corresponding average luminance values; (<b>c</b>) render of the ex-post condition; (<b>d</b>) false colour render of the ex-post luminance distribution. In evidence the analysed vertical surfaces, the corresponding average luminance values and the Relative Differences (RD) between the average luminance of the ex-ante and the ex-post installations.</p> Full article ">Figure 12
<p>Observation point I1 (simulation performed using Dialux EVO software): (<b>a</b>) render of the ex-ante condition; (<b>b</b>) false colour render of the ex-ante luminance distribution. In evidence the analysed vertical surfaces and the corresponding average luminance values; (<b>c</b>) render of the ex-post condition; (<b>d</b>) false colour render of the ex-post luminance distribution. In evidence the analysed vertical surfaces, the corresponding average luminance values and the Relative Differences (RD) between the average luminance of the ex-ante and the ex-post installations.</p> Full article ">
16 pages, 2708 KiB  
Article
Quasi-Z-Source Inverter-Based Photovoltaic Power System Modeling for Grid Stability Studies
by Lluís Monjo, Luis Sainz, Juan José Mesas and Joaquín Pedra
Energies 2021, 14(2), 508; https://doi.org/10.3390/en14020508 - 19 Jan 2021
Cited by 21 | Viewed by 4449
Abstract
Quasi-Z-source inverters (qZSIs) are becoming a powerful power conversion technology in photovoltaic (PV) power systems because they allow energy power conversion in a single stage operation. However, they can cause system resonances and reduce system damping, which may lead to instabilities. These stability [...] Read more.
Quasi-Z-source inverters (qZSIs) are becoming a powerful power conversion technology in photovoltaic (PV) power systems because they allow energy power conversion in a single stage operation. However, they can cause system resonances and reduce system damping, which may lead to instabilities. These stability problems are well known in grid-connected voltage source converter systems but not in quasi-Z-source inverter (qZSI)-based PV power systems. This paper contributes with Matlab/Simulink and PSCAD/EMTDC models of qZSI-based PV power systems to analyze transient interactions and stability problems. These models consider all power circuits and control blocks of qZSI-based PV power systems and can be used in sensitivity studies on the influence of system parameters on stability. PV power system stability is assessed from the proposed models. The causes of instabilities are analyzed from numerical simulations and possible solutions are proposed. Full article
(This article belongs to the Special Issue Applications of Medium Voltage Direct Current in Electric Systems)
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<p>Circuit and block diagram of quasi-Z-source inverter (qZSI)-based photovoltaic (PV) power systems.</p> Full article ">Figure 2
<p>Matlab/Simulink small-signal model of qZSI-based PV power systems (symbol ∆ is omitted for sake of simplicity): (<b>a</b>) General layout; (<b>b</b>) power balance subsystem (20); (<b>c</b>) duty cycle control subsystem.</p> Full article ">Figure 3
<p>Study of the PV panel (<span class="html-italic">T</span><sub>1</sub> = 25 °C): (<b>a</b>) <span class="html-italic">i<sub>pv</sub></span>-<span class="html-italic">v<sub>pv</sub></span> characteristics; (<b>b</b>) small-signal equivalent circuit; (<b>c</b>) influence of <span class="html-italic">N<sub>p</sub></span> and <span class="html-italic">G</span> on MPP<span class="html-italic">;</span> (<b>d</b>) influence of <span class="html-italic">N<sub>s</sub></span> and <span class="html-italic">G</span> on MPP.</p> Full article ">Figure 4
<p>Equivalent circuit of qZSI with continuous current input: (<b>a</b>) Shoot-through state; (<b>b</b>) non-shoot-through state.</p> Full article ">Figure 5
<p>PSCAD/EMTDC model of the qZSI-based PV power system: (<b>a</b>) Power circuit; (<b>b</b>) control circuit.</p> Full article ">Figure 5 Cont.
<p>PSCAD/EMTDC model of the qZSI-based PV power system: (<b>a</b>) Power circuit; (<b>b</b>) control circuit.</p> Full article ">Figure 6
<p>Study of the qZSI-based PV power system with the Matlab/Simulink and PSCAD/EMTDC models: (<b>a</b>) Time domain simulations. (<b>b</b>) Eigenvalues.</p> Full article ">Figure 7
<p>Root locus of the qZSI-based PV power system eigenvalues.</p> Full article ">Figure 8
<p>Stability study with PSCAD/EMTDC simulations.</p> Full article ">
27 pages, 2297 KiB  
Article
Hybridizing Lead–Acid Batteries with Supercapacitors: A Methodology
by Xi Luo, Jorge Varela Barreras, Clementine L. Chambon, Billy Wu and Efstratios Batzelis
Energies 2021, 14(2), 507; https://doi.org/10.3390/en14020507 - 19 Jan 2021
Cited by 23 | Viewed by 5574
Abstract
Hybridizing a lead–acid battery energy storage system (ESS) with supercapacitors is a promising solution to cope with the increased battery degradation in standalone microgrids that suffer from irregular electricity profiles. There are many studies in the literature on such hybrid energy storage systems [...] Read more.
Hybridizing a lead–acid battery energy storage system (ESS) with supercapacitors is a promising solution to cope with the increased battery degradation in standalone microgrids that suffer from irregular electricity profiles. There are many studies in the literature on such hybrid energy storage systems (HESS), usually examining the various hybridization aspects separately. This paper provides a holistic look at the design of an HESS. A new control scheme is proposed that applies power filtering to smooth out the battery profile, while strictly adhering to the supercapacitors’ voltage limits. A new lead–acid battery model is introduced, which accounts for the combined effects of a microcycle’s depth of discharge (DoD) and battery temperature, usually considered separately in the literature. Furthermore, a sensitivity analysis on the thermal parameters and an economic analysis were performed using a 90-day electricity profile from an actual DC microgrid in India to infer the hybridization benefit. The results show that the hybridization is beneficial mainly at poor thermal conditions and highlight the need for a battery degradation model that considers both the DoD effect with microcycle resolution and temperate impact to accurately assess the gain from such a hybridization. Full article
(This article belongs to the Special Issue Alternative Sources of Energy Modeling, Automation, Optimal Planning and Operation)
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<p>Selected system topology: DC microgrid with a parallel, fully-active hybrid energy storage system (HESS).</p> Full article ">Figure 2
<p>Proposed HESS control scheme.</p> Full article ">Figure 3
<p>Power profile in the battery-alone ESS system.</p> Full article ">Figure 4
<p>Power filtering and voltage results for the HESS with a first-order low-pass filter (LPF) (<math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>50</mn> </mrow> </semantics></math> s).</p> Full article ">Figure 5
<p>Power filtering and voltage results for the HESS with a first-order LPF (<math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>300</mn> </mrow> </semantics></math> s).</p> Full article ">Figure 6
<p>Power filtering and voltage results for the HESS with a finite impulse response (FIR) filter (<math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <mn>420</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>ω</mi> <mi>c</mi> </msub> <mo>=</mo> <mn>0.0005</mn> <mi>π</mi> </mrow> </semantics></math> rad/sample).</p> Full article ">Figure 7
<p>Example application of the rainflow counting algorithm based on a SoC profile.</p> Full article ">Figure 8
<p>Battery cycle life vs. depth of discharge (DoD) curve.</p> Full article ">Figure 9
<p>Equivalent electrical model of the lead–acid battery [<a href="#B61-energies-14-00507" class="html-bibr">61</a>,<a href="#B62-energies-14-00507" class="html-bibr">62</a>].</p> Full article ">Figure 10
<p>Normalized cycle life with temperature in a lead–acid battery [<a href="#B38-energies-14-00507" class="html-bibr">38</a>].</p> Full article ">Figure 11
<p>Flowchart of the proposed battery life estimation method.</p> Full article ">Figure 12
<p>Two-day electricity and temperature profiles.</p> Full article ">Figure 13
<p>Ninety-day electricity and temperature profiles.</p> Full article ">Figure 14
<p>Hybridization effect on the battery operation.</p> Full article ">Figure 15
<p>Thermal resistance’s effect on battery life.</p> Full article ">Figure 16
<p>The thermal time constant’s effect on battery life.</p> Full article ">Figure 17
<p>Converter power losses’ effect on battery life.</p> Full article ">
12 pages, 809 KiB  
Article
Designing of Dynamic Spectrum Shifting in Terms of Non-Local Space-Fractional Mechanics
by Krzysztof Szajek, Wojciech Sumelka, Krzysztof Bekus and Tomasz Blaszczyk
Energies 2021, 14(2), 506; https://doi.org/10.3390/en14020506 - 19 Jan 2021
Cited by 2 | Viewed by 1987
Abstract
In this paper, the applicability of the space-fractional non-local formulation (sFCM) to design 1D material bodies with a specific dynamic eigenvalue spectrum is discussed. Such a formulated problem is based on the proper spatial distribution of material length scale, which maps the information [...] Read more.
In this paper, the applicability of the space-fractional non-local formulation (sFCM) to design 1D material bodies with a specific dynamic eigenvalue spectrum is discussed. Such a formulated problem is based on the proper spatial distribution of material length scale, which maps the information about the underlying microstructure (it is important that the material length scale is one of two additional material parameters of sFCM compared to the classical local continuum mechanics—the second one, the order of fractional continua—is treated herein as a scaling parameter only). Technically, the design process for finding adequate length scale distribution is not trivial and requires the use of an inverse optimization procedure. In the analysis, the objective function considers a subset of eigenvalues reduced to a single value based on Kreisselmeier–Steinhauser formula. It is crucial that the total number of eigenvalues considered must be smaller than the limit which comes from the ratio of the sFCM length scale to the length of the material body. Full article
(This article belongs to the Special Issue Strain Energy in Composite Structures)
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<p>General scheme and length scale parameterization: (<b>top</b>) 1D space-fractional non-local formulation (sFCM) body of length <span class="html-italic">L</span> fixed at both ends; (<b>bottom</b>) spatial length scale distribution <math display="inline"><semantics> <mrow> <msub> <mo>ℓ</mo> <mi>f</mi> </msub> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> through 1D sFCM body.</p> Full article ">Figure 2
<p>Limit spatial length scale distributions through 1D sFCM body (<math display="inline"><semantics> <mrow> <mi>L</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>) for two analysed variants.</p> Full article ">Figure 3
<p>General workflow of the optimization procedure.</p> Full article ">Figure 4
<p>Eigenvalues (<b>left column</b>) and corresponding length scale distributions (<b>right column</b>) for particular material orders <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>∈</mo> <mo>{</mo> <mn>0.6</mn> <mo>,</mo> <mn>0.8</mn> <mo>,</mo> <mn>0.9</mn> <mo>}</mo> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mo>ℓ</mo> <mi>f</mi> </msub> <mo>=</mo> <mn>0.05</mn> </mrow> </semantics></math>.</p> Full article ">Figure 5
<p>Eigenvalues (<b>left column</b>) and corresponding length scale distributions (<b>right column</b>) for particular material orders <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>∈</mo> <mo>{</mo> <mn>0.6</mn> <mo>,</mo> <mn>0.8</mn> <mo>,</mo> <mn>0.9</mn> <mo>}</mo> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mo>ℓ</mo> <mi>f</mi> </msub> <mo>=</mo> <mn>0.025</mn> </mrow> </semantics></math>.</p> Full article ">
20 pages, 4506 KiB  
Article
Modeling and Dynamic Simulation of a Hybrid Liquid Desiccant System with Non-Adiabatic Falling-Film Air-Solution Contactors for Air Conditioning Applications in Buildings
by Juan Prieto, Antonio Atienza-Márquez and Alberto Coronas
Energies 2021, 14(2), 505; https://doi.org/10.3390/en14020505 - 19 Jan 2021
Cited by 2 | Viewed by 2487
Abstract
This paper presents an experimentally validated, dynamic model of a hybrid liquid desiccant system. For this purpose, we developed new components for the air-solution contactors, which are of the non-adiabatic falling-film type with horizontal tubes (made of improved polypropylene) and the solution tanks. [...] Read more.
