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Energies, Volume 12, Issue 6 (March-2 2019) – 222 articles

Cover Story (view full-size image): Tidal stream turbines operate in some of the most energetic seas, and consequently must withstand highly dynamic mechanical loading. At present, very few studies have reported on the operational performance of full-scale devices, providing little knowledge on the suitability of design tools used by turbine developers to quantify mechanical loading. The rotor loading characteristics of a full-scale turbine were measured and compared with theoretical predictions, with focus on the effects that the ambient environment has on device performance. View this paper.
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18 pages, 969 KiB  
Article
Software Architectures for Smart Grid System—A Bibliographical Survey
by Ramesh Ananthavijayan, Prabhakar Karthikeyan Shanmugam, Sanjeevikumar Padmanaban, Jens Bo Holm-Nielsen, Frede Blaabjerg and Viliam Fedak
Energies 2019, 12(6), 1183; https://doi.org/10.3390/en12061183 - 26 Mar 2019
Cited by 15 | Viewed by 6354
Abstract
Smart grid software interconnects multiple Engineering disciplines (power systems, communication, software and hardware technology, instrumentation, big data, etc.). The software architecture is an evolving concept in smart grid systems, in which system architecture development is a challenging process. The architecture has to realize [...] Read more.
Smart grid software interconnects multiple Engineering disciplines (power systems, communication, software and hardware technology, instrumentation, big data, etc.). The software architecture is an evolving concept in smart grid systems, in which system architecture development is a challenging process. The architecture has to realize the complex legacy power grid systems and cope with current Information and Communication Technologies (ICT). The distributed generation in a smart grid environment expects the software architecture to be distributed and to enable local control. Smart grid architecture should also be modular, flexible, and adaptable to technology upgrades. In this paper, the authors have made a comprehensive review of architectures for smart grids. An in depth analysis of layered and agent-based architectures based on the National Institute of Standards and Technology (NIST) conceptual model is presented. Also presented is a set of smart grid Reference Architectures dealing with cross domain technology. Full article
(This article belongs to the Special Issue Advanced Signal Processing Techniques Applied to Power Systems Control and Analysis)
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<p>Smart grid Architectural view.</p> Full article ">Figure 2
<p>NIST reference model for smart grid architecture [<a href="#B32-energies-12-01183" class="html-bibr">32</a>].</p> Full article ">
27 pages, 2608 KiB  
Article
A Horizon Optimization Control Framework for the Coordinated Operation of Multiple Distributed Energy Resources in Low Voltage Distribution Networks
by Konstantinos Kotsalos, Ismael Miranda, Nuno Silva and Helder Leite
Energies 2019, 12(6), 1182; https://doi.org/10.3390/en12061182 - 26 Mar 2019
Cited by 15 | Viewed by 4669
Abstract
In recent years, the installation of residential Distributed Energy Resources (DER) that produce (mainly rooftop photovoltaics usually bundled with battery system) or consume (electric heat pumps, controllable loads, electric vehicles) electric power is continuously increasing in Low Voltage (LV) distribution networks. Several technical [...] Read more.
In recent years, the installation of residential Distributed Energy Resources (DER) that produce (mainly rooftop photovoltaics usually bundled with battery system) or consume (electric heat pumps, controllable loads, electric vehicles) electric power is continuously increasing in Low Voltage (LV) distribution networks. Several technical challenges may arise through the massive integration of DER, which have to be addressed by the distribution grid operator. However, DER can provide certain degree of flexibility to the operation of distribution grids, which is generally performed with temporal shifting of energy to be consumed or injected. This work advances a horizon optimization control framework which aims to efficiently schedule the LV network’s operation in day-ahead scale coordinating multiple DER. The main objectives of the proposed control is to ensure secure LV grid operation in the sense of admissible voltage bounds and rated loading conditions for the secondary transformer. The proposed methodology leans on a multi-period three-phase Optimal Power Flow (OPF) addressed as a nonlinear optimization problem. The resulting horizon control scheme is validated within an LV distribution network through multiple case scenarios with high microgeneration and electric vehicle integration providing admissible voltage limits and avoiding unnecessary active power curtailments. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management 2018)
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<p>Configuration for interconnection of MV with the LV grid.</p> Full article ">Figure 2
<p>Structure of optimization variables; discriminated by state vector, control variables and the auxiliary variables per each time step.</p> Full article ">Figure 3
<p>Cost function functions. (<b>a</b>) cost function for utilizing a BESS-owned by the DSO; (<b>b</b>) cost of active power curtailment; (<b>c</b>) cost function of reactive power control for microgeneration; (<b>d</b>) cost function of an EV with V2G operation.</p> Full article ">Figure 4
<p>The IEEE European LV benchmark network. Fifty-five consumers are connected to this case network.</p> Full article ">Figure 5
<p>Data profiles: (<b>a</b>) load profiles; and (<b>b</b>) micro-generation profiles using seasonal (e.g., summer profiles) and regional data.</p> Full article ">Figure 6
<p>Data profiles: (<b>a</b>) trips in progress along a week. and (<b>b</b>) probability density function for EV charging demand, used for the dumb charging scenarios (source: [<a href="#B57-energies-12-01182" class="html-bibr">57</a>]).</p> Full article ">Figure 7
<p>State of the trip for Electric Vehicles used along the simulation period. Profiles were extracted for a summer week day.</p> Full article ">Figure 8
<p>Incremental integration of EV scenarios: (<b>a</b>) minimum voltage range over all phases and buses and (<b>b</b>) secondary transformer loading for each case of EV integration (the increase in loading is observed up to 120%).</p> Full article ">Figure 9
<p>Incremental integration of EV scenarios: (<b>a</b>) minimum voltage range over all phases and buses and (<b>b</b>) secondary transformer loading for each case of EV integration (the increase in loading is observable up to 120%).</p> Full article ">Figure 10
<p>Incremental integration of PV, Cases 01–03: (<b>a</b>) Case 01; (<b>b</b>) Case 01, solely APC was selected within the controller; (<b>c</b>) Case 02; (<b>d</b>) Case 03.</p> Full article ">Figure 11
<p>Control set-points and SoC derived by the MACOPF for centralized three-phase <math display="inline"><semantics> <msub> <mi>BESS</mi> <mn>101</mn> </msub> </semantics></math> for: (<b>a</b>) Case 01; (<b>b</b>) Case 02; (<b>c</b>) Case 03.</p> Full article ">Figure 12
<p>Secondary transformer loading conditions for Cases 01–03, overloaded conditions are noticed due to reversed power injected by microgeneration units; admissible conditions are obtained applying the proposed coordinated operation.</p> Full article ">Figure 13
<p>Case 04: (<b>a</b>) resulting voltage ranges and actions yielded for BESS<math display="inline"><semantics> <msub> <mrow/> <mn>101</mn> </msub> </semantics></math>; (<b>b</b>) control set-points and SoC for BESS<math display="inline"><semantics> <msub> <mrow/> <mn>101</mn> </msub> </semantics></math>.</p> Full article ">Figure 14
<p>Case 05: (<b>a</b>) resulting voltage ranges, coordinated charging in comparison with dumb charging; BESS<math display="inline"><semantics> <msub> <mrow/> <mn>101</mn> </msub> </semantics></math> scheduling of operation and V2G actions; (<b>b</b>) SoC for all EVs; circled by red line correspond to V2G mode of operation.</p> Full article ">Figure 15
<p>Case 06: (<b>a</b>) resulting voltage ranges, coordinated charging in comparison with dumb charging; BESS<math display="inline"><semantics> <msub> <mrow/> <mn>101</mn> </msub> </semantics></math> scheduling of operation and V2G actions; (<b>b</b>) SoC for all EVs, circled with a red line, correspond to V2G mode of operation.</p> Full article ">
18 pages, 7634 KiB  
Article
Improvement in Energy Performance of Building Envelope Incorporating Electrochromic Windows (ECWs)
by Bo Rang Park, Jongin Hong, Eun Ji Choi, Young Jae Choi, Choonyeob Lee and Jin Woo Moon
Energies 2019, 12(6), 1181; https://doi.org/10.3390/en12061181 - 26 Mar 2019
Cited by 32 | Viewed by 5305
Abstract
The present study sets out to review the thermal and optical properties of electrochromic windows (ECWs) through an analysis of the improvement in the energy performance of a building resulting from their application. The performance analysis was based on the change in the [...] Read more.
The present study sets out to review the thermal and optical properties of electrochromic windows (ECWs) through an analysis of the improvement in the energy performance of a building resulting from their application. The performance analysis was based on the change in the room temperature according to the solar transmittance and the orientation of the ECWs, the energy consumptions of the building’s heating/cooling systems, and that of the building’s lighting according to the visible light transmittance (VLT). To achieve this, the Quick Energy Simulation Tool (eQUEST), a building energy interpretation program, was used. The solar heat gain coefficient (SHGC) of the ECWs was found to be significantly reduced. This had the effect of lowering the room temperature in summer, such that the effect on the summer cooling energy consumption was also remarkable. However, with a reduction in the VLT, the lighting energy consumption increased. The net result of the changes in the heating/cooling and lighting energy consumptions was a reduction of about 11,207 kWh/yr (8.89%). The ECWs were found to realize a greater reduction in a building’s energy consumption than was possible with windows glazed with low-E coated glass. Full article
(This article belongs to the Special Issue Modeling, Control, and Optimization of Hybrid Energy Systems in Buildings)
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<p>A schematic of a typical electrochromic window.</p> Full article ">Figure 2
<p>Annual solar transmission rate by orientation according to window type.</p> Full article ">Figure 3
<p>Solar transmission performance by direction (Monthly)—South. (Variation: A percentage change compared to base model(C-2)).</p> Full article ">Figure 4
<p>Solar transmission performance by direction (Monthly)—East.</p> Full article ">Figure 5
<p>Solar transmission performance by direction (Monthly)—West.</p> Full article ">Figure 6
<p>Solar transmission performance by direction (Monthly)—North.</p> Full article ">Figure 7
<p>Indoor temperature by direction (Monthly)—South.</p> Full article ">Figure 8
<p>Indoor temperature by direction (Monthly)—East.</p> Full article ">Figure 9
<p>Indoor temperature by direction (Monthly)—West.</p> Full article ">Figure 10
<p>Indoor temperature by direction (Monthly)—North.</p> Full article ">Figure 11
<p>Annual heating and cooling energy consumption. (Variation: A percentage change compared to base model(C-2)).</p> Full article ">Figure 12
<p>Peak Heating and Cooling energy consumption. (Variation: A percentage change compared to base model(C-2)).</p> Full article ">
24 pages, 6945 KiB  
Article
Improving Simultaneous Cooling and Power Load-Following Capability for MGT-CCP Using Coordinated Predictive Controls
by Chen Chen, Jiangfan Lin, Lei Pan, Kwang Y. Lee and Li Sun
Energies 2019, 12(6), 1180; https://doi.org/10.3390/en12061180 - 26 Mar 2019
Cited by 5 | Viewed by 3010
Abstract
The distributed energy system is an energy supply method built around the end users, which can achieve energy sustainability and reduce emissions compared to traditional centralized energy systems. The micro gas turbine (MGT)-based combined cooling and power (CCP) system has received renewed attention [...] Read more.