This paper presents an experimentally validated, dynamic model of a hybrid liquid desiccant system. For this purpose, we developed new components for the air-solution contactors, which are of the non-adiabatic falling-film type with horizontal tubes (made of improved polypropylene) and the solution tanks. We also provide new experimental correlations for both the tube-solution heat transfer coefficient and the mass transfer coefficient on the airside as a function of the air velocity. To validate the model, the results obtained from the dynamic simulations were compared with those obtained by monitoring a demonstration unit installed in a sports center in Taipei (Taiwan). Once validated, the model was used to perform a sensitivity analysis at different operational conditions, such as the inlet water temperatures in the air-solution contactors and the LiCl mass fraction at which the system operates. The results of the sensitivity analysis were used to optimize the seasonal performance in terms of comfort and energy required by the system. Compared with a conventional air-handling unit that controls air temperature and humidity, the annual energy savings of the liquid desiccant systems are 17%. Full article
(This article belongs to the Special Issue Sustainable and Efficient Impact in Building: Energy, Economic and Environmental Approach)
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<p>General scheme of the hybrid liquid desiccant system (HLDS) coupled to the vapor compression heat pump (adapted from [<a href="#B6-energies-14-00505" class="html-bibr">6</a>]).</p> Full article ">Figure 2
<p>Schematic with the elements modeled for the dynamic simulations (adapted from [<a href="#B6-energies-14-00505" class="html-bibr">6</a>]).</p> Full article ">Figure 3
<p>Calculated and measured dehumidification (<b>a</b>) and absorber heat duty (<b>b</b>).</p> Full article ">Figure 4
<p>Monthly mean ambient temperature and humidity ratio.</p> Full article ">Figure 5
<p>Monthly internal loads.</p> Full article ">Figure 6
<p>Comparison between the calculated and measured air humidity ratios (<b>a</b>) and between the calculated and measured absorber water temperatures (<b>b</b>) for a typical day.</p> Full article ">Figure 7
<p>Comparison between calculated and measured monthly energy transferred in the main components of the system during February (<b>a</b>), April (<b>b</b>), and June (<b>c</b>).</p> Full article ">Figure 8
<p>Annual heating required by the HLDS (<b>a</b>), annual cooling required by the HLDS (<b>b</b>), annual air cooling in the absorber (<b>c</b>) and the number of hours at discomfort conditions (<b>d</b>) as a function of the minimum LiCl mass fraction, the inlet water temperatures in the absorber, regenerator and the heating and cooling coil.</p> Full article ">Figure 8 Cont.
<p>Annual heating required by the HLDS (<b>a</b>), annual cooling required by the HLDS (<b>b</b>), annual air cooling in the absorber (<b>c</b>) and the number of hours at discomfort conditions (<b>d</b>) as a function of the minimum LiCl mass fraction, the inlet water temperatures in the absorber, regenerator and the heating and cooling coil.</p> Full article ">Figure 9
<p>The number of hours out of comfort conditions as a function of the heating required by the HLDS (<b>a</b>) and the cooling required by the HLDS (<b>b</b>).</p> Full article ">Figure 10
<p>Monthly results of the different thermal loads calculated from the monthly optimized control strategy.</p> Full article ">Figure 11
<p>Conventional air handling unit cycle and HLDS cycle to control humidity and temperature separately.</p> Full article ">Figure 12
<p>Monthly results of the thermal energy required by a conventional system and the HLDS at optimal working conditions.</p> Full article ">
17 pages, 1326 KiB  
Article
Analysis of Factors Influencing Energy Efficiency Based on Spatial Quantile Autoregression: Evidence from the Panel Data in China
by Jinping Zhang, Qiuru Lu, Li Guan and Xiaoying Wang
Energies 2021, 14(2), 504; https://doi.org/10.3390/en14020504 - 19 Jan 2021
Cited by 13 | Viewed by 2430
Abstract
This research mainly studies the factors influencing the efficiency of energy utilization. Firstly, by calculating Moran’sI and local indicators of spatial association (LISA) of energy efficiency of regions in mainland China, we found that energy efficiency [...] Read more.
This research mainly studies the factors influencing the efficiency of energy utilization. Firstly, by calculating Moran’sI and local indicators of spatial association (LISA) of energy efficiency of regions in mainland China, we found that energy efficiency shows obvious spatial autocorrelation and spatial clustering phenomena. Secondly, we established the spatial quantile autoregression (SQAR) model, in which the energy efficiency is the response variable with seven influence factors. The seven factors include industrial structure, resource endowment, level of economic development etc. Based on the provincial panel data (1998–2016) of mainland China (data source: China Statistical Yearbook, Statistical Yearbook of provinces), the findings indicate that level of economic development and industrial structure have a significant role in promoting energy efficient. Resource endowment, government intervention and energy efficiency show a negative correlation. However, the negative effect of government intervention is weakened with the increase of energy efficiency. Lastly, we compare the results of SQAR with that of ordinary spatial autoregression (SAR). The empirical result shows that the SQAR model is superior to SAR model in influencing factors analysis of energy efficiency. Full article
(This article belongs to the Section C: Energy Economics and Policy)
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<p>Trend of <math display="inline"><semantics> <mrow> <mi>M</mi> <mi>o</mi> <mi>r</mi> <mi>a</mi> <msup> <mi>n</mi> <mo>’</mo> </msup> <mi>s</mi> <mspace width="4pt"/> <mi>I</mi> </mrow> </semantics></math>.</p> Full article ">Figure 2
<p>Scatter plot of <math display="inline"><semantics> <mrow> <mi>M</mi> <mi>o</mi> <mi>r</mi> <mi>a</mi> <msup> <mi>n</mi> <mo>’</mo> </msup> <mi>s</mi> <mspace width="4pt"/> <mi>I</mi> </mrow> </semantics></math> of provincial energy efficiency, 2008.</p> Full article ">Figure 3
<p>Scatter plot of <math display="inline"><semantics> <mrow> <mi>M</mi> <mi>o</mi> <mi>r</mi> <mi>a</mi> <msup> <mi>n</mi> <mo>’</mo> </msup> <mi>s</mi> <mspace width="4pt"/> <mi>I</mi> </mrow> </semantics></math> of provincial energy efficiency, 2016.</p> Full article ">Figure 4
<p>Local indicators of spatial association (LISA) of provincial energy efficiency, 2008.</p> Full article ">Figure 5
<p>LISA of provincial energy efficiency, 2016.</p> Full article ">Figure 6
<p>Multicollinearity test.</p> Full article ">Figure 7
<p>Heteroscedasticity test.</p> Full article ">
12 pages, 1098 KiB  
Article
Biogas Upgrading and Ammonia Recovery from Livestock Manure Digestates in a Combined Electromethanogenic Biocathode—Hydrophobic Membrane System
by Miriam Cerrillo, Laura Burgos and August Bonmatí
Energies 2021, 14(2), 503; https://doi.org/10.3390/en14020503 - 19 Jan 2021
Cited by 20 | Viewed by 3909
Abstract
Anaerobic digestion process can be improved in combination with bioelectrochemical systems in order to recover energy and resources from digestates. An electromethanogenic microbial electrolysis cell (MEC) coupled to an ammonia recovery system based on hydrophobic membranes (ARS-HM) has been developed in order to [...] Read more.
Anaerobic digestion process can be improved in combination with bioelectrochemical systems in order to recover energy and resources from digestates. An electromethanogenic microbial electrolysis cell (MEC) coupled to an ammonia recovery system based on hydrophobic membranes (ARS-HM) has been developed in order to recover ammonia, reduce organic matter content and upgrade biogas from digested pig slurry. A lab-scale dual-chamber MEC was equipped with a cation exchange membrane (CEM) and ARS with a hydrophobic membrane in the catholyte recirculation loop, to promote ammonia migration and absorption in an acidic solution. On the other hand, an electromethanogenic biofilm was developed in the biocathode to promote the transformation of CO2 into methane. The average nitrogen transference through the CEM was of 0.36 gN m−2 h−1 with a removal efficiency of 31%, with the ARS-HM in the catholyte recirculation loop. The removal of ammonia from the cathode compartment helped to maintain a lower pH value for the electromethanogenic biomass (7.69 with the ARS-HM, against 8.88 without ARS-HM) and boosted methane production from 50 L m−3 d−1 to 73 L m−3 d−1. Results have shown that the integration of an electromethanogenic MEC with an ARS-HM allows for the concomitant recovery of energy and ammonia from high strength wastewater digestates. Full article
(This article belongs to the Special Issue Anaerobic Digestion of Organic Waste: State of the Art and Future Perspectives and Challenges)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Schematic diagram of the set-up of the dual-chamber microbial electrolysis cells (MEC) with an electromethanogenic cathode and the ammonia recovery system based on hydrophobic membranes (ARS-HM) connected in the catholyte recirculation loop.</p> Full article ">Figure 2
<p>Current density production of the MEC and chemical oxygen demand (COD) and ammonium nitrogen (NH<sub>4</sub><sup>+</sup>-N) removal efficiencies, in the periods of MEC operation with disconnected and connected hydrophobic membrane system (ARS-HM).</p> Full article ">Figure 3
<p>Accumulated NH<sub>4</sub><sup>+</sup>-N in the acidic solution during the ARS-HM operation.</p> Full article ">Figure 4
<p>Comparison of the average daily charge production (<span class="html-italic">Q</span><sup>−</sup>) to the transport of charge in the form of ammonium (<span class="html-italic">Q</span><sup>+</sup>) transferred to the cathode compartment and the charge <span class="html-italic">Q</span><sup>−</sup> derived to methane production in the biocathode.</p> Full article ">
24 pages, 2442 KiB  
Review
A Review of Recent Advances in Emerging Alternative Heating and Cooling Technologies
by Mubarak Ismail, Metkel Yebiyo and Issa Chaer
Energies 2021, 14(2), 502; https://doi.org/10.3390/en14020502 - 19 Jan 2021
Cited by 25 | Viewed by 6065
Abstract
The heating and cooling industry underpins everything we do, e.g., manufacturing, commercial and residential applications. Many of these applications invariably use mechanical refrigeration technologies, consequently contributing significantly to the environmental impacts of the refrigeration, air conditioning, and heat pump (RACHP) industry both through [...] Read more.
The heating and cooling industry underpins everything we do, e.g., manufacturing, commercial and residential applications. Many of these applications invariably use mechanical refrigeration technologies, consequently contributing significantly to the environmental impacts of the refrigeration, air conditioning, and heat pump (RACHP) industry both through direct and indirect emissions of CO2. To reduce these emissions, research and development worldwide aim to improve the performance of conventional systems and the development of new refrigeration technologies of potentially much lower environmental impacts. As we transition to a low carbon economy, there are sizable environmental and economic benefits from developing and using efficient, innovative, low carbon heating and cooling technologies that reduce energy use and carbon emissions. This paper provides an up-to-date and comprehensive critical review and evaluation of recent advances in emerging alternative heating and cooling technologies that have the potential to reduce the environmental impacts of refrigeration in the RACHP sector. The paper highlights the basic working principle of operation, its main applications, the challenges and opportunities in penetrating the market. The paper also highlights further research and development needed to accelerate the development and adoption of these alternative refrigeration technologies by the sector. Most of the technologies reviewed have a Technology Readiness Level (TRL) of 3–4, except electrocaloric technology which is less ready compared to its counterparts with a TRL of 1–2 at this stage. Furthermore, most technologies have capacities ranging between a few kilowatts to a maximum of 7 kW with a coefficient of performance COP between 1 and 10 reported in the literature. Full article
(This article belongs to the Special Issue Alternative and Emerging Cooling and Heating Technologies)
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<p>Schematic showing the basic working principle of Magnetic Refrigeration.</p> Full article ">Figure 2
<p>Schematics showing the basic working principle of Electrocaloric Refrigeration.</p> Full article ">Figure 3
<p>Schematics showing the basic working principle of thermoelectric Refrigeration.</p> Full article ">Figure 4
<p>Schematics showing the basic working principle of Thermoacoustic Refrigeration.</p> Full article ">Figure 5
<p>Schematics showing the basic working principle of Stirling Refrigeration.</p> Full article ">Figure 6
<p>Schematic showing the basic working principle of Barocaloric Refrigeration.</p> Full article ">Figure 7
<p>Schematics showing the basic working principle of Elastocaloric Refrigeration based on information obtained from Shape Memory Alloys by Lagoudas [<a href="#B51-energies-14-00502" class="html-bibr">51</a>].</p> Full article ">
27 pages, 6560 KiB  
Article
Polish Energy Transition 2040: Energy Mix Optimization Using Grey Wolf Optimizer
by Damian Hasterok, Rui Castro, Marcin Landrat, Krzysztof Pikoń, Markus Doepfert and Hugo Morais
Energies 2021, 14(2), 501; https://doi.org/10.3390/en14020501 - 19 Jan 2021
Cited by 27 | Viewed by 5194
Abstract
Poland is facing demanding challenges to achieve a sustainable energy mix in the near future. Crucial and tough decisions must be made about the direction of the national energy economy, safety, and environmental impact. Considering the electricity and heating demand forecast, this paper [...] Read more.
Poland is facing demanding challenges to achieve a sustainable energy mix in the near future. Crucial and tough decisions must be made about the direction of the national energy economy, safety, and environmental impact. Considering the electricity and heating demand forecast, this paper proposes an optimization model based on the Grey Wolf Optimizer meta-heuristic to support the definition of ideal energy mix considering the investment and operational costs. The proposed methodology uses the present energy mix in Poland (the most recent values are from 2017) to calibrate the model implemented in the EnergyPLAN tool. Afterwards, EnergyPLAN relates to an optimization process allowing the identification of the most convenient energy mix in 2040 in Poland. The values obtained are compared with those proposed by Polish public entities showing advantage regarding the global costs of the project nevertheless respecting the same levels of CO2 and the energy import and export balance. The expected savings can achieve 1.3 billion euros a year and more than 8 million tonnes of CO2 emission reduction. Sensitivity analysis considering the decrease of the global cost of renewables-based sources is also presented. Full article
(This article belongs to the Special Issue Novel Developments in Energy Resources Management, Distribution Systems, Microgrids and Energy Communities)
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<p>Capacity forecast of technologies for years 2020–2040 [<a href="#B6-energies-14-00501" class="html-bibr">6</a>].</p> Full article ">Figure 2
<p>Electricity production forecast of technologies for years 2020–2040 [<a href="#B6-energies-14-00501" class="html-bibr">6</a>].</p> Full article ">Figure 3
<p>Flowchart of the Polish energy system.</p> Full article ">Figure 4
<p>Sensitivity analysis methodology.</p> Full article ">Figure 5
<p>Diagram of the optimization process and the interaction between MATLAB (orange box) and EnergyPLAN (blue box).</p> Full article ">Figure 6
<p>Comparison of costs for EPP 2040 and GWO forecasts.</p> Full article ">Figure 7
<p>Sensitivity analysis graph of total annual costs with decreased renewable energy sources (RES) costs.</p> Full article ">Figure 8
<p>Total annual costs in the electricity sector considering RES prices reduction.</p> Full article ">Figure 9
<p>Sensitivity analysis of installed capacity with decreased RES costs.</p> Full article ">Figure 10
<p>The capacity of RES after sensitivity analysis.</p> Full article ">Figure 11
<p>Sensitivity analysis graph of CO<sub>2</sub> emission and total annual costs (TAC) with carbon tax variation.</p> Full article ">Figure 12
<p>TAC with carbon tax variation after sensitivity analysis.</p> Full article ">Figure 13
<p>Sensitivity analysis graph of electricity production with carbon tax variation.</p> Full article ">Figure 14
<p>RES installed capacity with carbon tax variation after sensitivity analysis.</p> Full article ">Figure 15
<p>Sensitivity analysis graph of CO<sub>2</sub> emission and TAC with the natural gas price increase.</p> Full article ">Figure 16
<p>Sensitivity analysis graph of electricity TAC with the natural gas price increase.</p> Full article ">Figure 17
<p>Sensitivity analysis graph of electricity production with the natural gas price increase.</p> Full article ">Figure 18
<p>RES capacity with the natural gas price increase after sensitivity analysis.</p> Full article ">
20 pages, 3200 KiB  
Article
Continuous Production of Lipids with Microchloropsis salina in Open Thin-Layer Cascade Photobioreactors on a Pilot Scale
by Torben Schädler, Anna-Lena Thurn, Thomas Brück and Dirk Weuster-Botz
Energies 2021, 14(2), 500; https://doi.org/10.3390/en14020500 - 18 Jan 2021
Cited by 13 | Viewed by 3058
Abstract
Studies on microalgal lipid production as a sustainable feedstock for biofuels and chemicals are scarce, particularly those on applying open thin-layer cascade (TLC) photobioreactors under dynamic diurnal conditions. Continuous lipid production with Microchloropsis salina was studied in scalable TLC photobioreactors at 50 m [...] Read more.
Studies on microalgal lipid production as a sustainable feedstock for biofuels and chemicals are scarce, particularly those on applying open thin-layer cascade (TLC) photobioreactors under dynamic diurnal conditions. Continuous lipid production with Microchloropsis salina was studied in scalable TLC photobioreactors at 50 m2 pilot scale, applying a physically simulated Mediterranean summer climate. A cascade of two serially connected TLC reactors was applied, promoting biomass growth under nutrient-replete conditions in the first reactor, while inducing the accumulation of lipids via nitrogen limitation in the second reactor. Up to 4.1 g L−1 of lipids were continuously produced at productivities of up to 0.27 g L−1 d−1 (1.8 g m2 d−1) at a mean hydraulic residence time of 2.5 d in the first reactor and 20 d in the second reactor. Coupling mass balances with the kinetics of microalgal growth and lipid formation enabled the simulation of phototrophic process performances of M. salina in TLC reactors in batch and continuous operation at the climate conditions studied. This study demonstrates the scalability of continuous microalgal lipid production in TLC reactors with M. salina and provides a TLC reactor model for the realistic simulation of microalgae lipid production processes after re-identification of the model parameters if other microalgae and/or varying climate conditions are applied. Full article
(This article belongs to the Special Issue Conception, Modelling, Control, and Intensification of Photobioreactors Applied to the Valorization of Microalgae)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>A thin-layer cascade (TLC) photobioreactor made of pond liner with an illuminated surface area of 50 m<sup>2</sup>. Two 12 m × 2 m channels were each connected with an open retention tank (<b>A</b>), a centrifugal pump (<b>B</b>), and an inlet module (<b>C</b>) for continuous circulation of the microalgal suspension. The reactor was placed in a glass hall of the TUM AlgaeTec-Center, with application of physically reproduced light and air conditions in accordance with 12 June 2012 in Almería, Spain. The yellow color of the microalgal suspension was caused by nitrogen limitation to induce the accumulation of lipids in <span class="html-italic">M. salina</span>.</p> Full article ">Figure 2
<p>(<b>a</b>) Mean daily specific growth rates (○) as a function of integral photosynthetic photon flux density I<sup>*</sup> measured during 4 independent nutrient-replete batch processes of 10 days in a thin-layer cascade reactor (A = 8 m<sup>2</sup>) with <span class="html-italic">M. salina</span> under a physically simulated Mediterranean summer climate. Error bars represent 95% confident intervals. Equation (18) was fitted to experimental growth rates via nonlinear regression (―). The grey lines (<span style="color:#BFBFBF">―</span>) represent the 95% confidence interval of the identified Equation (18). (<b>b</b>) Mean daily specific growth rates (○) of <span class="html-italic">M. salina</span> as a function of urea concentration and integral photosynthetic photon flux density I<sup>*</sup> in a continuously operated thin-layer cascade reactor (A = 8 m<sup>2</sup>, D = 0.3 d<sup>−1</sup>) with an influent urea concentration of 1.2 g L<sup>−1</sup> under a physically simulated Mediterranean summer climate.</p> Full article ">Figure 3