The distributed energy system is an energy supply method built around the end users, which can achieve energy sustainability and reduce emissions compared to traditional centralized energy systems. The micro gas turbine (MGT)-based combined cooling and power (CCP) system has received renewed attention as an important distributed energy system technology due to its substantial energy savings and reduced emission levels. The task of the MGT-CCP system is to quickly adapt to changes in various renewable energy sources to maintain the balance in energy supply and demand in a distributed energy system. Therefore, it is imperative to improve the load tracking capability of the MGT-CCP system with advanced control technologies toward achieving this goal. However, the difficulty of controlling the MGT-CCP system is that the MGT responds very fast while CCP responds very slowly. To this end, the dynamic characteristics and nonlinear distribution of the MGT and CCP processes are analyzed, and a coordinated predictive control strategy is proposed by utilizing the generalized predictive control for the MGT system and the Hammerstein generalized predictive control for the CCP system. The coordinated predictive control of generalized predictive control and Hammerstein generalized predictive control was implemented in an 80 kW MGT-CCP simulator to verify the effectiveness of the proposed method. The simulation results show that compared with PID and MPC, the proposed control method not only can greatly improve simultaneous cooling and power load-following capability, but also has the best control effect when accessing with renewable energy. Full article
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<p>The MGT-CCP system schematic diagram.</p> Full article ">Figure 2
<p>Step response of MGT-CCP system: Fuel and valve openings increased by 10% at 500 s and 3000 s, respectively.</p> Full article ">Figure 3
<p>The value of V-gap between different operating points in MGT-CCP system. (<b>a</b>) Nonlinearity distribution of MGT-CCP process under varying fuel <math display="inline"><semantics> <mrow> <msub> <mi>u</mi> <mn>1</mn> </msub> </mrow> </semantics></math>; (<b>b</b>) Nonlinearity distribution of MGT-CCP process under varying refrigerant valve opening <math display="inline"><semantics> <mrow> <msub> <mi>u</mi> <mn>2</mn> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 4
<p>Structure of Hammerstein-GPC.</p> Full article ">Figure 5
<p>Coordinated predictive control strategy for the MGT-CCP system.</p> Full article ">Figure 6
<p>Identification data (power generation system). (<b>a</b>) input command data; (<b>b</b>) output data.</p> Full article ">Figure 7
<p>Estimated output and true output (power generation system).</p> Full article ">Figure 8
<p>Identification data (cooling system). (<b>a</b>) input command data; (<b>b</b>) output data.</p> Full article ">Figure 8 Cont.
<p>Identification data (cooling system). (<b>a</b>) input command data; (<b>b</b>) output data.</p> Full article ">Figure 9
<p>Estimated output and true output (cooling system).</p> Full article ">Figure 10
<p>Control structure of comparison methods. (<b>a</b>) PID; (<b>b</b>) MPC.</p> Full article ">Figure 11
<p>Case 1: Load tracking performance of the MGT-CCP system (Solid in blue: proposed method; dashed in black: Conventional MPC; dot in green: reference). (<b>a</b>,<b>b</b>) Output variables; (<b>c</b>,<b>d</b>) Manipulated variables.</p> Full article ">Figure 12
<p>Case 1: Load tracking performance of the MGT-CCP system (Solid in blue: proposed method; dot-dashed in red: PID; dot in green: reference). (<b>a</b>,<b>b</b>) Output variables; (<b>c</b>,<b>d</b>) Manipulated variables.</p> Full article ">Figure 13
<p>Unknown input disturbances.</p> Full article ">Figure 14
<p>Case 2: performance of unknown input disturbance rejection (Solid in blue: proposed method; dot-dashed in red: PID; dot in green: reference). (<b>a</b>,<b>b</b>) Output variables; (<b>c</b>,<b>d</b>) Manipulated variables.</p> Full article ">Figure 14 Cont.
<p>Case 2: performance of unknown input disturbance rejection (Solid in blue: proposed method; dot-dashed in red: PID; dot in green: reference). (<b>a</b>,<b>b</b>) Output variables; (<b>c</b>,<b>d</b>) Manipulated variables.</p> Full article ">Figure 15
<p>The block diagram of the MGT-CCP system connected to renewable energy.</p> Full article ">Figure 16
<p>Power from renewable sources.</p> Full article ">Figure 17
<p>Case 3: Tracking performance on time-varying power load demands (Solid in blue: proposed method; dot-dashed in red: PID; dot in green: reference). (<b>a</b>) Sum of power output; (<b>b</b>,<b>c</b>) Output variables; (<b>d</b>,<b>e</b>) Manipulated variables.</p> Full article ">Figure 17 Cont.
<p>Case 3: Tracking performance on time-varying power load demands (Solid in blue: proposed method; dot-dashed in red: PID; dot in green: reference). (<b>a</b>) Sum of power output; (<b>b</b>,<b>c</b>) Output variables; (<b>d</b>,<b>e</b>) Manipulated variables.</p> Full article ">
18 pages, 10496 KiB  
Article
Representative Sampling Implementation in Online VFA/TIC Monitoring for Anaerobic Digestion
by Camilo Wilches, Maik Vaske, Kilian Hartmann and Michael Nelles
Energies 2019, 12(6), 1179; https://doi.org/10.3390/en12061179 - 26 Mar 2019
Cited by 8 | Viewed by 4612
Abstract
This paper describes an automatic sampling system for anaerobic reactors that allows taking representative samples following the guidelines of Gy’s (1998) theory of sampling. Due to the high heterogeneity degree in a digester the sampling errors are larger than the analysis error, making [...] Read more.
This paper describes an automatic sampling system for anaerobic reactors that allows taking representative samples following the guidelines of Gy’s (1998) theory of sampling. Due to the high heterogeneity degree in a digester the sampling errors are larger than the analysis error, making representative sampling a prerequisite for successful process control. In our system, samples are automatically processed, generating a higher density of data and avoiding human error by sample manipulation. The combination of a representative sampling system with a commercial automate titration unit generates a robust online monitoring system for biogas plants. The system was successfully implemented in an operating biogas plant to control a feeding-on-demand biogas system. Full article
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<p>Process diagram sampling device.</p> Full article ">Figure 2
<p>Subsample dosing. <b>1:</b> Valves position before taking subsample. <b>2:</b> Valves position after taking the sample. (red = digestate, blue = air).</p> Full article ">Figure 3
<p>Physical construction of the three valves <span class="html-italic">Vent_PE1</span>, <span class="html-italic">Vent_PE3</span> and <span class="html-italic">Vent_PE3</span> to define subsample volume according to the enclosed air volume, <math display="inline"><semantics> <msub> <mi>V</mi> <mrow> <mi>e</mi> <mi>n</mi> <mi>c</mi> <mi>l</mi> <mi>o</mi> <mi>s</mi> <mi>e</mi> <mi>d</mi> </mrow> </msub> </semantics></math>.</p> Full article ">Figure 4
<p>Above left: Sampling system installed at the research plant. Marked sample collection. Above right: Dosing unit and titrator. Below: Visualization for the operator (key: a. Connection pump manifold; b. Collecting Tank; c. Pressure air; d. Drain; e. Watter; f. Venting; g. Peristaltic dosing pump; h. Titration cell; i. Peristaltic pump; j. Distilled water; k. KCL-solution).</p> Full article ">Figure 5
<p>Sampling parameters.</p> Full article ">Figure 6
<p>Configurations comparison. Lowest graphic presents corresponding feeding and agitation schedule.</p> Full article ">Figure 7
<p>Three months online monitoring. On the abscissa time is given in days and on the ordinate the following aspects are given. Left: presents the digester feeding. Two feeding transition of maize silage can be identified from 1300 kg almost every 2 h to 6500 kg every 12 h and later 13,000 kg once a day. Middle: presents gas storage volume and CHP electrical generation. Generated power was reduced due to the low gas storage levels. Right: presents results of online monitoring and methane content. Process disturbance can be identified by the increase of the VFA/TIC. Calibration of the gas analyzer is marked showing a difference in the methane content from 53% to 45%.</p> Full article ">
14 pages, 1220 KiB  
Article
Does Reduction of Material and Energy Consumption Affect to Innovation Efficiency? The Case of Manufacturing Industry in South Korea
by Jaeho Shin, Changhee Kim and Hongsuk Yang
Energies 2019, 12(6), 1178; https://doi.org/10.3390/en12061178 - 26 Mar 2019
Cited by 8 | Viewed by 3847
Abstract
“Reduction of material and energy consumption” (RMEC) exists as a major objective of innovation and it is proved to affect positively to innovation performance from previous literature. Though innovation should be measured in efficiency rather than performance itself, however, the relationship between material [...] Read more.
“Reduction of material and energy consumption” (RMEC) exists as a major objective of innovation and it is proved to affect positively to innovation performance from previous literature. Though innovation should be measured in efficiency rather than performance itself, however, the relationship between material and energy reduction on innovation efficiency is still unanswered. In this paper, we analyzed the effect of RMEC on innovation efficiency considering both innovation inputs and outputs. We utilized data of 388 manufacturing enterprises in Korea, and performed data envelopment analysis (DEA) and tobit regression analysis. According to the result, firms show difference by industry type in terms of innovation efficiency and RMEC. Moreover, the effect of RMEC on innovation efficiency turned out to be negative. The result indicates a possibility that input used for innovation might overweigh the output yielded when firms pursue innovation for the RMEC. Full article
(This article belongs to the Special Issue Sustainability Assessment of Energy Technologies and Energy Systems and Their Contribution to the UN Sustainable Development Goals)
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<p>Research model.</p> Full article ">Figure 2
<p>Innovation efficiency and MER objective matrix.</p> Full article ">Figure 3
<p>2 × 2 matrix categorized by industry type.</p> Full article ">
28 pages, 4853 KiB  
Article
Estimating On-Road Vehicle Fuel Economy in Africa: A Case Study Based on an Urban Transport Survey in Nairobi, Kenya
by Aderiana Mutheu Mbandi, Jan R. Böhnke, Dietrich Schwela, Harry Vallack, Mike R. Ashmore and Lisa Emberson
Energies 2019, 12(6), 1177; https://doi.org/10.3390/en12061177 - 26 Mar 2019
Cited by 17 | Viewed by 11662
Abstract
In African cities like Nairobi, policies to improve vehicle fuel economy help to reduce greenhouse gas emissions and improve air quality, but lack of data is a major challenge. We present a methodology for estimating fuel economy in such cities. Vehicle characteristics and [...] Read more.