<p>(<b>a</b>) Specific lipid-free growth rate <math display="inline"><semantics> <mrow> <msub> <mi>μ</mi> <mrow> <mi>X</mi> <mo>−</mo> <mi>L</mi> </mrow> </msub> </mrow> </semantics></math> of <span class="html-italic">M. salina</span> as a function of intracellular nitrogen quota <math display="inline"><semantics> <mrow> <msub> <mi>Q</mi> <mi>N</mi> </msub> </mrow> </semantics></math> in a TLC reactor (A = 8 m<sup>2</sup>) using a physical simulation of a Mediterranean summer climate. Equation (20) was fitted to the measured lipid-free growth rates and nitrogen quota via nonlinear regression (―). (<b>b</b>) Equation (21) was fitted to the measured daily lipid formation rates <math display="inline"><semantics> <mrow> <msub> <mi>q</mi> <mi>L</mi> </msub> </mrow> </semantics></math> as a function of the lipid quota <math display="inline"><semantics> <mrow> <msub> <mi>Q</mi> <mi>L</mi> </msub> </mrow> </semantics></math> via nonlinear regression (―). The grey lines (<span style="color:#BFBFBF">―</span>) represent the 95% confidence interval of both fits.</p> Full article ">Figure 4
<p>Continuous lipid production with <span class="html-italic">M. salina</span> in two serially connected thin-layer cascade reactors under a physically simulated Mediterranean summer climate. The first TLC reactor (8 m<sup>2</sup>, 55 L, ○) was supplied with fresh feed medium and was operated at a hydraulic residence time of 2.5 d. The second TLC reactor (50 m<sup>2</sup>, 330 L, <span style="color:#E53418">△</span>) was supplied from the first reactor at a hydraulic residence time of 20 d. (<b>a</b>) Cell dry weight concentration (CDW, error bars omitted for visual clarity, average relative standard deviation 0.5%), (<b>b</b>) lipid concentration (<math display="inline"><semantics> <mrow> <msub> <mi>c</mi> <mi>L</mi> </msub> </mrow> </semantics></math>), (<b>c</b>) lipid quota in dry weight, and (<b>d</b>) lipid space–time yield (STY<sub>Lipid</sub>) of the first (─) and second TLC (<span style="color:#E53418">─</span>) and overall lipid STY of the reactor cascade (<span style="color:#0065BD">─</span>). The vertical line indicates the initiation of continuous operation.</p> Full article ">Figure 5
<p>Batch processes with <span class="html-italic">M. salina</span> in a thin-layer cascade reactor under a physically simulated Mediterranean summer climate, applying (<b>a</b>) nutrient-replete and (<b>b</b>) nitrogen-limited growth conditions. Experimentally measured cell dry weight (CDW, error bars omitted for visual clarity, average relative standard deviation 0.7%) concentration (○), lipid concentration (△), and urea concentration (<span style="color:gray">□</span>), and simulated CDW concentration (<span style="color:#ED7D31">─</span>), lipid concentration (--), and urea concentration (<span style="color:#BFBFBF">--</span>).</p> Full article ">Figure 6
<p>(<b>a</b>) Cell dry weight concentration (CDW, error bars omitted for visual clarity, average relative standard deviation 0.5%), and (<b>b</b>) lipid concentration in a continuous process with <span class="html-italic">M. salina</span> using two serially connected thin-layer cascade reactors under a physically simulated Mediterranean summer climate. The first TLC reactor (8 m<sup>2</sup>, 55 L) was supplied with fresh feed medium and was operated at a hydraulic residence time of 2.5 d. The second TLC reactor (50 m<sup>2</sup>, 330 L) was supplied from the first reactor at a hydraulic residence time of 20 d. Experimental results of the first (○) and second reactor (<span style="color:#ED7D31">○</span>), and simulation of CDW and lipid concentration in the first (─) and second reactor (<span style="color:#ED7D31">─</span>). The vertical line indicates initiation of continuous operation.</p> Full article ">Figure 7
<p>Experimentally observed (white bars) and simulated (red bars) steady-state cell dry weight (CDW) concentrations with <span class="html-italic">M. salina</span> in continuously operated thin-layer cascade photobioreactors at dilution rates of 0.31 d<sup>−1</sup>, 0.4 d<sup>−1</sup>, 0.5 d<sup>−1</sup><sub>,</sub> and 0.6 d<sup>−1</sup> with urea concentrations in the feed medium of 1.2 g L<sup>−1</sup>, 1.5 g L<sup>−1</sup>, 1.2 g L<sup>−1</sup><sub>,</sub> and 0.9 g L<sup>−1</sup>, respectively. Error bars represent single standard deviations of diurnally deviating CDW concentrations during the steady state.</p> Full article ">
22 pages, 9082 KiB  
Article
Monofacial and Bifacial Micro PV Installation as Element of Energy Transition—The Case of Poland
by Piotr Olczak, Małgorzata Olek, Dominika Matuszewska, Artur Dyczko and Tomasz Mania
Energies 2021, 14(2), 499; https://doi.org/10.3390/en14020499 - 18 Jan 2021
Cited by 38 | Viewed by 4549
Abstract
The several government subsidies available in Poland contributed to an increased interest in PV installations. Installed PV capacity increased from 100 MW in 2016 up to 2682.7 MW in July 2020. In 2019 alone, 104,000 microinstallations (up to 50 kWp) were installed in [...] Read more.
The several government subsidies available in Poland contributed to an increased interest in PV installations. Installed PV capacity increased from 100 MW in 2016 up to 2682.7 MW in July 2020. In 2019 alone, 104,000 microinstallations (up to 50 kWp) were installed in Poland. The paper determines the energy gain and the associated reduction of CO2 emissions for two types of solar installation located in Poland. The monofacial solar modules with a power of 5.04 kWp (located in Leki) and bifacial solar modules with a power of 6.1 kWp (located in Bydgoszcz). Both installations use mono-crystalline Si-based 1st generation PV cells. With comparable insolation, a bifacial installation produces approx. 10% (for high insolation) to 28% (for low insolation) more energy than a monofacial PV installation. Avoided annual CO2 emission in relation to the installation capacity ranges from 0.58 to 0.64 Mg/kWp for monofacial and from 0.68 to 0.74 Mg/kWp for bifacial and is on average approx. 16% higher for bifacial installations. Cost-benefit analyses were made. For different electricity prices, the NPV for monofacial and bifacial was determined. Full article
(This article belongs to the Special Issue Technologies Conducive to Low Green House Gas Emission)
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<p>Yearly horizontal insolation in Poland calculated per province’s capital city. KP province—Kuyavian-Pomeranian; M province–Lesser Poland. Source own study based on [<a href="#B18-energies-14-00499" class="html-bibr">18</a>].</p> Full article ">Figure 2
<p>Annual values of energy sent to the grid in relation to the installed capacity and the annual share of energy sent to the grid in relation to the consumed, in the Lesser Poland province 1 June 2019–31 May 2020. Source own study based on [<a href="#B32-energies-14-00499" class="html-bibr">32</a>].</p> Full article ">Figure 3
<p>Annual values of energy sent to the grid in relation per kWp to insolation and the maximum annual self-consumed (max. self-consumed/insolation) share, in the Lesser Poland province, 1 June 2019–31 May 2020. Source own study based on [<a href="#B32-energies-14-00499" class="html-bibr">32</a>].</p> Full article ">Figure 4
<p>Annual values of energy sent to the grid in relation to the installed capacity and the annual share of energy sent to the grid in relation to the consumed, in the Kuyavian-Pomeranian province, 2019. Source: own study based on [<a href="#B32-energies-14-00499" class="html-bibr">32</a>].</p> Full article ">Figure 5
<p>Annual values of energy sent to the grid in relation to insolation and the maximum annual self-consumed (max. self-consumed/insolation) share in the Kuyavian-Pomeranian province, 2019. Source own study based on [<a href="#B32-energies-14-00499" class="html-bibr">32</a>].</p> Full article ">Figure 6
<p>Panels on the roof of a single-family building in Leki.</p> Full article ">Figure 7
<p>Setting up 5 × 4 panels on the ground in Bydgoszcz.</p> Full article ">Figure 8
<p>Energy production in the PV installation Leki and energy: added to the grid, consumed and Energy consumption in the building, June 2020.</p> Full article ">Figure 9
<p>Self-consumption coefficient (SC) and self-sufficiency coefficient (SS) for several days of June 2020.</p> Full article ">Figure 10
<p>Self-consumption coefficient (SC) and self-sufficiency coefficient (SS) as a function of energy production per hour. June 2020.</p> Full article ">Figure 11
<p>Daily energy production in PV installation (Leki), June 2020.</p> Full article ">Figure 12
<p>Daily energy production in PV installation (Bydgoszcz), June 2020.</p> Full article ">Figure 13
<p>Comparison of insolation values varied from locations for June in the last 11 years. Source own study based on [<a href="#B18-energies-14-00499" class="html-bibr">18</a>,<a href="#B33-energies-14-00499" class="html-bibr">33</a>,<a href="#B57-energies-14-00499" class="html-bibr">57</a>].</p> Full article ">Figure 14
<p>Comparison of the insolation values for both locations for June against the Typical Reference Year data and different location of the surface. (TRY_H–Typical Reference Year–Horizontal Surface, TRY_S45-Typical Reference Year–south directed surface titled 45°, TRY_SW30-Typical Reference Year–south-west directed surface titled 30° [<a href="#B18-energies-14-00499" class="html-bibr">18</a>].</p> Full article ">Figure 15
<p>Comparison of insolation values for both locations for individual days in June. (References to detail figures are marked-energy production results for both installations.)</p> Full article ">Figure 16
<p>Comparison of the unit results of energy production from installations for 12 and 13 June.</p> Full article ">Figure 17
<p>Comparison of the unit results of energy production in an installation, for: (<b>a</b>) 15 June; (<b>b</b>) 22 June.</p> Full article ">Figure 18
<p>Daily reduction of CO<sub>2</sub> emissions as a function of insolation.</p> Full article ">Figure 19
<p>Unit (investment) cost of CO<sub>2</sub> emission reduction as a function of CO<sub>2</sub> emission factor in the national grid and emissions related to the production of panels: (<b>a</b>) Leki; (<b>b</b>) Bydgoszcz.</p> Full article ">Figure 20
<p>Unit (investment) cost of CO<sub>2</sub> emission reduction as a function of CO<sub>2</sub> emission factor in the national grid and emissions related to the production of Leki panels with subsidy.</p> Full article ">Figure 21
<p>Net Present Value (NPV) as a function of electricity price and discount rate value: (<b>a</b>) for Leki; (<b>b</b>) for Bydgoszcz. ElP = 0.15 EUR/kWh is actual electricity price in Poland.</p> Full article ">Figure 22
<p>Difference of Net Present Value (diff.NPV) Leki-Bydgoszcz as a function of electricity price and discount rate value: (<b>a</b>) excluding subsidies; (<b>b</b>) including subsidies. ElP = 0.15 EUR/kWh is actual electricity price in Poland.</p> Full article ">
16 pages, 5013 KiB  
Article
Horizontally Assembled Trapezoidal Piezoelectric Cantilevers Driven by Magnetic Coupling for Rotational Energy Harvester Applications
by Yonghyeon Na, Min-Seon Lee, Jung Woo Lee and Young Hun Jeong
Energies 2021, 14(2), 498; https://doi.org/10.3390/en14020498 - 18 Jan 2021
Cited by 8 | Viewed by 2611
Abstract
Horizontally assembled trapezoidal piezoelectric cantilevers driven by magnetic coupling were fabricated for rotational energy harvester applications. A dodecagonal rigid frame with an attached array of six trapezoidal cantilevers served as a stator for electrical power generation. A rotor disk with six permanent magnets [...] Read more.
Horizontally assembled trapezoidal piezoelectric cantilevers driven by magnetic coupling were fabricated for rotational energy harvester applications. A dodecagonal rigid frame with an attached array of six trapezoidal cantilevers served as a stator for electrical power generation. A rotor disk with six permanent magnets (PMs) interacted magnetically with the counterpart cantilever’s tip-mass PMs of the stator by rotational motion. Each trapezoidal piezoelectric cantilever beam was designed to operate in a transverse mode that utilizes a planar Ag/Pd electrode printed onto lead zirconate titanate (PZT) piezoelectric thick film. The optimized distance between a pair of PMs of the rotor and the stator was evaluated as approximately 10 mm along the same vertical direction to make the piezoelectric cantilever beam most deflectable without the occurrence of cracks. The theoretically calculated resistance torque was maximized at 46 mN·m for the optimized trapezoidal piezoelectric cantilever. The proposed energy harvester was also demonstrated for wind energy harvester applications. Its harvested output power reached a maximum of approximately 22 mW at a wind speed of 10 m/s under a resistive load of 30 kΩ. The output performance of the proposed energy harvester makes it possible to power numerous low-power applications such as smart sensor systems. Full article
(This article belongs to the Section A3: Wind, Wave and Tidal Energy)
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<p>Image of a custom-made wind tunnel to evaluate the characteristics of a wind energy harvester.</p> Full article ">Figure 2
<p>Illustrated schematic: (<b>a</b>) top-view; (<b>b</b>) side-view image of a trapezoidal piezoelectric bimorph cantilever interacting with the rotor disk for magneto-piezo-elastic energy conversion; (<b>c</b>) image of the Ag/Pd-electrode printed trapezoidal piezoelectric thick film and the cantilever beam with the piezoelectric thick film attached to it.</p> Full article ">Figure 3
<p>Illustrated schematic of: (<b>a</b>) the test equipment for the evaluation of the power generation capability of the proposed energy harvester; (<b>b</b>) a top-view image of the dodecagonal stator and a bottom-view of the disk rotor; (<b>c</b>) optimized PM configuration of the energy harvester with two magnetically coupled PM pairs in a static state.</p> Full article ">Figure 4
<p>Cylindrical coordinate system of the rotor’s PM and stator’s tip-mass PM, and the resultant experimental data: (<b>a</b>) illustrated schematic of TPBC and PM of rotor; (<b>b</b>) the deflection behavior of TPBC with variation of the height, ∆<span class="html-italic">r</span>; (<b>c</b>) the deflection behavior of TPBC with the rotor’s rotation speed from 80 rpm to 280 rpm.</p> Full article ">Figure 5
<p>Output power of a trapezoidal piezoelectric bimorph cantilever with variation of: (<b>a</b>) the radius gap of ∆<span class="html-italic">r</span>, the rotor’s height of <span class="html-italic">h</span>; (<b>b</b>) rotation speed of the rotor.</p> Full article ">Figure 6
<p>Load-deflection plot of the trapezoidal piezoelectric bimorph cantilever and testing image.</p> Full article ">Figure 7
<p>Calculated resistance torque of the rotary energy harvester under the effects of an attractive and a repulsive magnetic field according to the parameters: (<b>a</b>) height (<span class="html-italic">h</span>); (<b>b</b>) rotation speed (rpm) of the rotor disk.</p> Full article ">Figure 8
<p>Images of the wind energy harvester with the magnetically coupled trapezoidal piezoelectric cantilever array at the dodecagonal frame of the stator: (<b>a</b>) Top-view; (<b>b</b>) isometric-view.</p> Full article ">Figure 9
<p>Output characteristics of the parallel electric connected piezoelectric cantilever array as a function of the wind speed when it ranged from 4 m/s to 10 m/s: (<b>a</b>) Output current; (<b>b</b>) output voltage; (<b>c</b>) output power.</p> Full article ">
15 pages, 2373 KiB  
Review
An Integrated Approach to Convert Lignocellulosic and Wool Residues into Balanced Fertilisers
by Filippo Marchelli, Giorgio Rovero, Massimo Curti, Elisabetta Arato, Barbara Bosio and Cristina Moliner
Energies 2021, 14(2), 497; https://doi.org/10.3390/en14020497 - 18 Jan 2021
Cited by 12 | Viewed by 3818
Abstract
Valorising biomass waste and producing renewable energy or materials is the aim of several conversion technologies. In this work, we consider two residues from different production chains: lignocellulosic residues from agriculture and wool residues from sheep husbandry. These materials are produced in large [...] Read more.
Valorising biomass waste and producing renewable energy or materials is the aim of several conversion technologies. In this work, we consider two residues from different production chains: lignocellulosic residues from agriculture and wool residues from sheep husbandry. These materials are produced in large quantities, and their disposal is often costly and challenging for farmers. For their valorisation, we focus on slow pyrolysis for the former and water hydrolysis for the latter, concisely presenting the main literature related to these two processes. Pyrolysis produces the C-rich biochar, suitable for soil amending. Hydrolysis produces a N-rich fertiliser. We demonstrate how these two processes could be fruitfully integrated, as their products can be flexibly mixed to produce fertilisers. This solution would allow the achievement of balanced and tuneable ratios between C and N and the enhancement of the mechanical properties. We propose scenarios for this combined valorisation and for its coupling with other industries. As a result, biomass waste would be returned to the field, following the principles of circular economy. Full article
(This article belongs to the Special Issue Environmental and Energetic Valorization of Renewable Resources)
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<p>The proposed integrated approach to valorise agricultural and wool residues.</p> Full article ">Figure 2
<p>Trend of the <span class="html-italic">C/N</span> ratio for different feedstocks pyrolysed at different temperatures (refer to <a href="#energies-14-00497-t001" class="html-table">Table 1</a> for the acronyms and values).</p> Full article ">Figure 3
<p>Trend of the <span class="html-italic">C/N</span> ratio as a function of the converted residual wool, for two values of biomass mass flow rate.</p> Full article ">Figure 4
<p>Trend of the <span class="html-italic">C/N</span> ratio as a function of the biochar in the fertiliser, for two values of fed mass of wool per day.</p> Full article ">Figure 5
<p>Possible scheme of an integrated process.</p> Full article ">
28 pages, 42725 KiB  
Article
Energy and Economic Investigation of a Biodiesel-Fired Engine for Micro-Scale Cogeneration
by Diego Perrone, Angelo Algieri, Pietropaolo Morrone and Teresa Castiglione
Energies 2021, 14(2), 496; https://doi.org/10.3390/en14020496 - 18 Jan 2021
Cited by 14 | Viewed by 2983
Abstract
The work aims at investigating the techno-economic performance of a biodiesel micro combined heat and power (CHP) system for residential applications. The CHP unit is based on a direct-injection compression ignition engine providing 6.7 kWel and 11.3 kWth. A 0D [...] Read more.
The work aims at investigating the techno-economic performance of a biodiesel micro combined heat and power (CHP) system for residential applications. The CHP unit is based on a direct-injection compression ignition engine providing 6.7 kWel and 11.3 kWth. A 0D model is developed and validated to characterise the behaviour of the biodiesel-fired engine at full and partial load in terms of efficiency, fuel consumption, and emissions. Furthermore, non-dimensional polynomial correlations are proposed to foresee the performance of biodiesel-fuelled engines for micro-CHP applications at partial loads. Afterwards, the CHP system is adopted to satisfy the electric and thermal demand of domestic users in Southern Italy. To this purpose, a parametric analysis is performed considering a different number of apartments and operating strategies (electric-driven and thermal-driven). A bi-variable optimisation based on the primary energy saving (PES) index and payback period (PBT) permits selecting the thermal-driven strategy and five apartments as the most suitable solution. The optimal PBT and PES are equal to 5.3 years and 22.4%, respectively. The corresponding annual thermal self-consumption reaches 81.3% of the domestic request, and the thermal surplus is lower than 8%. Finally, a sensitivity analysis is adopted to define the influence of the costs of energy vectors and a cogeneration unit on the economic feasibility of the biodiesel CHP system. The analysis highlights that the investigated apparatus represents an attractive option to satisfy the energy requests in micro-scale applications, providing valuable energy and economic advantages compared to traditional energy production. Full article
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Number of papers on biodiesel-fired internal combustion engines from 2000 to 2020. Automotive and small power applications (red bar), combined heat and power (CHP) generation (blue bar). Authors elaboration on Scopus data [<a href="#B23-energies-14-00496" class="html-bibr">23</a>]. Document search criterion refers to “Article title, Abstract, Keywords” menu and adopts “Biodiesel” AND “internal combustion engines” keywords for ICE applications. “Biodiesel” AND “CHP” AND NOT “biodiesel production” AND NOT “hydrogen” AND NOT “gasification” are used for CHP applications.</p> Full article ">Figure 2
<p>Micro-CHP system layout and energy fluxes.</p> Full article ">Figure 3
<p>Comparison between numerical and experimental results in terms of brake thermal efficiency and specific fuel consumption.</p> Full article ">Figure 4
<p>Comparison between numerical and experimental results: (<b>a</b>) heat rate release; (<b>b</b>) cylinder pressure.</p> Full article ">Figure 5
<p>Comparison between numerical and experimental results in terms of NO<sub>x</sub> emissions.</p> Full article ">Figure 6
<p>Energy balance of the biodiesel-fired micro-CHP system.</p> Full article ">Figure 7
<p>CHP performances in terms of normalised parameters and comparison with experimental data: (<b>a</b>) electric efficiency; (<b>b</b>) exhaust thermal efficiency; (<b>c</b>) cooling circuit thermal efficiency; (<b>d</b>) fuel consumption. Authors elaboration on experimental literature data [<a href="#B31-energies-14-00496" class="html-bibr">31</a>,<a href="#B32-energies-14-00496" class="html-bibr">32</a>,<a href="#B84-energies-14-00496" class="html-bibr">84</a>].</p> Full article ">Figure 7 Cont.