In African cities like Nairobi, policies to improve vehicle fuel economy help to reduce greenhouse gas emissions and improve air quality, but lack of data is a major challenge. We present a methodology for estimating fuel economy in such cities. Vehicle characteristics and activity data, for both the formal fleet (private cars, motorcycles, light and heavy trucks) and informal fleet—minibuses (matatus), three-wheelers (tuktuks), goods vehicles (AskforTransport) and two-wheelers (bodabodas)—were collected and used to estimate fuel economy. Using two empirical models, general linear modelling (GLM) and artificial neural network (ANN), the relationships between vehicle characteristics for this fleet and fuel economy were analyzed for the first time. Fuel economy for bodabodas (4.6 ± 0.4 L/100 km), tuktuks (8.7 ± 4.6 L/100 km), passenger cars (22.8 ± 3.0 L/100 km), and matatus (33.1 ± 2.5 L/100 km) was found to be 2–3 times worse than in the countries these vehicles are imported from. The GLM provided the better estimate of predicted fuel economy based on vehicle characteristics. The analysis of survey data covering a large informal urban fleet helps meet the challenge of a lack of availability of vehicle data for emissions inventories. This may be useful to policy makers as emissions inventories underpin policy development to reduce emissions. Full article
(This article belongs to the Section A: Sustainable Energy)
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<p>The data combinations required to develop the NMR vehicle fleet dataset and estimate fuel economy using the three different modelling approaches: calculated fuel economy, GLM and ANN.</p> Full article ">Figure 2
<p>A map of the 15 field sites where the questionnaire survey interviews were conducted in the NMR. The map was created using GRASS software [<a href="#B55-energies-12-01177" class="html-bibr">55</a>].</p> Full article ">Figure 3
<p>Vehicle characteristics from questionnaire data, mean with 95% confidence interval for vehicle age, engine size, and weight.</p> Full article ">Figure 4
<p>Vehicle activity from questionnaire data, mean and 95% confidence interval about the mean of the vehicle kilometres travelled (VKT), fuel consumption (FC) and Fuel Economy (FE′) for Kenyan classes.</p> Full article ">Figure 5
<p>A map of missing values. The variables in columns correspond with those from Equation (3) as follows: Age (age of vehicle as proxy for technology), MIL (mileage on the car from cumulated odometer reading), YBT (vehicle turnover from years since vehicle bought by current owner), GVW (gross value weight), DPW (days per week vehicle used), CC (engine size), TT (transmission type), FT (fuel type), NOS (number of seats on vehicle). The <span class="html-italic">y</span>-axis presents the count of the different variables.</p> Full article ">Figure 6
<p>Diagnostic graph of observed variables plotted against the imputed values.</p> Full article ">Figure 7
<p>A comparison of GLM and various configurations ANN model and then the best NN model (two layers, four and one neuron) is compared to the GLM model. NN<sub>ij</sub> denotes the network configuration of the neural network with i, the number of nodes in the first layer and j the number of nodes in the second layer. All the values in these plots are log-normal transformed. The plot on the bottom half of the figure, <span class="html-italic">x</span>-axis represents calculated fuel economy (FE′) and the <span class="html-italic">y</span>-axis is predicted fuel economy (FE″).</p> Full article ">Figure 8
<p>Plot of the comparative statistics of the bootstrap. AIC, BIC, MSE of the three top ANN models (NN4.1, NN3.1, NN4) and the GLM model. <b>I</b>, <b>II</b>, <b>III</b>, <b>IV</b> comprises of AIC and BIC comparisons of ANN and <b>V</b>, <b>VI</b>, <b>VII</b> comprises of MSE comparisons of GLM and ANN.</p> Full article ">Figure 9
<p>Fuel economies for different countries from various sources: India [<a href="#B24-energies-12-01177" class="html-bibr">24</a>], Kenya (current study), South Africa [<a href="#B29-energies-12-01177" class="html-bibr">29</a>], China [<a href="#B44-energies-12-01177" class="html-bibr">44</a>], Japan [<a href="#B74-energies-12-01177" class="html-bibr">74</a>], EU [<a href="#B14-energies-12-01177" class="html-bibr">14</a>,<a href="#B75-energies-12-01177" class="html-bibr">75</a>], USA [<a href="#B75-energies-12-01177" class="html-bibr">75</a>,<a href="#B76-energies-12-01177" class="html-bibr">76</a>].</p> Full article ">Figure A1
<p>A sample questionnaire for use in the field survey in Nairobi.</p> Full article ">
26 pages, 2249 KiB  
Article
Guidelines and Cost-Benefit Analysis of the Structural Health Monitoring Implementation in Offshore Wind Turbine Support Structures
by Maria Martinez-Luengo and Mahmood Shafiee
Energies 2019, 12(6), 1176; https://doi.org/10.3390/en12061176 - 26 Mar 2019
Cited by 27 | Viewed by 7222
Abstract
This paper investigates how the implementation of Structural Health Monitoring Systems (SHMS) in the support structure (SS) of offshore wind turbines (OWT) affects capital expenditure (CAPEX) and operational expenditure (OPEX) of offshore wind farms (WF). In order to determine the added value of [...] Read more.
This paper investigates how the implementation of Structural Health Monitoring Systems (SHMS) in the support structure (SS) of offshore wind turbines (OWT) affects capital expenditure (CAPEX) and operational expenditure (OPEX) of offshore wind farms (WF). In order to determine the added value of Structural Health Monitoring (SHM), the balance between the reduction in OPEX and the increase in CAPEX is evaluated. In this paper, guidelines for SHM implementation in offshore WF are developed and applied to a baseline scenario. The application of these guidelines consist of a review of present regulations in the United Kingdom and Germany, the development of SHM strategy, where the first stage of the Statistical Pattern Recognition (SPR) paradigm is explored, failure modes that can be monitored are identified, and SHM technologies and sensor distributions within the turbines are described for a baseline scenario. Furthermore, an inspection strategy where the different structural inspections to be carried out above and below water is also developed, together with an inspection plan for the lifetime of the structures, for the aforementioned baseline scenario. Once the guidelines have been followed and the SHM and inspection strategies developed, a cost-benefit analysis is performed on the baseline case (10% instrumented assets) and three other scenarios with 20%, 30% and 50% of instrumented assets. Finally, a sensitivity analysis is conducted to evaluate the effects of SHM hardware cost and the time spent in completing the inspections on OPEX and CAPEX of the WF. The results show that SHM hardware cost increases CAPEX significantly, however this increase is much lower than the reduction in OPEX caused by SHM. The results also show that an increase in the percentage of instrumented assets will reduce OPEX and this reduction is considerably higher than the cost of SHM implementation. Full article
(This article belongs to the Special Issue Probabilistic Methods for Design and Planning of Operation and Maintenance of Wind Turbines)
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<p>Statistical Pattern Recognition stages.</p> Full article ">Figure 2
<p>CAPEX increase due to SHM implementation in Scenario 3, optimistic case of hardware costs.</p> Full article ">Figure 3
<p>CAPEX increase due to SHM implementation in Scenario 3, average case of hardware costs.</p> Full article ">Figure 4
<p>CAPEX increase due to SHM implementation in Scenario 3, pessimistic case of hardware costs.</p> Full article ">Figure 5
<p>Graphical comparison of lifetime cost of structural inspections under different scenarios.</p> Full article ">Figure 6
<p>Lifetime OPEX reduction from baseline case.</p> Full article ">Figure 7
<p>Lifetime cost of inspection depending on the lifetime inspection frequency.</p> Full article ">
22 pages, 4934 KiB  
Article
Exergy Analysis and Optimization of a Combined Heat and Power Geothermal Plant
by Fabien Marty, Sylvain Serra, Sabine Sochard and Jean-Michel Reneaume
Energies 2019, 12(6), 1175; https://doi.org/10.3390/en12061175 - 26 Mar 2019
Cited by 14 | Viewed by 4657
Abstract
This paper presents the optimization of parallel distribution between electricity and heat production for a geothermal plant. The geothermal fluid is split into two streams, one used for an Organic Rankine Cycle (ORC) system, and the other for a District Heating Network (DHN). [...] Read more.
This paper presents the optimization of parallel distribution between electricity and heat production for a geothermal plant. The geothermal fluid is split into two streams, one used for an Organic Rankine Cycle (ORC) system, and the other for a District Heating Network (DHN). The superstructure to be used for the optimization problem includes the ORC components and the DHN topology constituted by a definite consumer and optional consumers. A Mixed Integer Non-Linear Programming (MINLP) optimization problem is formulated and solved using the GAMS software. This paper is focused on exergetic aspect. The main lines for formulation of the problem are reminded, yet the exergetic model is fully described. Exergy analysis is performed for two optimal solutions (economic and exergetic objective functions). Results for both optimizations are first compared. The analysis of exergetic efficiency of the ORC and the DHN may suggest that exergetic optimization privileges the system with the highest efficiency: the ORC. The DHN configuration is then the smallest as possible. Finally, a sensitive analysis is performed for the exergetic optimization. This analysis reveals our previous conclusion is not necessarily true. Taller configuration can exist even if ORC efficiency is higher than DHN efficiency. These results highlight the relevance of using an optimization approach for a Combined Heat and Power (CHP) plant. Full article
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<p>Schematic representation of the series (<b>a</b>), the parallel (<b>b</b>), the preheat-parallel (<b>c</b>), and the HB4 (<b>d</b>) CHP configurations [<a href="#B17-energies-12-01175" class="html-bibr">17</a>].</p> Full article ">Figure 2
<p>Superstructure of the optimization problem and main variables and input data.</p> Full article ">Figure 3
<p>Solution strategy: (<b>a</b>) summarize of steps, (<b>b</b>) algorithm in order to find a confidence solution [<a href="#B18-energies-12-01175" class="html-bibr">18</a>].</p> Full article ">Figure 4
<p>Exergy flow for <math display="inline"><semantics> <mrow> <mi>max</mi> <mi>P</mi> <mi>r</mi> <mi>o</mi> <mi>f</mi> <mi>i</mi> <mi>t</mi> </mrow> </semantics></math>.</p> Full article ">Figure 5
<p>DHN topology for <math display="inline"><semantics> <mrow> <mi>max</mi> <mi>P</mi> <mi>r</mi> <mi>o</mi> <mi>f</mi> <mi>i</mi> <mi>t</mi> </mrow> </semantics></math>.</p> Full article ">Figure 6
<p>Exergy flow for <math display="inline"><semantics> <mrow> <mi>min</mi> <mover accent="true"> <mi>E</mi> <mo>˙</mo> </mover> <msub> <mi>x</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>s</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 7
<p>DHN topology for <math display="inline"><semantics> <mrow> <mi>min</mi> <mover accent="true"> <mi>E</mi> <mo>˙</mo> </mover> <msub> <mi>x</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>s</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 8
<p>Evolution of <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>E</mi> <mo>˙</mo> </mover> <msub> <mi>x</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>s</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>ψ</mi> <mrow> <mi>O</mi> <mi>R</mi> <mi>C</mi> </mrow> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>ψ</mi> <mrow> <mi>D</mi> <mi>H</mi> <mi>N</mi> </mrow> </msub> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <msub> <mi>ψ</mi> <mrow> <mi>p</mi> <mi>l</mi> <mi>a</mi> <mi>n</mi> <mi>t</mi> </mrow> </msub> </mrow> </semantics></math> with the flow rate of the geothermal source.</p> Full article ">Figure 9
<p>Evolution of <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>E</mi> <mo>˙</mo> </mover> <msub> <mi>x</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>s</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>ψ</mi> <mrow> <mi>O</mi> <mi>R</mi> <mi>C</mi> </mrow> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>ψ</mi> <mrow> <mi>D</mi> <mi>H</mi> <mi>N</mi> </mrow> </msub> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <msub> <mi>ψ</mi> <mrow> <mi>p</mi> <mi>l</mi> <mi>a</mi> <mi>n</mi> <mi>t</mi> </mrow> </msub> </mrow> </semantics></math> with the temperature of the geothermal source (letters in <math display="inline"><semantics> <mrow> <msub> <mi>ψ</mi> <mrow> <mi>p</mi> <mi>l</mi> <mi>a</mi> <mi>n</mi> <mi>t</mi> </mrow> </msub> </mrow> </semantics></math> curve refer to the DHN configuration in Figure 11).</p> Full article ">Figure 10
<p>ORC representation on working fluid <span class="html-italic">T-s</span> diagram [<a href="#B18-energies-12-01175" class="html-bibr">18</a>].</p> Full article ">Figure 11
<p>Evolution of the DHN configuration during the temperature decrease.</p> Full article ">
17 pages, 1014 KiB  
Article
Evaluating the Effectiveness of New and Old Kinetic Energy Conversion from an Electric Power Economics Perspective: Evidence on the Shandong Province of China
by Wanlei Xue, Bingkang Li, Yongqi Yang, Huiru Zhao and Nan Xu
Energies 2019, 12(6), 1174; https://doi.org/10.3390/en12061174 - 26 Mar 2019
Cited by 9 | Viewed by 3453
Abstract
This paper proposes a hybrid model for evaluating the effectiveness of new and old kinetic energy conversion (NOKEC), China’s major strategic move aiming to transform the mode of economic growth and improvie the quality of economic development. Considering the goals of NOKEC and [...] Read more.
This paper proposes a hybrid model for evaluating the effectiveness of new and old kinetic energy conversion (NOKEC), China’s major strategic move aiming to transform the mode of economic growth and improvie the quality of economic development. Considering the goals of NOKEC and the supporting roles of power industry to NOKEC, this paper constructs an index system for NOKEC effectiveness evaluation from an electric power economics perspective, involving three dimensions and 17 secondary indicators. Furthermore, a hybrid evaluation model based on DEMATEL-ANP and DQ-GRA techniques is developed to accomplish the evaluation of Shandong’s NOKEC effectiveness. The results show that Shandong’s NOKEC effectiveness increased from 2015–2017, indicating that Shandong’s NOKEC policies have achieved remarkable results. According to the evaluation results, this paper puts forward the indicators that should be paid close attention to and the following work priorities in Shandong’s future NOKEC process, which has certain practical value for the promotion of Shandong’s NOKEC. In addition, the evaluation model proposed in this paper considers the interrelationships between indicators and overcomes the shortcomings of traditional GRA, showing good applicability to similar effectiveness evaluation issues. Finally, the limitations and universality of the model are discussed and the improvement direction is put forward. Full article
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<p>Interaction between primary indicators.</p> Full article ">Figure 2
<p>Network hierarchy of the index system.</p> Full article ">Figure 3
<p>Comparison of the actual and target values of NOKEC EEIs.</p> Full article ">
15 pages, 5031 KiB  
Article
Optimal Placement of UHF Sensors for Accurate Localization of Partial Discharge Source in GIS
by Rui Liang, Shenglei Wu, Peng Chi, Nan Peng and Yi Li
Energies 2019, 12(6), 1173; https://doi.org/10.3390/en12061173 - 26 Mar 2019
Cited by 5 | Viewed by 3629
Abstract
This paper proposes an optimal placement model of ultra-high frequency (UHF) sensors for accurate location of partial discharge (PD) in gas-insulated switchgear (GIS). The model is based on 0-1 program in consideration of the attenuation influence on the propagation of electromagnetic (EM) waves [...] Read more.
This paper proposes an optimal placement model of ultra-high frequency (UHF) sensors for accurate location of partial discharge (PD) in gas-insulated switchgear (GIS). The model is based on 0-1 program in consideration of the attenuation influence on the propagation of electromagnetic (EM) waves generated by PD in GIS. the optimal placement plan improves the economy, observability, and accuracy of PD locating. After synchronously acquiring the time of the initial EM waves reaching each UHF sensor, PD occurring time can be obtained. Then, initial locating results can be acquired by using the Euclidean distance measuring method and the extended time difference of arriving (TDOA) location method. With the information of all UHF sensors and the inherent topological structure of GIS, the locating accuracy can be further improved. The method is verified by experiment, showing that the method can avoid the influence of false information and obtain higher locating accuracy by revising initial locating results. Full article
(This article belongs to the Special Issue Optimization Methods Applied to Power Systems Ⅱ)
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<p>L-type structure of gas-insulated switchgear (GIS).</p> Full article ">Figure 2
<p>T-type structure of GIS.</p> Full article ">Figure 3
<p>Location method based on time difference of arriving (TDOA).</p> Full article ">Figure 4
<p>Extended TDOA location method.</p> Full article ">Figure 5
<p>The sensors adjacent to Sm.</p> Full article ">Figure 6
<p>Flow chart of the location method.</p> Full article ">Figure 7
<p>Partial discharge (PD) online monitoring system diagram.</p> Full article ">Figure 8
<p>Laboratory for the PD online monitoring system. (<b>a</b>) Experimental Platform, (<b>b</b>) ultra-high frequency (UHF) sensor in GIS, (<b>c</b>) discharge model in GIS.</p> Full article ">Figure 9
<p>Measured partial discharge signal.</p> Full article ">Figure 10
<p>Noise reduction result.</p> Full article ">Figure 11
<p>Sensor placement results.</p> Full article ">
14 pages, 4836 KiB  
Article
Research of the Fundamental Wave of Wound-Rotor Brushless Doubly-Fed Machine
by Zhenming Li, Xuefan Wang, Lezhi Ou, Xinmai Gao and Fei Xiong
Energies 2019, 12(6), 1172; https://doi.org/10.3390/en12061172 - 26 Mar 2019
Viewed by 2497
Abstract
The brushless doubly-fed machine (BDFM) is a special type of machine with two sets of stator windings and one set of rotor winding. The magnetic field of the BDFM is considered to be complex with no regularity. To study the principles of magnetic [...] Read more.
The brushless doubly-fed machine (BDFM) is a special type of machine with two sets of stator windings and one set of rotor winding. The magnetic field of the BDFM is considered to be complex with no regularity. To study the principles of magnetic fields for the BDFM, a general expression of the fundamental wave is deduced, which shows that the fundamental wave can be regarded as a standing wave when it is observed from rotor reference; also, some discussions about the characteristics of the fundamental wave are presented in the paper. Next, a model of wound-rotor BDFM prototype is established, and the enveloping line and the relations between rotor position and its electrical angle of the magnetic field are figured out in the paper. Finally, after detecting the induced electromotive force (EMF) of measurement coils embedded in the corresponding prototype machine, the validity of the proposed conclusions is verified. Full article
(This article belongs to the Special Issue Electrical Engineering for Sustainable and Renewable Energy)
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<p>Rotor winding scheme of the BDFM prototype.</p> Full article ">Figure 2
<p>Envelope line of different <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> </mrow> </semantics></math> values.</p> Full article ">Figure 3
<p>Envelope line and angle relations of <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>.</p> Full article ">Figure 4
<p>Simulated envelope line and angle relations of: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>=</mo> <mn>0.99</mn> </mrow> </semantics></math>; (<b>b</b>)<math display="inline"><semantics> <mrow> <mtext> </mtext> <msub> <mi>k</mi> <mrow> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>=</mo> <mn>0.9</mn> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>=</mo> <mn>0.7</mn> </mrow> </semantics></math>; (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math>.</p> Full article ">Figure 4 Cont.
<p>Simulated envelope line and angle relations of: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>=</mo> <mn>0.99</mn> </mrow> </semantics></math>; (<b>b</b>)<math display="inline"><semantics> <mrow> <mtext> </mtext> <msub> <mi>k</mi> <mrow> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>=</mo> <mn>0.9</mn> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>=</mo> <mn>0.7</mn> </mrow> </semantics></math>; (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math>.</p> Full article ">Figure 5
<p>Simulated envelope line and angle relations of <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>.</p> Full article ">Figure 6
<p>Scene of prototype test. (<b>a</b>) The rotor structure of prototype; (<b>b</b>) Prototype and converter.</p> Full article ">Figure 7
<p>Oscillograph of induced EMF in the 19th measurement coil and reference coil recorded simultaneously.</p> Full article ">Figure 8
<p>Amplitude variation range of 23 measurement coils with the theoretical envelope line.</p> Full article ">Figure 9
<p>Comparison of experimental and simulation result of angle–position relation.</p> Full article ">
17 pages, 5558 KiB  
Article
Water Condensation in Traction Battery Systems
by Woong-Ki Kim, Fabian Steger, Bhavya Kotak, Peter V. R. Knudsen, Uwe Girgsdies and Hans-Georg Schweiger
Energies 2019, 12(6), 1171; https://doi.org/10.3390/en12061171 - 26 Mar 2019
Cited by 7 | Viewed by 5783
Abstract
Lithium-ion traction battery systems of hybrid and electric vehicles must have a high level of durability and reliability like all other components and systems of a vehicle. Battery systems get heated while in the application. To ensure the desired life span and performance, [...] Read more.
Lithium-ion traction battery systems of hybrid and electric vehicles must have a high level of durability and reliability like all other components and systems of a vehicle. Battery systems get heated while in the application. To ensure the desired life span and performance, most systems are equipped with a cooling system. The changing environmental condition in daily use may cause water condensation in the housing of the battery system. In this study, three system designs were investigated, to compare different solutions to deal with pressure differences and condensation: (1) a sealed battery system, (2) an open system and (3) a battery system equipped with a pressure compensation element (PCE). These three designs were tested under two conditions: (a) in normal operation and (b) in a maximum humidity scenario. The amount of the condensation in the housing was determined through a change in relative humidity of air inside the housing. Through PCE and available spacing of the housing, moisture entered into the housing during the cooling process. While applying the test scenarios, the gradient-based drift of the moisture into the housing contributed maximum towards the condensation. Condensation occurred on the internal surface for all the three design variants. Full article
(This article belongs to the Section E: Electric Vehicles)
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<p>Housing of the physical simulated battery system (PSBS) (<b>A</b>: Ball valve, <b>B</b>: Nozzle, <b>C</b>: PCE, <b>D</b>: U profile on the cold plate, <b>E</b>: housing, <b>F</b>: thermocouple, <b>G</b>: dew sensor, <b>H</b>: 17 mimicked cells, <b>I</b>: pressure sensor, <b>J</b>: cables for humidity sensor, <b>K</b>: outlet of the coolant, <b>L</b>: inlet of the coolant).</p> Full article ">Figure 2
<p>Geometric representation of the mimicked cell (1) Heating foil (2) Aluminum sheet (3) polymethyl methacrylate (PMMA).</p> Full article ">Figure 3
<p>Position and mounting of the sensors inside the battery system: <b>T<sub>1</sub></b> to <b>T<sub>5</sub></b>: temperature sensors in the housing, <b>T<sub>6</sub></b>: temperature sensor on the outside front wall, <b>H<sub>1</sub></b>: humidity sensor at cold plate, <b>H<sub>2</sub></b>: humidity sensor at the simulated cells, <b>H<sub>3</sub></b>: humidity sensor on the climatic chamber, <b>P<sub>1</sub></b>: pressure sensor on the climatic chamber, <b>P<sub>2</sub></b>: pressure sensor in the housing, <b>D<sub>1</sub></b>: dew sensor on the front wall in outside, <b>D<sub>2</sub></b>: dew sensor on the cold plate next to the inlet of the housing.</p> Full article ">Figure 4
<p>Experimental setup and communication between equipment (<b>brown line</b>: communication, black line: analog signal, <b>blue line</b>: coolant).</p> Full article ">Figure 5
<p>Test Profile 1 (for examination of the condensation during the normal operation of battery in hot and humid conditions).</p> Full article ">Figure 6
<p>Test profile 2 (for examination of the condensation with a faulty cooling system in harsh environmental conditions).</p> Full article ">Figure 7
<p>Pressure, absolute humidity and condensation measurements for the sealed battery system (without a PCE) during normal operation: (<b>a</b>) Pressure in the housing (P<sub>out</sub>: external pressure the system, P<sub>In</sub>: internal pressure the system) (<b>b</b>) Calculated absolute humidity of the air and condensation inside the housing (H<sub>1</sub> absolute humidity on the cold plate at input in the housing, H<sub>2</sub>: absolute humidity on the inner wall in the housing, black line: the detection of the condensation by the dew sensor, C: condensation detected, N.C: no condensation detected).</p> Full article ">Figure 7 Cont.