<p>CHP performances in terms of normalised parameters and comparison with experimental data: (<b>a</b>) electric efficiency; (<b>b</b>) exhaust thermal efficiency; (<b>c</b>) cooling circuit thermal efficiency; (<b>d</b>) fuel consumption. Authors elaboration on experimental literature data [<a href="#B31-energies-14-00496" class="html-bibr">31</a>,<a href="#B32-energies-14-00496" class="html-bibr">32</a>,<a href="#B84-energies-14-00496" class="html-bibr">84</a>].</p> Full article ">Figure 8
<p>Daily profiles of the energy demand of a single apartment during a typical day in winter, summer, and intermediate seasons in Southern Italy: (<b>a</b>) electric; (<b>b</b>) thermal; Authors elaboration on literature data [<a href="#B86-energies-14-00496" class="html-bibr">86</a>].</p> Full article ">Figure 9
<p><span class="html-italic">PES</span> index as a function of the number of apartment under the thermal- and electric driven strategies.</p> Full article ">Figure 10
<p>Influence of the number of apartments on the system’s economic feasibility: (<b>a</b>) net present values; (<b>b</b>) payback periods. Thermal-driven strategy.</p> Full article ">Figure 11
<p><span class="html-italic">PBT</span> as a function of the <span class="html-italic">PES</span> index for different apartments.</p> Full article ">Figure 12
<p>Comparison between thermal- and electric-driven strategies: (<b>a</b>) thermal self-consumption and integration; (<b>b</b>) thermal surplus; (<b>c</b>) electric self-consumption and integration; (<b>d</b>) electric surplus.</p> Full article ">Figure 12 Cont.
<p>Comparison between thermal- and electric-driven strategies: (<b>a</b>) thermal self-consumption and integration; (<b>b</b>) thermal surplus; (<b>c</b>) electric self-consumption and integration; (<b>d</b>) electric surplus.</p> Full article ">Figure 13
<p>Hourly energy balance of the micro-CHP system for thermal-driven strategy: (<b>a</b>) thermal exchange in winter; (<b>b</b>) electric exchange in winter; (<b>c</b>) thermal exchange in summer; (<b>d</b>) electric exchange in summer; (<b>e</b>) thermal exchange in intermediate seasons; (<b>f</b>) electric exchange in intermediate seasons.</p> Full article ">Figure 14
<p>Monthly energy balances for the micro-CHP system with thermal-driven strategy and five apartments: (<b>a</b>) thermal balance; (<b>b</b>) electric balance.</p> Full article ">Figure 15
<p>Fuel consumption, CO<sub>2</sub>, and NO<sub>x</sub> emissions on a monthly basis for the micro-CHP system. Five apartments and thermal-driven strategy.</p> Full article ">Figure 16
<p>Payback period maps: (<b>a</b>) influence of the specific cost of CHP and biodiesel; (<b>b</b>) effect of the cost of electric and thermal energy.</p> Full article ">
22 pages, 26453 KiB  
Article
Effect of the Foresight Horizon on Computation Time and Results Using a Regional Energy Systems Optimization Model
by Jessica Thomsen, Noha Saad Hussein, Arnold Dolderer and Christoph Kost
Energies 2021, 14(2), 495; https://doi.org/10.3390/en14020495 - 18 Jan 2021
Cited by 10 | Viewed by 2874
Abstract
Due to the high complexity of detailed sector-coupling models, a perfect foresight optimization approach reaches complexity levels that either requires a reduction of covered time-steps or very long run-times. To mitigate these issues, a myopic approach with limited foresight can be used. This [...] Read more.
Due to the high complexity of detailed sector-coupling models, a perfect foresight optimization approach reaches complexity levels that either requires a reduction of covered time-steps or very long run-times. To mitigate these issues, a myopic approach with limited foresight can be used. This paper examines the influence of the foresight horizon on local energy systems using the model DISTRICT. DISTRICT is characterized by its intersectoral approach to a regionally bound energy system with a connection to the superior electricity grid level. It is shown that with the advantage of a significantly reduced run-time, a limited foresight yields fairly similar results when the input parameters show a stable development. With unexpected, shock-like events, limited foresight shows more realistic results since it cannot foresee the sudden parameter changes. In general, the limited foresight approach tends to invest into generation technologies with low variable cost and avoids investing into demand reduction or efficiency with high upfront costs as it cannot compute the benefits over the time span necessary for full cost recovery. These aspects should be considered when choosing the foresight horizon. Full article
(This article belongs to the Special Issue Municipal Energy System Planning: New Approaches, Applications and Future Research Needs)
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<p>Illustration of the perfect foresight approach.</p> Full article ">Figure 2
<p>Illustration of the myopic recursive approach, where the optimization problem is divided into several smaller optimization problems that are optimized consecutively without information about future periods.</p> Full article ">Figure 3
<p>Model region including electricity grid, demand regions, and spot market connection area (<b>left</b>) and heating grid, demand regions, and central region (<b>right</b>).</p> Full article ">Figure 4
<p>Time-step selection for the optimization years (2020, 2025, 2030, and 2035).</p> Full article ">Figure 5
<p>Average CO<sub>2</sub> emission factor in the electricity mix.</p> Full article ">Figure 6
<p>Average day-ahead spot market price for TECH and EEX_SHOCK scenarios.</p> Full article ">Figure 7
<p>Annual heat demand for the regarded system, assuming the entire building stock has the same building standard.</p> Full article ">Figure 8
<p>Cost difference between the two approaches over the optimization period.</p> Full article ">Figure 9
<p>Installed generation capacities in the EEX_SHOCK scenario.</p> Full article ">Figure 10
<p><b>Left</b> picture displays retrofit decisions of the perfect foresight and the <b>right</b> picture of the myopic approach.</p> Full article ">Figure 11
<p>Heat generation in the RETRO scenario for the two expansion approaches.</p> Full article ">Figure 12
<p>Cost difference between the two approaches over the optimization period for the RETRO scenario with high CO<sub>2</sub> prices.</p> Full article ">Figure 13
<p>The relative difference between the results of the myopic and the perfect foresight approach in each scenario, the difference is displayed as value = [result perfect foresight − result myopic]/result perfect foresight.</p> Full article ">Figure 14
<p>Duration of the optimization runs for the complete time horizon in hours.</p> Full article ">Figure A1
<p>EnEV standards according to [<a href="#B29-energies-14-00495" class="html-bibr">29</a>].</p> Full article ">
25 pages, 2875 KiB  
Article
Lifetime Assessment of PILC Cables with Regard to Thermal Aging Based on a Medium Voltage Distribution Network Benchmark and Representative Load Scenarios in the Course of the Expansion of Distributed Energy Resources
by Martin Zapf, Tobias Blenk, Ann-Catrin Müller, Hermann Pengg, Ivana Mladenovic and Christian Weindl
Energies 2021, 14(2), 494; https://doi.org/10.3390/en14020494 - 18 Jan 2021
Cited by 11 | Viewed by 3961
Abstract
The decentralized feed-ins from distributed energy resources (DER) represent a significant change in the manner in which the power grid is used. If this leads to high loads on electrical equipment, its aging can be accelerated. This applies in particular with regard to [...] Read more.
The decentralized feed-ins from distributed energy resources (DER) represent a significant change in the manner in which the power grid is used. If this leads to high loads on electrical equipment, its aging can be accelerated. This applies in particular with regard to the thermal aging of older generations of power cables, namely paper insulated lead covered (PILC) cables. This type of power cable can still be found frequently in medium voltage (MV) networks. If aging of these cables is significantly accelerated in the presence of DER, distribution system operators (DSO) could face unplanned premature cable failures and a high replacement demand and costs. Therefore, this paper investigates the thermal aging of PILC cables in a MV distribution network benchmark for different load scenarios, using standardized load profiles and representative expansion scenarios for wind power and photovoltaics plants in particularly affected network areas in Germany. A main objective of this paper is to present a methodology for estimating the thermal degradation of PILC cables. An approach is used to draw simplified conclusions from the loading of cables to their conductor or insulation temperature. For this purpose, mainly Joule losses are considered. In addition, thermal time constants are used for the heating and cooling processes. Based on the insulation temperature, thermal aging is determined using the Arrhenius law or the Montsinger rule. However, it is important to note that there is an urgent need for research on reference data in this area. For this reason, the results of the lifetime estimation presented in this paper should only be considered as an approximation if the selected reference data from the literature for the aging model are actually applicable. The lifetime assessment is performed for a highly utilized line segment of the network benchmark. Accordingly, extreme values are examined. Different operational control strategies of DSO to limit cable utilization are investigated. The results show that the expansion of DER can lead to a short but high cable utilization, although the average utilization does not increase or increases only slightly. This can lead to significantly lower cable lifetimes. The possible influence of these temporarily high loads is shown by comparing the resulting cable lifetime with previous situations without DER. It is also shown that DSO could already reduce excessive aging of PILC cables by preventing overloads in a few hours of a year. In addition to these specific results, general findings on the network load due to the influence of DER are obtained, which are of interest for congestion management. Full article
(This article belongs to the Section A1: Smart Grids and Microgrids)
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<p>Temperature curve during heating (<b>left</b>) and cooling (<b>right</b>).</p> Full article ">Figure 2
<p>Thermal network models, following [<a href="#B26-energies-14-00494" class="html-bibr">26</a>].</p> Full article ">Figure 3
<p>Aging acceleration factor according to Arrhenius reaction rate theory (B = 15,000) and Montsinger rule (<math display="inline"><semantics> <mrow> <msub> <mi>T</mi> <mi>d</mi> </msub> <mo>=</mo> <mn>6</mn> <mo> </mo> <mo>°</mo> <mi mathvariant="normal">C</mi> </mrow> </semantics></math>) at a reference hottest point temperature of 110 °C.</p> Full article ">Figure 4
<p>Lifetime regarding different reference data and aging models.</p> Full article ">Figure 5
<p>Topology of European MV distribution network benchmark, following [<a href="#B48-energies-14-00494" class="html-bibr">48</a>].</p> Full article ">Figure 6
<p>Voltage-dependent reactive power control for power generators in the medium-voltage grid.</p> Full article ">Figure 7
<p>Load profile H0 for households, following [<a href="#B51-energies-14-00494" class="html-bibr">51</a>].</p> Full article ">Figure 8
<p>Load profile G0 for commercial/industry, following [<a href="#B51-energies-14-00494" class="html-bibr">51</a>].</p> Full article ">Figure 9
<p>Annual load duration curve of feed-in profiles from [<a href="#B53-energies-14-00494" class="html-bibr">53</a>] for wind power and PV plants.</p> Full article ">Figure 10
<p>Annual load duration curves of line segment 2 for different load scenarios.</p> Full article ">Figure 11
<p>Correlation of the load of line segment 2 with the network load of feeder 1 for the scenarios wind power-dominated (<b>left</b>) and without DER (<b>right</b>).</p> Full article ">Figure 12
<p>Correlation of the load of line segment 2 with the network load of the entire MV distribution network benchmark for the scenarios wind power-dominated (<b>left</b>) and without DER (<b>right</b>).</p> Full article ">Figure 13
<p>Correlation of the load of line segment 5 with the network load (<b>left</b>) and the sum of all withdrawals from loads and network losses (<b>right</b>) from Feeder 1.</p> Full article ">Figure 14
<p>Comparison of the static and dynamic conductor temperature calculation method.</p> Full article ">Figure 15
<p>Calculated lifetime for the exemplary PILC cable of line segment 2 regarding different reference data and aging models if a maximum utilization of 120% is allowed (typical age for replacement from [<a href="#B3-energies-14-00494" class="html-bibr">3</a>]).</p> Full article ">Figure 16
<p>Calculated Lifetime for the exemplary PILC cable of line segment 2 regarding different reference data and aging models if a maximum utilization of 100% is allowed (typical age for replacement from [<a href="#B3-energies-14-00494" class="html-bibr">3</a>]).</p> Full article ">
15 pages, 15477 KiB  
Article
A DC Microgrid System for Powering Remote Areas
by Tri Ardriani, Pekik Argo Dahono, Arwindra Rizqiawan, Erna Garnia, Pungky Dwi Sastya, Ahmad Husnan Arofat and Muhammad Ridwan
Energies 2021, 14(2), 493; https://doi.org/10.3390/en14020493 - 18 Jan 2021
Cited by 12 | Viewed by 4440
Abstract
DC microgrid has been gaining popularity as solution as a more efficient and simpler power system especially for remote areas, where the main grid has yet to be built. This paper proposes a DC microgrid system based on renewable energy sources that employs [...] Read more.