<p>Pressure, absolute humidity and condensation measurements for the sealed battery system (without a PCE) during normal operation: (<b>a</b>) Pressure in the housing (P<sub>out</sub>: external pressure the system, P<sub>In</sub>: internal pressure the system) (<b>b</b>) Calculated absolute humidity of the air and condensation inside the housing (H<sub>1</sub> absolute humidity on the cold plate at input in the housing, H<sub>2</sub>: absolute humidity on the inner wall in the housing, black line: the detection of the condensation by the dew sensor, C: condensation detected, N.C: no condensation detected).</p> Full article ">Figure 8
<p>Pressure variation in the battery housing and climatic chamber in case of the sealed battery system during abnormal operation.</p> Full article ">Figure 9
<p>Absolute humidity of the air and condensation inside the housing during abnormal operation in case of a sealed battery system.</p> Full article ">Figure 10
<p>Absolute humidity and condensation measurements for the open battery system during normal operation.</p> Full article ">Figure 11
<p>Absolute humidity of the air and condensation inside the housing during abnormal operation in case of the open battery system.</p> Full article ">Figure 12
<p>Absolute humidity and condensation measurements for the simulated battery system equipped with PCE during normal operation (for shorter duration test).</p> Full article ">Figure 13
<p>Absolute humidity of the air and condensation inside the housing during normal operation in case of the battery system equipped with PCE (test of 120 h).</p> Full article ">Figure 14
<p>Absolute humidity of the air and condensation inside the housing during abnormal operation in case of the battery system equipped with PCE.</p> Full article ">
18 pages, 9485 KiB  
Article
Thermal Stress and Cyclic Stress Analysis of a Vertical Water-Cooled Wall at a Utility Boiler under Flexible Operation
by Liping Pang, Size Yi, Liqiang Duan, Wenxue Li and Yongping Yang
Energies 2019, 12(6), 1170; https://doi.org/10.3390/en12061170 - 26 Mar 2019
Cited by 11 | Viewed by 4246
Abstract
Supercritical once-through utility boilers are increasingly common in flexible operations in China. In this study, the tube temperature changes at a vertical water-cooled wall are analyzed during a fluctuating flexible operation. There are considerable differences in the temperatures of the parallel tubes at [...] Read more.
Supercritical once-through utility boilers are increasingly common in flexible operations in China. In this study, the tube temperature changes at a vertical water-cooled wall are analyzed during a fluctuating flexible operation. There are considerable differences in the temperatures of the parallel tubes at the minimum load, and the resulting thermal stress distributions at a front water-cooled wall are established using structural calculation software ANSYS 17.1, USA. A wide thermal stress distribution occurs among the parallel tubes, and the local cyclic stress amplitudes under flexible operation are higher than those under cold, warm, hot, or load-following operations. Because of the water wall expansion structure at the furnace, the higher tube temperature areas suffer from compressive stress, while the lower tube temperature areas suffer from tensile stress. During flexible operation, combustion uniformity and a two-phase flow distribution can improve the safety of vertical water-cooled wall operation. The minimum load of the utility boiler should be set as a limitation, and the tube temperature is an important parameter affecting the thermal and cyclic stresses. Full article
(This article belongs to the Section F: Electrical Engineering)
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<p>Generating capacity in a peaking power plant by year.</p> Full article ">Figure 2
<p>Operating hours by load bandwidth.</p> Full article ">Figure 3
<p>Spiral and vertical water-cooled wall inside the furnace.</p> Full article ">Figure 4
<p>Tube temperature distribution along the vertical water-cooled wall under the minimum load.</p> Full article ">Figure 5
<p>Tube temperature distributions at the front, left, back, and right vertical water walls.</p> Full article ">Figure 6
<p>Tube temperature differences at the front, left, back, and right wall.</p> Full article ">Figure 7
<p>Load and tube temperature difference vs. time at the highest tube temperature difference point.</p> Full article ">Figure 8
<p>Heat flux distribution comparison between high load and flexible operation at the four sidewalls.</p> Full article ">Figure 9
<p>Top view of original intermediate header.</p> Full article ">Figure 10
<p>The two-phase flow ratio distribution in original intermediate header.</p> Full article ">Figure 11
<p>Front wall model and temperature boundary of the finite element.</p> Full article ">Figure 12
<p>Shear stress contours along the front wall.</p> Full article ">Figure 13
<p>Thermal stress distributions along the width of the front wall at the highest tube temperature difference.</p> Full article ">Figure 14
<p>Thermal stress contour of the X direction at the highest tube temperature difference.</p> Full article ">Figure 15
<p>Thermal stress contour of the Y direction under the highest tube temperature difference.</p> Full article ">Figure 16
<p>Vertical water wall expansions at the front wall.</p> Full article ">Figure 17
<p>Shear stress cycle and load vs. time at the highest tube temperature difference point.</p> Full article ">Figure 18
<p>ASME fatigue design curve.</p> Full article ">
17 pages, 6968 KiB  
Article
A Comprehensive VSM Control Strategy Designed for Unbalanced Grids
by Huiyu Miao, Fei Mei, Yun Yang, Hongfei Chen and Jianyong Zheng
Energies 2019, 12(6), 1169; https://doi.org/10.3390/en12061169 - 26 Mar 2019
Cited by 10 | Viewed by 4483
Abstract
A virtual synchronous machine (VSM) is a converter which, compared to other types of converters, has more friendly interactions with the power grid because it is able to simulate the external characteristics of a synchronous machine, which can provide virtual inertia and damping. [...] Read more.
A virtual synchronous machine (VSM) is a converter which, compared to other types of converters, has more friendly interactions with the power grid because it is able to simulate the external characteristics of a synchronous machine, which can provide virtual inertia and damping. When the grid voltage is unbalanced, there will be negative sequence current and power oscillations. There will also be double-frequency ripples on the DC bus, which affect the normal operation of the DC power source or load. In order to solve these problems, a comprehensive control strategy is proposed in this paper. The principle of a VSM operated as a current source converter, also called VISMA, is used in the design. A complex coefficient filter is applied to separate the positive and negative sequence components of the grid voltage. By analyzing the reasons of power oscillations under unbalanced voltage, the electrical simulation part of the VSM is improved to achieve several objectives: to suppress negative sequence current and DC voltage ripples. Additionally, the rated voltage in the reactive control part is adaptively adjusted to stabilize the system. The validity of the proposed control strategy is verified by simulation and experiment. Full article
(This article belongs to the Special Issue Control in Power Electronics)
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<p>Topology of the three-phase rectifier.</p> Full article ">Figure 2
<p>Control diagram of the virtual synchronous machine (VSM).</p> Full article ">Figure 3
<p>The positive and negative sequence components diagram.</p> Full article ">Figure 4
<p>The Bode diagram of the complex component filter (<math display="inline"><semantics> <mrow> <msub> <mi>ω</mi> <mrow> <mi>s</mi> <mi>e</mi> <mi>t</mi> </mrow> </msub> </mrow> </semantics></math> = 100π rad/s).</p> Full article ">Figure 5
<p>The implementation diagram for positive sequence separation.</p> Full article ">Figure 6
<p>VSM control block diagram with no negative sequence current.</p> Full article ">Figure 7
<p>VSM control block diagram with no DC voltage ripples.</p> Full article ">Figure 8
<p>The scheme of the modeled systems.</p> Full article ">Figure 9
<p>Simulation of the VSM under normal conditions.</p> Full article ">Figure 9 Cont.
<p>Simulation of the VSM under normal conditions.</p> Full article ">Figure 10
<p>Three-phase currents with a PI current inner loop.</p> Full article ">Figure 11
<p>DC voltage with a PI current inner loop.</p> Full article ">Figure 12
<p>Three-phase currents with a current hysteresis loop.</p> Full article ">Figure 13
<p>DC voltage with a current hysteresis loop.</p> Full article ">Figure 14
<p>Three-phase current with no negative sequence.</p> Full article ">Figure 15
<p>DC bus voltage with no current negative sequence.</p> Full article ">Figure 16
<p>Three-phase current with no DC voltage ripples.</p> Full article ">Figure 17
<p>DC bus voltage with no ripples.</p> Full article ">Figure 18
<p>The scheme of the experiment.</p> Full article ">Figure 19
<p>Voltage, current, and DC voltage under normal conditions.</p> Full article ">Figure 20
<p>Three-phase grid voltage and DC bus voltage with no current negative sequence on AC side.</p> Full article ">Figure 21
<p>Three-phase current with no negative sequence.</p> Full article ">Figure 22
<p>Three-phase grid voltage and DC voltage with no DC voltage ripples.</p> Full article ">Figure 23
<p>Three-phase current with no DC voltage ripples.</p> Full article ">
11 pages, 3844 KiB  
Article
Application of Silicon Oxide on High Efficiency Monocrystalline Silicon PERC Solar Cells
by Shude Zhang, Yue Yao, Dangping Hu, Weifei Lian, Hongqiang Qian, Jiansheng Jie, Qingzhu Wei, Zhichun Ni, Xiaohong Zhang and Lingzhi Xie
Energies 2019, 12(6), 1168; https://doi.org/10.3390/en12061168 - 26 Mar 2019
Cited by 25 | Viewed by 5161
Abstract
In the photovoltaic industry, an antireflection coating consisting of three SiNx layers with different refractive indexes is generally adopted to reduce the reflectance and raise the efficiency of monocrystalline silicon PERC (passivated emitter and rear cell) solar cells. However, for SiNx [...] Read more.
In the photovoltaic industry, an antireflection coating consisting of three SiNx layers with different refractive indexes is generally adopted to reduce the reflectance and raise the efficiency of monocrystalline silicon PERC (passivated emitter and rear cell) solar cells. However, for SiNx, a refractive index as low as about 1.40 cannot be achieved, which is the optimal value for the third layer of a triple-layer antireflection coating. Therefore, in this report the third layer is replaced by SiOx, which possesses a more appropriate refractive index of 1.46, it and can be easily integrated into the SiNx deposition process with the plasma-enhanced chemical vapor deposition (PECVD) method. Through simulation and analysis with SunSolve, three different thicknesses were selected to construct the SiOx third layer. The replacement of 15 nm SiNx with 30 nm SiOx as the third layer of antireflection coating can bring about an efficiency gain of 0.15%, which originates from the reflectance reduction and spectral response enhancement below about 550 nm wavelength. However, because the EVA encapsulation material of the solar module absorbs light in short wavelengths, the spectral response advantage of solar cells with 30 nm SiOx is partially covered up, resulting in a slightly lower cell-to-module (CTM) ratio and an output power gain of only 0.9 W for solar module. Full article
(This article belongs to the Special Issue Selected Papers from the 9th Edition of the International SOLARIS Conference)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The manufacturing process flow of industrialized monocrystalline silicon solar cells.</p> Full article ">Figure 2
<p>The simulation structure of monocrystalline silicon PERC solar cells in SunSolve. The front busbars and fingers are excluded to focus on the antireflection coating.</p> Full article ">Figure 3
<p>The simulated reflectance curves of monocrystalline silicon PERC solar cells with different third layers of antireflection coating in SunSolve. The corresponding weighted average reflectances (<span class="html-italic">WARs</span>) are listed.</p> Full article ">Figure 4
<p>Box plots of the photovoltaic parameters (<b>a</b>—open circuit voltage, <b>b</b>—short-circuit current, <b>c</b>—fill factor, and <b>d</b>—efficiency) of the monocrystalline silicon PERC solar cells fabricated with different third layers of antireflection coating. Each group contained about 100 solar cells. The outliers and mean values are represented by solid lozenges and hollow squares. The solid black spheres in d represent the median efficiency gains compared with the 15 nm SiN<sub>x</sub> group.</p> Full article ">Figure 5
<p>(<b>a</b>) Reflectance curves of the 30 nm SiO<sub>x</sub> third layer sample and the 15 nm SiN<sub>x</sub> third layer sample before metallization. (<b>b</b>) External quantum efficiency curves of the 30 nm SiO<sub>x</sub> third layer sample and the 15 nm SiN<sub>x</sub> third layer sample after metallization.</p> Full article ">Figure 6
<p>Electroluminescence images of monocrystalline silicon PERC solar modules with 30 nm SiO<sub>x</sub> as the third layer of antireflection coating before and after the LID test (<b>a,b</b>) or PID test (<b>c,d</b>).</p> Full article ">Figure 7
<p>Reflectance (RF), external quantum efficiency (EQE), and internal quantum efficiency (IQE) curves of monocrystalline silicon PERC solar cells with the 15 nm SiN<sub>x</sub> third layer and the 30 nm SiO<sub>x</sub> third layer as the antireflection coating. The mean photovoltaic parameters of each group containing about 400 solar cells are listed.</p> Full article ">
12 pages, 2952 KiB  
Article
Impedance Estimation with an Enhanced Particle Swarm Optimization for Low-Voltage Distribution Networks
by Daisuke Kodaira, Jingyeong Park, Sung Yeol Kim, Soohee Han and Sekyung Han
Energies 2019, 12(6), 1167; https://doi.org/10.3390/en12061167 - 26 Mar 2019
Cited by 4 | Viewed by 4289
Abstract
Many researchers in recent years have studied voltage deviation issues in distribution networks. Characterizing the impedance between consuming nodes in a network is the key to controlling the network voltage. Existing impedance estimation methods are faced with three challenges: time synchronized measurement, a [...] Read more.
Many researchers in recent years have studied voltage deviation issues in distribution networks. Characterizing the impedance between consuming nodes in a network is the key to controlling the network voltage. Existing impedance estimation methods are faced with three challenges: time synchronized measurement, a generalization of the network model, and convergence of the optimization for objective functions. This paper extends an existing impedance estimation algorithm by introducing an enhanced particle swarm optimization (PSO). To overcome this method’s local optimum problem, we propose adaptive inertia weights. Also, our proposed method is based on a new general model for a low voltage distribution network with non-synchronized measurements. In the case study, the improved impedance estimation algorithm realizes better accuracy than the existing method. Full article
(This article belongs to the Special Issue Machine Learning and Optimization with Applications of Power System)
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<p>Simulation model: generalized linear Low-Voltage distribution network.</p> Full article ">Figure 2
<p>Five T-nodes in the model for the case study.</p> Full article ">Figure 3
<p>Average and 95% confidence interval for estimated impedance (real and imaginary part).</p> Full article ">Figure 4
<p>Average and 95% confidence interval for error of estimated impedance (real and imaginary part).</p> Full article ">
22 pages, 976 KiB  
Review
A Brief Review of Anaerobic Digestion of Algae for Bioenergy
by John J. Milledge, Birthe V. Nielsen, Supattra Maneein and Patricia J. Harvey
Energies 2019, 12(6), 1166; https://doi.org/10.3390/en12061166 - 26 Mar 2019
Cited by 138 | Viewed by 11882
Abstract
The potential of algal biomass as a source of liquid and gaseous biofuels has been the subject of considerable research over the past few decades, with researchers strongly agreeing that algae have the potential of becoming a viable aquatic energy crop with a [...] Read more.
The potential of algal biomass as a source of liquid and gaseous biofuels has been the subject of considerable research over the past few decades, with researchers strongly agreeing that algae have the potential of becoming a viable aquatic energy crop with a higher energy potential compared to that from either terrestrial biomass or municipal solid waste. However, neither microalgae nor seaweed are currently cultivated solely for energy purposes due to the high costs of harvesting, concentrating and drying. Anaerobic digestion of algal biomass could theoretically reduce costs associated with drying wet biomass before processing, but practical yields of biogas from digestion of many algae are substantially below the theoretical maximum. New processing methods are needed to reduce costs and increase the net energy balance. This review examines the biochemical and structural properties of seaweeds and of microalgal biomass that has been produced as part of the treatment of wastewater, and discusses some of the significant hurdles and recent initiatives for producing biogas from their anaerobic digestion. Full article
(This article belongs to the Special Issue Production and Utilization of Biogas)
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<p>Major steps for biogas production. Cellulose, lipids, and proteins are generally found in all seaweeds. Laminarin, fucoidan, and alginate are typical of brown seaweed (colour-coded brown). Starch and ulvan are typical of green seaweeds (colour-coded green), and the polymeric polysaccharides carrageenan and agar are characteristic of red seaweeds (colour-coded red) [<a href="#B42-energies-12-01166" class="html-bibr">42</a>].</p> Full article ">Figure 2
<p>Annual variation in biodegradability index (BI) (BMP divided by theoretical methane yields), expressed in %, of A. nodosum with variations in polyphenol content and C:N ratio. Polyphenol content is expressed in mg g<sup>−1</sup> total solids (TS). C:N ratio is expressed as the percentage of the sum of the ultimate analysis (C:N ratio divided by sum of % ultimate analysis). Figure derived from data by Tabassum, et al. [<a href="#B191-energies-12-01166" class="html-bibr">191</a>].</p> Full article ">
15 pages, 1124 KiB  
Article
A Class-E Amplifier for a Loosely Coupled Inductive Power Transfer System with Multiple Receivers
by Alexander Sutor, Martin Heining and Rainer Buchholz
Energies 2019, 12(6), 1165; https://doi.org/10.3390/en12061165 - 26 Mar 2019
Cited by 9 | Viewed by 3641
Abstract
We present a method for optimizing the electronic power system for a new type of photobioreactor or photoreactor in general. In the case of photobioreactors, photosynthetic active microorganisms or cells are grown. A novel concept for the illumination of photobioreactors was necessary, as [...] Read more.
We present a method for optimizing the electronic power system for a new type of photobioreactor or photoreactor in general. In the case of photobioreactors, photosynthetic active microorganisms or cells are grown. A novel concept for the illumination of photobioreactors was necessary, as the external illumination of those reactors leads to a limited penetration depth of light. Due to the limited penetration depth, no standard reactors can be use for cultivation, but custom made reactors with very small volume to surface ratio have to be used. This still prevents the technology from a large scale industrial impact. The solution we propose in this paper is an internal illumination via Wireless Light Emitters. This increases the manageable culture volume of photosynthetic active microorganisms or cells. The illumination system is based on floating light emitters, which are powered wirelessly by near field resonant inductive coupling. The floating light emitters are able to illuminate a photobioreactor more homogeneously than external illumination systems do. We designed a class-E amplifier and field coils to produce an intermediate frequency electromagnetic field inside the reactor. An appropriate magnetic flux density was found to be approx. B = 1 mT and the driving frequency is f = 176 kHz. We conducted experiments with a laboratory size photoreactor. The cultivation volume was 30 L containing up to 3000 WLEs. The maximum electric power input was more than 300 W and we calculated an efficiency of up to 76%. Full article
(This article belongs to the Section D: Energy Storage and Application)
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<p>(<b>a</b>) series production on professional PCB board; (<b>b</b>) close-up of side view and top view; (<b>c</b>) encapsulated Wireless Light Emitters (WLE); (<b>d</b>) construction drawing.</p> Full article ">Figure 2
<p>Three test reactors with diameters of (<b>a</b>) 50 mm, (<b>b</b>) 150 mm, and (<b>c</b>) 300 mm. The largest reactor with the four tagged driving coils has been used in the experiments described here.</p> Full article ">Figure 3
<p>Lumped network of the receiver in parallel connection as proposed in [<a href="#B29-energies-12-01165" class="html-bibr">29</a>].</p> Full article ">Figure 4
<p>The upper righthand circuit represents a single WLE-receiver. The lower circuit stands for a lumped network of <span class="html-italic">n</span> receivers.</p> Full article ">Figure 5
<p>Most basic circuit for the class-E amplifier.</p> Full article ">Figure 6
<p>Simulations of a tuned and a mistuned amplifier. The arrows indicate the direction into which the minimum moves when changing the values for <span class="html-italic">C</span> and <math display="inline"><semantics> <msub> <mi>C</mi> <mn>1</mn> </msub> </semantics></math>.</p> Full article ">Figure 7
<p>Some measured signals. Notice that the amplifier is well tuned. The output power is approx. 9 W.</p> Full article ">Figure 8
<p>The amplifier is mistuned at its maximum power of 55 W.</p> Full article ">Figure 9
<p>Complete circuit of the 300 W amplifier #2 including a load of 3000 WLEs.</p> Full article ">Figure 10
<p>Simulation results for amplifier #2.</p> Full article ">Figure 11
<p>Measurement results for amplifier #2. Active power approx. 250 W.</p> Full article ">Figure 12
<p>Measurement results for amplifier #2. Active power approx. 300 W.</p> Full article ">Figure 13
<p>Comparison of internal (int) and external (ext) illumination. The numbers on the right are the diameters of the utilized reactors in mm.</p> Full article ">
14 pages, 2572 KiB  
Article
Data-Driven Decentralized Algorithm for Wind Farm Control with Population-Games Assistance
by Julian Barreiro-Gomez, Carlos Ocampo-Martinez, Fernando D. Bianchi and Nicanor Quijano
Energies 2019, 12(6), 1164; https://doi.org/10.3390/en12061164 - 26 Mar 2019
Cited by 6 | Viewed by 3451
Abstract
In wind farms, the interaction between turbines that operate close by experience some problems in terms of their power generation. Wakes caused by upstream turbines are mainly responsible of these interactions, and the phenomena involved in this case is complex especially when the [...] Read more.