DC microgrid has been gaining popularity as solution as a more efficient and simpler power system especially for remote areas, where the main grid has yet to be built. This paper proposes a DC microgrid system based on renewable energy sources that employs decentralized control and without communication between one grid point and another. It can be deployed as an individual isolated unit or to form an expandable DC microgrid through DC bus for better reliability and efficiency. The key element of the proposed system is the power conditioner system (PCS) that works as an interface between energy sources, storage system, and load. PCS consists of modular power electronics devices and a power management unit, which controls power delivery to the AC load and the grid as well as the storage system charging and discharging sequence. Prototypes with 3 kWp solar PV and 13.8 kWh energy storage were developed and adopt a pole-mounted structure for ease of transportation and installation that are important in remote areas. This paper presents measurement results under several conditions of the developed prototypes. The evaluation shows promising results and a solid basis for electrification in remote areas. Full article
(This article belongs to the Special Issue Microgrids: Planning, Protection and Control)
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<p>The proposed DC microgrid system.</p> Full article ">Figure 2
<p>(<b>a</b>) Block diagram of a power conditioner system (PCS). (<b>b</b>) Converters topology employed in PCS.</p> Full article ">Figure 3
<p>Flowchart of the PCS management unit.</p> Full article ">Figure 4
<p>Multi-point DC microgrid configuration.</p> Full article ">Figure 5
<p>Power flow in multi-point DC microgrid system.</p> Full article ">Figure 6
<p>Solar tower: An implementation of PCS.</p> Full article ">Figure 7
<p>PCS field evaluation with distant loads.</p> Full article ">Figure 8
<p>Inverter evaluation: (<b>a</b>) Efficiency vs. load, (<b>b</b>) voltage and current THD vs. load, and (<b>c</b>) battery and inverter voltage vs. load.</p> Full article ">Figure 8 Cont.
<p>Inverter evaluation: (<b>a</b>) Efficiency vs. load, (<b>b</b>) voltage and current THD vs. load, and (<b>c</b>) battery and inverter voltage vs. load.</p> Full article ">Figure 9
<p>Field testing results: (<b>a</b>) Voltage drop on cable, and (<b>b</b>) losses on cable.</p> Full article ">Figure 10
<p>Battery charging and discharging process with varying load current.</p> Full article ">
24 pages, 1227 KiB  
Article
Thermoelectric Generation with Impinging Nano-Jets
by Fatih Selimefendigil, Hakan F. Oztop and Mikhail A. Sheremet
Energies 2021, 14(2), 492; https://doi.org/10.3390/en14020492 - 18 Jan 2021
Cited by 5 | Viewed by 2115
Abstract
In this study, thermoelectric generation with impinging hot and cold nanofluid jets is considered with computational fluid dynamics by using the finite element method. Highly conductive CNT particles are used in the water jets. Impacts of the Reynolds number of nanojet stream combinations [...] Read more.
In this study, thermoelectric generation with impinging hot and cold nanofluid jets is considered with computational fluid dynamics by using the finite element method. Highly conductive CNT particles are used in the water jets. Impacts of the Reynolds number of nanojet stream combinations (between (Re1, Re2) = (250, 250) to (1000, 1000)), horizontal distance of the jet inlet from the thermoelectric device (between (r1, r2) = (−0.25, −0.25) to (1.5, 1.5)), impinging jet inlet to target surfaces (between w2 and 4w2) and solid nanoparticle volume fraction (between 0 and 2%) on the interface temperature variations, thermoelectric output power generation and conversion efficiencies are numerically assessed. Higher powers and efficiencies are achieved when the jet stream Reynolds numbers and nanoparticle volume fractions are increased. Generated power and efficiency enhancements 81.5% and 23.8% when lowest and highest Reynolds number combinations are compared. However, the power enhancement with nanojets using highly conductive CNT particles is 14% at the highest solid volume fractions as compared to pure water jet. Impacts of horizontal location of jet inlets affect the power generation and conversion efficiency and 43% variation in the generated power is achieved. Lower values of distances between the jet inlets to the target surface resulted in higher power generation while an optimum value for the highest efficiency is obtained at location zh = 2.5ws. There is 18% enhancement in the conversion efficiency when distances at zh = ws and zh = 2.5ws are compared. Finally, polynomial type regression models are obtained for estimation of generated power and conversion efficiencies for water-jets and nanojets considering various values of jet Reynolds numbers. Accurate predictions are obtained with this modeling approach and it is helpful in assisting the high fidelity computational fluid dynamics simulations results. Full article
(This article belongs to the Special Issue Numerical Simulation of Convective Heat Transfer)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>3D schematic view of confined nanojet impinging system with TEG module (<b>a</b>) and 2D representation with boundary conditions (<b>b</b>).</p> Full article ">Figure 2
<p>Mesh independence test results for two different jet stream Reynolds number combinations ( (r<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, r<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (1, 1), z<math display="inline"><semantics> <msub> <mrow/> <mi>h</mi> </msub> </semantics></math> = 3w<math display="inline"><semantics> <msub> <mrow/> <mi>s</mi> </msub> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mspace width="3.33333pt"/> <mo>=</mo> <mspace width="3.33333pt"/> <mn>0.02</mn> </mrow> </semantics></math>).</p> Full article ">Figure 2 Cont.
<p>Mesh independence test results for two different jet stream Reynolds number combinations ( (r<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, r<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (1, 1), z<math display="inline"><semantics> <msub> <mrow/> <mi>h</mi> </msub> </semantics></math> = 3w<math display="inline"><semantics> <msub> <mrow/> <mi>s</mi> </msub> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mspace width="3.33333pt"/> <mo>=</mo> <mspace width="3.33333pt"/> <mn>0.02</mn> </mrow> </semantics></math>).</p> Full article ">Figure 3
<p>Comparison of local Nu number for various locations along the hot surface at Reynolds number of 100 with Ref. [<a href="#B45-energies-14-00492" class="html-bibr">45</a>] (<b>a</b>) and average Nu number comparison for slot jet impingement cooling considering two values of aspect ratio at Reynolds number of 500 with Ref. [<a href="#B46-energies-14-00492" class="html-bibr">46</a>] (<b>b</b>).</p> Full article ">Figure 3 Cont.
<p>Comparison of local Nu number for various locations along the hot surface at Reynolds number of 100 with Ref. [<a href="#B45-energies-14-00492" class="html-bibr">45</a>] (<b>a</b>) and average Nu number comparison for slot jet impingement cooling considering two values of aspect ratio at Reynolds number of 500 with Ref. [<a href="#B46-energies-14-00492" class="html-bibr">46</a>] (<b>b</b>).</p> Full article ">Figure 4
<p>Comparison of generated TEG power with the present code and available results in Ref. [<a href="#B47-energies-14-00492" class="html-bibr">47</a>].</p> Full article ">Figure 5
<p>Effects of different jet stream Reynolds number combinations on the variation of streamlines within the channels, electric potential and temperature distributions within the TEG module ( (r<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>,r<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (1,1), z<math display="inline"><semantics> <msub> <mrow/> <mi>h</mi> </msub> </semantics></math> = 3w<math display="inline"><semantics> <msub> <mrow/> <mi>s</mi> </msub> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics></math>).</p> Full article ">Figure 5 Cont.
<p>Effects of different jet stream Reynolds number combinations on the variation of streamlines within the channels, electric potential and temperature distributions within the TEG module ( (r<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>,r<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (1,1), z<math display="inline"><semantics> <msub> <mrow/> <mi>h</mi> </msub> </semantics></math> = 3w<math display="inline"><semantics> <msub> <mrow/> <mi>s</mi> </msub> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics></math>).</p> Full article ">Figure 6
<p>Impacts of hot jet stream Reynolds number on the variation of interface temperatures of the cold and hot side (mid-axis) (<b>a</b>,<b>b</b>) and generated TEG power (<b>c</b>) (Re<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math> = 500, (r<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>,r<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (1,1), z<math display="inline"><semantics> <msub> <mrow/> <mi>h</mi> </msub> </semantics></math> = 3w<math display="inline"><semantics> <msub> <mrow/> <mi>s</mi> </msub> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics></math>).</p> Full article ">Figure 6 Cont.