In wind farms, the interaction between turbines that operate close by experience some problems in terms of their power generation. Wakes caused by upstream turbines are mainly responsible of these interactions, and the phenomena involved in this case is complex especially when the number of turbines is high. In order to deal with these issues, there is a need to develop control strategies that maximize the energy captured from a wind farm. In this work, an algorithm that uses multiple estimated gradients based on measurements that are classified by using a simple distributed population-games-based algorithm is proposed. The update in the decision variables is computed by making a superposition of the estimated gradients together with the classification of the measurements. In order to maximize the energy captured and maintain the individual power generation, several constraints are considered in the proposed algorithm. Basically, the proposed control scheme reduces the communications needed, which increases the reliability of the wind farm operation. The control scheme is validated in simulation in a benchmark corresponding to the Horns Rev wind farm. Full article
(This article belongs to the Special Issue Control Schemes for Wind Electricity Systems)
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<p>Example of wind farm layout and the corresponding wake effect.</p> Full article ">Figure 2
<p>General steps of the heuristic proposed approach.</p> Full article ">Figure 3
<p>Example gradient estimation with four strategies <math display="inline"><semantics> <mrow> <mi mathvariant="script">S</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mspace width="3.33333pt"/> <mo>=</mo> <mspace width="3.33333pt"/> <mrow> <mo>{</mo> <msubsup> <mrow> <mi mathvariant="bold-italic">s</mi> </mrow> <mi>k</mi> <mn>1</mn> </msubsup> <mo>,</mo> <msubsup> <mrow> <mi mathvariant="bold-italic">s</mi> </mrow> <mi>k</mi> <mn>2</mn> </msubsup> <mo>,</mo> <msubsup> <mrow> <mi mathvariant="bold-italic">s</mi> </mrow> <mi>k</mi> <mn>3</mn> </msubsup> <mo>,</mo> <msubsup> <mrow> <mi mathvariant="bold-italic">s</mi> </mrow> <mi>k</mi> <mn>4</mn> </msubsup> <mo>}</mo> </mrow> </mrow> </semantics></math>, i.e., <math display="inline"><semantics> <mrow> <mi>n</mi> <mo>=</mo> <mn>4</mn> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <mi>f</mi> <mo>:</mo> <msup> <mi mathvariant="double-struck">R</mi> <mn>2</mn> </msup> <mo>↦</mo> <mi mathvariant="double-struck">R</mi> </mrow> </semantics></math>, i.e., <math display="inline"><semantics> <mrow> <mi>m</mi> <mo>=</mo> <mn>2</mn> </mrow> </semantics></math>. Vectors illustrate the direction for the strategies update and the superposition of influences over strategy with index 1. (<b>a</b>) Various available measurements every iteration, (<b>b</b>) one available measurement every iteration.</p> Full article ">Figure 4
<p>General scheme for the gradient-estimation-based algorithm with population-games assistance.</p> Full article ">Figure 5
<p>Typical decentralized control scheme. Each wind turbine has information about the total generated power and its own axial induction factor.</p> Full article ">Figure 6
<p>Horns Rev wind farm of 80 turbines facing a main wind speed with <math display="inline"><semantics> <msup> <mn>45</mn> <mo>°</mo> </msup> </semantics></math> direction.</p> Full article ">Figure 7
<p>(<b>a</b>) Total powers for scenario 1 (free-stream wind speed of 10 m/s) for four wind speed directions. (<b>b</b>) Power generated by wind turbines 1–10 and with wind direction of <math display="inline"><semantics> <msup> <mn>45</mn> <mo>°</mo> </msup> </semantics></math>. (<b>c</b>) Axial coefficients for wind turbines 1–10 and with wind direction of <math display="inline"><semantics> <msup> <mn>45</mn> <mo>°</mo> </msup> </semantics></math>.</p> Full article ">Figure 8
<p>(<b>a</b>) Total powers for scenario 2 (free-stream wind speed of 12 m/s) for four wind speed directions. (<b>b</b>) Power generated by wind turbines 1–10 and with wind direction of <math display="inline"><semantics> <msup> <mn>45</mn> <mo>°</mo> </msup> </semantics></math>. (<b>c</b>) Axial coefficients for wind turbines 1–10 and with wind direction of <math display="inline"><semantics> <msup> <mn>45</mn> <mo>°</mo> </msup> </semantics></math>.</p> Full article ">
12 pages, 2216 KiB  
Article
A Novel Approach to Stabilize Foam Using Fluorinated Surfactants
by Muhammad Shahzad Kamal
Energies 2019, 12(6), 1163; https://doi.org/10.3390/en12061163 - 26 Mar 2019
Cited by 26 | Viewed by 4800
Abstract
Selection of surfactants for enhanced oil recovery and other upstream applications is a challenging task. For enhanced oil recovery applications, a surfactant should be thermally stable, compatible with reservoir brine, and have lower adsorption on reservoir rock, have high foamability and foam stability, [...] Read more.
Selection of surfactants for enhanced oil recovery and other upstream applications is a challenging task. For enhanced oil recovery applications, a surfactant should be thermally stable, compatible with reservoir brine, and have lower adsorption on reservoir rock, have high foamability and foam stability, and should be economically viable. Foam improves the oil recovery by increasing the viscosity of the displacing fluid and by reducing the capillary forces due to a reduction in interfacial tension. In this work, foamability and foam stability of two different surfactants were evaluated using a dynamic foam analyzer. These surfactants were fluorinated zwitterionic, and hydrocarbon zwitterionic surfactants. The effect of various parameters such as surfactant type and structure, temperature, salinity, and type of injected gas was investigated on foamability and foam stability. The foamability was assessed using the volume of foam produced by injecting a constant volume of gas and foam stability was determined by half-life time. The maximum foam generation was obtained using hydrocarbon zwitterionic surfactant. However, the foam generated using fluorinated zwitterionic surfactant was more stable. A mixture of zwitterionic fluorinated and hydrocarbon fluorinated surfactant showed better foam generation and foam stability. The foam generated using CO2 has less stability compared to the foam generated using air injection. Presence of salts increases the foam stability and foam generation. At high temperature, the foamability of the surfactants increased. However, the foam stability was reduced at high temperature for all type of surfactants. This study helps in optimizing the surfactant formulations consisting of a fluorinated and hydrocarbon zwitterionic surfactant for foam injections. Full article
(This article belongs to the Special Issue CO2 EOR and CO2 Storage in Oil Reservoirs)
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<p>The structure of the surfactants used in this study.</p> Full article ">Figure 2
<p>Foam height vs. time for different surfactant system using air and CO<sub>2</sub> at 25 °C.</p> Full article ">Figure 3
<p>FVS of surfactants using seawater and air as a gas medium at 25 °C.</p> Full article ">Figure 4
<p>Bubble size of foam generated using different surfactant systems in high salinity brine using air injection at 25 °C.</p> Full article ">Figure 5
<p>Foamability of different surfactant systems in seawater and deionized water using CO<sub>2</sub> injection at 25 °C.</p> Full article ">Figure 6
<p>FVS of different surfactant systems in deionized water using CO<sub>2</sub> injection at 25 °C.</p> Full article ">Figure 7
<p>Foamability of different surfactant systems in seawater using CO<sub>2</sub> injection at high temperature (80 °C).</p> Full article ">Figure 8
<p>Foam volume stability (FVS) of surfactants using CO<sub>2</sub> injection when dissolved in the SW at 80 °C.</p> Full article ">
17 pages, 6886 KiB  
Article
Research on the Operation Control Strategy of a Low-Voltage Direct Current Microgrid Based on a Disturbance Observer and Neural Network Adaptive Control Algorithm
by Liang Zhang, Kang Chen, Ling Lyu and Guowei Cai
Energies 2019, 12(6), 1162; https://doi.org/10.3390/en12061162 - 25 Mar 2019
Cited by 13 | Viewed by 3060
Abstract
Low-voltage direct current (DC) microgrid based on distributed generation (DG), the problems of load mutation affecting the DC bus under island mode, and the security problems that may arise when the DC microgrid is switched from island mode to grid-connected mode are considered. [...] Read more.
Low-voltage direct current (DC) microgrid based on distributed generation (DG), the problems of load mutation affecting the DC bus under island mode, and the security problems that may arise when the DC microgrid is switched from island mode to grid-connected mode are considered. Firstly, a DC bus control algorithm based on disturbance observer (DOB) was proposed to suppress the impact of system load mutation on DC bus in island mode. Then, in a grid-connected mode, a pre-synchronization control algorithm based on a neural network adaptive control was proposed, and the droop controller was improved to ensure better control accuracy. Through this pre-synchronization control, the microgrid inverters output voltage could quickly track the power grid’s voltage and achieve an accurate grid-connected operation. The effectiveness of the algorithms was verified by simulation. Full article
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<p>Equivalent circuit of a photovoltaic cell.</p> Full article ">Figure 2
<p>A simulation model of a photovoltaic cell. CCS: controlled current source; IGBT: Insulated Gate Bipolar Transistor; MPPT: Maximum Power Point Tracking.</p> Full article ">Figure 3
<p>A control flow chart of the disturbance observation method.</p> Full article ">Figure 4
<p>A control flow chart of the DC bus control algorithm. PI: proportion-integral; DOB: disturbance observer.</p> Full article ">Figure 5
<p>A DOB control structure.</p> Full article ">Figure 6
<p>A structure diagram of the voltage source inverter control system. PWM: Pulse Width Modulation; PCC: Point of Common Coupling; LC: inductance-capacitance.</p> Full article ">Figure 7
<p>Voltage and current double loop control link with virtual impedance.</p> Full article ">Figure 8
<p>A cerebellar model articulation controller (CMAC) control structure diagram. VAS: virtual associative space; PSS: physical storage space.</p> Full article ">Figure 9
<p>A CMAC and PID composite control structure diagram.</p> Full article ">Figure 10
<p>A schematic diagram of pre-synchronization process.</p> Full article ">Figure 11
<p>The pre-synchronization control algorithm. ANN: artificial neural network.</p> Full article ">Figure 12
<p>The DC bus voltage waveform in island operation.</p> Full article ">Figure 13
<p>The DC bus power waveform in island operation.</p> Full article ">Figure 14
<p>A three-phase output voltage waveform of the inverter.</p> Full article ">Figure 15
<p>A square wave tracing experimental waveform.</p> Full article ">Figure 16
<p>An output voltage comparison diagram between the inverter and the power grid under the traditional PLL algorithm.</p> Full article ">Figure 17
<p>An output voltage comparison diagram between the inverter and the power grid under the proposed algorithm.</p> Full article ">
28 pages, 7467 KiB  
Article
Hybrid Adsorption-Compression Systems for Air Conditioning in Efficient Buildings: Design through Validated Dynamic Models
by Valeria Palomba, Efstratios Varvagiannis, Sotirios Karellas and Andrea Frazzica
Energies 2019, 12(6), 1161; https://doi.org/10.3390/en12061161 - 25 Mar 2019
Cited by 29 | Viewed by 5807
Abstract
Hybrid sorption-compression systems are gaining interest for heating/cooling/ refrigeration purposes in different applications, since they allow exploiting the benefits of both technologies and a better utilization of renewable sources. However, design of such components is still difficult, due to the intrinsic complexity of [...] Read more.