<p>Impacts of hot jet stream Reynolds number on the variation of interface temperatures of the cold and hot side (mid-axis) (<b>a</b>,<b>b</b>) and generated TEG power (<b>c</b>) (Re<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math> = 500, (r<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>,r<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (1,1), z<math display="inline"><semantics> <msub> <mrow/> <mi>h</mi> </msub> </semantics></math> = 3w<math display="inline"><semantics> <msub> <mrow/> <mi>s</mi> </msub> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics></math>).</p> Full article ">Figure 7
<p>Effects of different jet stream Reynolds number combinations on the distribution of hot (<b>a</b>) and cold (<b>b</b>) interface temperatures (mid-axis) ((r<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, r<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (1, 1), z<math display="inline"><semantics> <msub> <mrow/> <mi>h</mi> </msub> </semantics></math> = 3w<math display="inline"><semantics> <msub> <mrow/> <mi>s</mi> </msub> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics></math>).</p> Full article ">Figure 8
<p>Generated powers (<b>a</b>) and efficiencies of the TEG device (<b>b</b>) with varying jet stream Reynolds number combinations ((r<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, r<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (1, 1), z<math display="inline"><semantics> <msub> <mrow/> <mi>h</mi> </msub> </semantics></math> = 3w<math display="inline"><semantics> <msub> <mrow/> <mi>s</mi> </msub> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics></math>).</p> Full article ">Figure 9
<p>Effects of varying jet-stream inlet horizontal location combinations on the distribution of streamlines in the mid-plane channels (<b>a</b>–<b>c</b>) and electric potential variations in the TEG device (<b>d</b>–<b>f</b>) ((Re<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, Re<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (500, 500), z<math display="inline"><semantics> <msub> <mrow/> <mi>h</mi> </msub> </semantics></math> = 3w<math display="inline"><semantics> <msub> <mrow/> <mi>s</mi> </msub> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics></math>).</p> Full article ">Figure 10
<p>Impacts of jet inlet horizontal location combinations on the variation of the interface temperatures at the cold (<b>a</b>) and hot side (<b>b</b>) of the TEG module ((Re<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, Re<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (500, 500), z<math display="inline"><semantics> <msub> <mrow/> <mi>h</mi> </msub> </semantics></math> = 3w<math display="inline"><semantics> <msub> <mrow/> <mi>s</mi> </msub> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics></math>).</p> Full article ">Figure 11
<p>Generated powers (<b>a</b>,<b>b</b>) and efficiency (<b>c</b>) variation of the TEG device with respect to changes in the jet inlet horizontal location combinations ((Re<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, Re<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (500, 500), z<math display="inline"><semantics> <msub> <mrow/> <mi>h</mi> </msub> </semantics></math> = 3w<math display="inline"><semantics> <msub> <mrow/> <mi>s</mi> </msub> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics></math>).</p> Full article ">Figure 12
<p>Impacts of distance from the inlet to target surface on the variation of interface temperatures at the cold (<b>a</b>) and hot (<b>b</b>) side ((Re<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, Re<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (500, 500), (r<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, r<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (1, 1), <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics></math>).</p> Full article ">Figure 13
<p>Generated power (<b>a</b>) and efficiency (<b>b</b>) of the TEG module with varying distance from the inlet to target surface ((Re<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, Re<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (500, 500), (r<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, r<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (1,1), <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics></math>).</p> Full article ">Figure 14
<p>Impacts of solid nanoparticle volume fractions of CNT on the variation of cold and hot interface temperatures ((Re<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, Re<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (500, 500), (r<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, r<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (1, 1), z<math display="inline"><semantics> <msub> <mrow/> <mi>h</mi> </msub> </semantics></math> = 3w<math display="inline"><semantics> <msub> <mrow/> <mi>s</mi> </msub> </semantics></math>).</p> Full article ">Figure 15
<p>Generated power (<b>a</b>) and efficiency (<b>b</b>) of the TEG module with varying solid nanoparticle volume fractions of CNT and for different inlet horizontal distance of the hot jet stream ((Re<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, Re<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (500, 500), r<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math> = 1, z<math display="inline"><semantics> <msub> <mrow/> <mi>h</mi> </msub> </semantics></math> = 3w<math display="inline"><semantics> <msub> <mrow/> <mi>s</mi> </msub> </semantics></math>).</p> Full article ">Figure 15 Cont.
<p>Generated power (<b>a</b>) and efficiency (<b>b</b>) of the TEG module with varying solid nanoparticle volume fractions of CNT and for different inlet horizontal distance of the hot jet stream ((Re<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>, Re<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>) = (500, 500), r<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math> = 1, z<math display="inline"><semantics> <msub> <mrow/> <mi>h</mi> </msub> </semantics></math> = 3w<math display="inline"><semantics> <msub> <mrow/> <mi>s</mi> </msub> </semantics></math>).</p> Full article ">Figure 16
<p>Polynomial surface fit (<b>a</b>) and residual (<b>b</b>) plot for the generated TEG power with varying jet stream Reynolds numbers at <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics></math>.</p> Full article ">Figure 17
<p>Contour plot (<b>a</b>) and residual (<b>b</b>) obtained with the polynomial fit for the efficiency of the TEG device with varying jet stream Reynolds numbers at <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics></math>.</p> Full article ">Figure 17 Cont.
<p>Contour plot (<b>a</b>) and residual (<b>b</b>) obtained with the polynomial fit for the efficiency of the TEG device with varying jet stream Reynolds numbers at <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics></math>.</p> Full article ">
29 pages, 911 KiB  
Article
Investigating the Asymmetric Effect of Economic Growth on Environmental Quality in the Next 11 Countries
by Gideon Kwaku Minua Ampofo, Jinhua Cheng, Edwin Twum Ayimadu and Daniel Akwasi Asante
Energies 2021, 14(2), 491; https://doi.org/10.3390/en14020491 - 18 Jan 2021
Cited by 13 | Viewed by 2819
Abstract
This study investigates the asymmetric cointegration and causal relationships between economic growth, carbon emissions, and energy consumption in the next eleven (11) countries over the period 1972–2013. The nonlinear autoregressive distributed lag (NARDL) bounds testing approach and nonpragmatic Granger causality tests are employed. [...] Read more.
This study investigates the asymmetric cointegration and causal relationships between economic growth, carbon emissions, and energy consumption in the next eleven (11) countries over the period 1972–2013. The nonlinear autoregressive distributed lag (NARDL) bounds testing approach and nonpragmatic Granger causality tests are employed. This research’s empirical results have entrenched vital relationships that have significant policy implications. We affirm nonlinear cointegration among the variables in Bangladesh, Iran, Turkey, and Vietnam. The long-run asymmetric effect outcomes indicate a definite boom in economic growth, significantly increases carbon emission in Turkey, and a decline in Vietnam. Additionally, a positive shock to energy consumption significantly increases the carbon emission in Bangladesh, Iran, and Turkey, but a decrease in emissions in Vietnam. Findings from the Wald test reveal a long-run asymmetric effect between carbon emission and economic growth in Bangladesh, Iran, and Vietnam, and for Iran, an asymmetric short-run impact. Long-run and short-run asymmetric effects between carbon emission and energy consumption in Bangladesh and Iran. In terms of asymmetric causality results, bidirectional causality between carbon emission and economic growth was noted in Bangladesh and Turkey, and a unidirectional causality from economic growth to carbon emission in Egypt and South Korea. Energy consumption causes carbon emission in Bangladesh, Egypt, Pakistan, South Korea, and not vice versa. We determined a bidirectional asymmetric causality relationship between carbon emission and energy consumption in Vietnam and a unidirectional causality link from carbon emissions to Turkey’s energy consumption. Full article
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Figure 1

Figure 1
<p>Dynamic multiple adjustments of carbon emission to a unitary change of economic growth in Bangladesh.</p> Full article ">Figure 2
<p>Dynamic multiple adjustments of carbon emission to a unit change in economic growth in Iran.</p> Full article ">Figure 3
<p>Dynamic multiple adjustments of carbon emission to a unit variation of economic growth in Turkey.</p> Full article ">Figure 4
<p>Dynamic multiple adjustments of carbon emission to a unitary variation of economic growth in Vietnam.</p> Full article ">Figure 5
<p>Plot of cumulative sum of recursive residuals for Bangladesh.</p> Full article ">Figure 6
<p>Plot of cumulative sum squares of recursive residuals for Bangladesh.</p> Full article ">Figure 7
<p>Plot of cumulative sum of recursive residuals for Iran.</p> Full article ">Figure 8
<p>Plot of cumulative sum squares of recursive for residuals for Iran.</p> Full article ">Figure 9
<p>Plot of cumulative sum of recursive residuals for Turkey.</p> Full article ">Figure 10
<p>Plot of cumulative sum of squares recursive residuals for Turkey.</p> Full article ">Figure 11
<p>Plot of cumulative sum of recursive residuals for Vietnam.</p> Full article ">Figure 12
<p>Plot of cumulative sum of squares recursive residuals for Vietnam.</p> Full article ">
13 pages, 2276 KiB  
Article
Oxidation Stability of Natural Ester Modified by Means of Fullerene Nanoparticles
by Dominika Szcześniak and Piotr Przybylek
Energies 2021, 14(2), 490; https://doi.org/10.3390/en14020490 - 18 Jan 2021
Cited by 16 | Viewed by 3369
Abstract
Increasing environmental demands influence the requirements for devices and materials used in the power industry. One example is a power transformer and an electro-insulating liquid used in it. In order to meet these requirements, electro-insulating liquids should be characterized by, inter alia, high [...] Read more.
Increasing environmental demands influence the requirements for devices and materials used in the power industry. One example is a power transformer and an electro-insulating liquid used in it. In order to meet these requirements, electro-insulating liquids should be characterized by, inter alia, high biodegradability and good fire properties. One of such liquids is natural ester. However, its oxidation stability is low in comparison to mineral oil and demands improvement, which can be achieved by the addition of an antioxidant. The authors of this work used fullerene nanoparticles for that purpose. Pure natural ester samples were prepared, and samples with two concentrations of fullerene, 250 mg/L and 500 mg/L in natural ester. All these samples were aged in a thermal oxidation process. Thereafter, the aging properties of all the samples were compared to assess the oxidation stability of modified liquids. Moreover, the electrical properties of prepared insulating liquids were investigated to assess if fullerene deteriorates these properties after aging process. Based on the obtained results, it was proved that the aging process slowed down in the case of both fullerene concentrations in ester. The acid number of natural ester modified using fullerene was lower than in the case of pure liquid. Full article
(This article belongs to the Special Issue Nanoparticles and Nanofluids for Electrical Power and Energy Systems)
►▼ Show Figures

Figure 1

Figure 1
<p>Chemical structure of natural ester molecule, based on [<a href="#B1-energies-14-00490" class="html-bibr">1</a>].</p> Full article ">Figure 2
<p>The colour change of natural ester FR3 during fullerene dissolution process; I, II, III, IV, V, VI correspond with the absorbance spectra in <a href="#energies-14-00490-f003" class="html-fig">Figure 3</a>.</p> Full article ">Figure 3
<p>Absorbance spectra in UV-VIS range measured during fullerene dissolution in natural ester I—pure natural ester; II, III, IV, V, VI—the following stages of fullerene dissolution for the samples taken from the top of the bottle, VII—the samples taken from the bottom.</p> Full article ">Figure 4
<p>The results of acid number (<b>a</b>), water content (<b>b</b>), interfacial tension (<b>c</b>) and kinematic viscosity (<b>d</b>) of natural ester (NE) and nanofluids (NFs) of different fullerene concentrations before and after the aging process.</p> Full article ">Figure 5
<p>The results of breakdown voltage (<b>a</b>), electrical permittivity (<b>b</b>), volume resistivity (<b>c</b>), and dissipation factor (<b>d</b>) of natural ester (NE) and nanofluids (NFs) of different fullerene concentration before and after the aging process.</p> Full article ">
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