Hybrid sorption-compression systems are gaining interest for heating/cooling/ refrigeration purposes in different applications, since they allow exploiting the benefits of both technologies and a better utilization of renewable sources. However, design of such components is still difficult, due to the intrinsic complexity of the systems and the lack of reliable models. In particular, the combination of adsorption-compression cascade unit has not been widely explored yet and there are no simulations or sizing tools reported in the literature. In this context, the present paper describes a model of a hybrid adsorption-compression system, realised in Modelica language using the commercial software Dymola. The models of the main components of the sorption and vapour compression unit are described in details and their validation presented. In addition, the integrated model is used for proving the feasibility of the system under dynamic realistic conditions and an example of the technical sizing that the model is able to accomplish is given. Full article
(This article belongs to the Section D: Energy Storage and Application)
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<p>The hybrid system proposed: (1) solar thermal collectors field. (2) photovoltaic panels. (3) adsorbers of the adsorption chiller. (4) adsorption chiller condenser. (5) adsorption chiller evaporator. (6) vapour compression chiller condenser. (7) vapour compression chiller evaporator. (8) compressor. (9) dry cooler for heat rejection to the ambient.</p> Full article ">Figure 2
<p>Layout of the model of the adsorption module with the indication of fluid ports and thermal ports as in the model implementation in Dymola.</p> Full article ">Figure 3
<p>Schematics of the adsorber (left) and its implementation, with input and output variables and energy flows for the adsorber during adsorption (middle) and desorption (right).</p> Full article ">Figure 4
<p>Representation of the evaporator/condenser (left) and its implementation, with input and output variables and energy flows for the evaporator (middle) and condenser (right).</p> Full article ">Figure 5
<p>CV formulation for the evaporator (up) and the condenser (bottom) heat exchanger models.</p> Full article ">Figure 6
<p>Compression chiller model layout representing the Dymola implementation.</p> Full article ">Figure 7
<p>Validation of the model for the adsorber. The red area represents experimental error.</p> Full article ">Figure 8
<p>Representation of the compression chiller model calibration procedure.</p> Full article ">Figure 9
<p>Compression chiller validation results in terms of relative errors (%) for the evaporator capacity and the EER under various inlet water temperatures.</p> Full article ">Figure 10
<p>Dymola layout of the hybrid integrated model. 1: sorption module; 2: compression chiller; 3: control unit; 4: 3-way valve for switching between heating and cooling mode of the compression chiller; 5: 3-way valves to switch between the hydraulic connections of the units and the direct connection of the compression chiller to the heat rejection (medium temperature) circuit.</p> Full article ">Figure 11
<p>Boundary conditions for the dynamic simulation of the hybrid system - temperature and cooling demands for a reference day in Aglantzia (CY).</p> Full article ">Figure 12
<p>Temperatures in the circuits of the sorption module and heat pump for the reference conditions. The outlet of the evaporator of the adsorption unit (light green) also represents the inlet of the condenser in the vapour compression chiller; the inlet of the of the evaporator of the adsorption unit (dark green) also represents the outlet of the condenser in the vapour compression chiller.</p> Full article ">Figure 13
<p>Thermal powers in the components of the sorption module and the vapour compression chiller for the reference conditions.</p> Full article ">Figure 14
<p>Sensitivity analysis - results for the relative size of thermal/electric units.</p> Full article ">
17 pages, 2596 KiB  
Article
A Power Exchange Strategy for Multiple Areas with Hydro Power and Flexible Loads
by Jichun Liu, Yangfang Yang, Yue Xiang and Junyong Liu
Energies 2019, 12(6), 1160; https://doi.org/10.3390/en12061160 - 25 Mar 2019
Cited by 2 | Viewed by 2553
Abstract
Areas with hydro power may purchase extra power from the outside power market during dry seasons, which will cause a deviation between the actual and expected power purchase amount due to the inaccurate judgment of the market situation. Because of the uncertainty of [...] Read more.
Areas with hydro power may purchase extra power from the outside power market during dry seasons, which will cause a deviation between the actual and expected power purchase amount due to the inaccurate judgment of the market situation. Because of the uncertainty of price fluctuations, the risk of purchasing power in the real-time market to eliminate this deviation is very high. This paper proposes an innovative trade mode, where the power exchange strategy between multiple areas is adopted through forming an alliance, i.e., one area can use the controllable elements within others, and constructing a monthly and post day-ahead two phase optimization model. The objective function of the monthly stochastic robust optimization considers the power purchase cost to determine the controllable elements dispatch dates for every area in the alliance. Thus, areas can make reasonable dispatch schedules for controllable elements to avoid the resource waste that means more controllable elements are prepared before post day-ahead optimization but less are used after post day-ahead optimization. While the post day-ahead optimization model determines the internal controllable elements dispatch and power exchange amount after the day-ahead market clearing process, users’ satisfaction and dispatch schedule changes for energy storage device are also considered. In order to solve the proposed two phase model, the dual principle and linearization methods are used to convert them into mixed-integer linear programming problems that can be effectively solved by the Cplex solver. The study case verifies the power deviation cost decreases with the power exchange strategy and the important role of energy storage devices. Full article
(This article belongs to the Section A1: Smart Grids and Microgrids)
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<p>Power exchange from broker A with positive deviation to broker B with negative deviation.</p> Full article ">Figure 2
<p>The monthly optimization result. IL = interruptible load; TL = transferable load; NS = energy storage.</p> Full article ">Figure 3
<p>Areas’ forecast net load curve for one day.</p> Full article ">Figure 4
<p>Historical day-ahead electricity price data.</p> Full article ">Figure 5
<p>Areas’ interruptible load costs.</p> Full article ">Figure 6
<p>Areas’ transferable load costs.</p> Full article ">Figure 7
<p>Controllable elements cooperative operation times.</p> Full article ">Figure 8
<p>The influence of robust conservative degree on cost.</p> Full article ">Figure 9
<p>Influence of controllable elements capacity on optimization cost.</p> Full article ">
13 pages, 6015 KiB  
Article
Modeling the Performance of a Zinc/Bromine Flow Battery
by Boram Koo, Dongcheul Lee, Jaeshin Yi, Chee Burm Shin, Dong Joo Kim, Eun Mi Choi and Tae Hyuk Kang
Energies 2019, 12(6), 1159; https://doi.org/10.3390/en12061159 - 25 Mar 2019
Cited by 21 | Viewed by 6215
Abstract
The zinc/bromine (Zn/Br2) flow battery is an attractive rechargeable system for grid-scale energy storage because of its inherent chemical simplicity, high degree of electrochemical reversibility at the electrodes, good energy density, and abundant low-cost materials. It is important to develop a [...] Read more.
The zinc/bromine (Zn/Br2) flow battery is an attractive rechargeable system for grid-scale energy storage because of its inherent chemical simplicity, high degree of electrochemical reversibility at the electrodes, good energy density, and abundant low-cost materials. It is important to develop a mathematical model to calculate the current distributions in a Zn/Br2 flow cell in order to predict such quantities as current, voltage, and energy efficiencies under various charge and discharge conditions. This information can be used to design both of bench and production scale cells and to select the operating conditions for optimum performance. This paper reports a modeling methodology to predict the performance of a Zn/Br2 flow battery. The charge and discharge behaviors of a single cell is calculated based on a simple modeling approach by considering Ohm’s law and charge conservation on the electrodes based on the simplified polarization characteristics of the electrodes. An 8-cell stack performance is predicted based on an equivalent circuit model composed of the single cells and the resistances of the inlet and outlet streams of the positive and negative electrolytes. The model is validated by comparing the modeling results with the experimental measurements. Full article
(This article belongs to the Special Issue Grid-Scale Energy Storage Management)
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<p>A schematic of a Zn/Br<sub>2</sub> flow battery stack composed of 8 cells.</p> Full article ">Figure 2
<p>An equivalent circuit model corresponding to the schematic of <a href="#energies-12-01159-f001" class="html-fig">Figure 1</a>.</p> Full article ">Figure 3
<p>Experimental discharge curves of a Zn/Br<sub>2</sub> flow battery stack composed of 8 cells for different discharge (<b>a</b>) currents and (<b>b</b>) powers.</p> Full article ">Figure 4
<p>Cell voltage as a function of applied current density during discharge.</p> Full article ">Figure 5
<p>Comparison of the modeling charge and discharge behaviors of a Zn/Br<sub>2</sub> flow battery stack composed of 8 cells with the experimental data.</p> Full article ">Figure 6
<p>Variations of the internal currents as a function of time during (<b>a</b>) charging and (<b>b</b>) discharging with the constant current of 20 A.</p> Full article ">Figure 7
<p>Distributions of internal currents at 50% state of charge (SOC) during charging and discharging with the constant current of 20 A.</p> Full article ">Figure 8
<p>Variations of the shunt currents in channels as a function of time during charging and discharging with the constant current of 20 A for the (<b>a</b>) positive and (<b>b</b>) negative electrolytes.</p> Full article ">Figure 8 Cont.
<p>Variations of the shunt currents in channels as a function of time during charging and discharging with the constant current of 20 A for the (<b>a</b>) positive and (<b>b</b>) negative electrolytes.</p> Full article ">Figure 9
<p>Variations of the shunt currents in manifolds as a function of time during charging and discharging with the constant current of 20 A for the (<b>a</b>) positive and (<b>b</b>) negative electrolytes.</p> Full article ">Figure 10
<p>Current, voltage, and energy efficiencies under various discharge conditions.</p> Full article ">
17 pages, 3982 KiB  
Article
An Improved Droop Control Method for Voltage-Source Inverter Parallel Systems Considering Line Impedance Differences
by Junjie Ma, Xudong Wang, Jinfeng Liu and Hanying Gao
Energies 2019, 12(6), 1158; https://doi.org/10.3390/en12061158 - 25 Mar 2019
Cited by 12 | Viewed by 3030
Abstract
In this paper, the effect of the line impedance difference between various inverters on power sharing with the traditional droop control method is fully analyzed. It reveals that the line impedance difference causes a significant reactive power error. An improved droop control method [...] Read more.
In this paper, the effect of the line impedance difference between various inverters on power sharing with the traditional droop control method is fully analyzed. It reveals that the line impedance difference causes a significant reactive power error. An improved droop control method to eliminate the reactive power errors caused by the line impedance errors is proposed. In the proposed method, a voltage compensation determined by the actual reactive power error between the local inverter and the average one is added into the local voltage reference based on the CAN communication. Even when the communication is interrupted, the controller will operate with the last value of the average power, which still outperforms the traditional method. The effectiveness of the proposed control method is verified by simulation and experimental results, which show the proposed method possesses the better power sharing performance and dynamic response. Full article
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<p>Diagram of inverter parallel system with two units considering line impedance.</p> Full article ">Figure 2
<p>Single-line diagram of two inverters in parallel with different line impedance.</p> Full article ">Figure 3
<p>Control configuration diagram of inverter parallel system with proposed droop control method.</p> Full article ">Figure 4
<p>Detailed block diagram of droop control method with compensation controller.</p> Full article ">Figure 5
<p>Small-signal model root trajectories with parameters variations. (<b>a</b>) Root trajectories when <span class="html-italic">k<sub>Q_i</sub></span> is varied from 0 to 1 × 10<sup>−2</sup>; (<b>b</b>) Root trajectories when <span class="html-italic">k<sub>P_d</sub></span> is varied from 0 to 1 × 10<sup>−7</sup>.</p> Full article ">Figure 6
<p>The simulated communication system in Matlab.</p> Full article ">Figure 7
<p>The simulated waveforms of the communication system.</p> Full article ">Figure 8
<p>Simulation results of proposed method in simulation I. (<b>a</b>) The active power (W); (<b>b</b>) The reactive power (var); (<b>c</b>) The RMS value of inverter output voltage (V); (<b>d</b>) The inverter output voltage (V).</p> Full article ">Figure 9
<p>Simulation results of proposed method in simulation II. (<b>a</b>) The active power (W); (<b>b</b>) The reactive power (var); (<b>c</b>) The current waveforms of two inverters around 0.3 s (A); (<b>d</b>) The current waveforms of two inverters around 0.5 s (A).</p> Full article ">Figure 10
<p>Performance with the communication delay. (<b>a</b>) The active power (W); (<b>b</b>) The reactive power (var).</p> Full article ">Figure 11
<p>Photograph of experimental prototype of two-inverter parallel system.</p> Full article ">Figure 12
<p>The experimental active/reactive power of proposed method in experiment I.</p> Full article ">Figure 13
<p>Experimental waveforms of current and voltage in dynamic process of proposed method in experiment II: (<b>a</b>) with repetitive step change of non-linear load; (<b>b</b>) during T<sub>1</sub>; (<b>c</b>) during T<sub>2</sub>.</p> Full article ">Figure 14
<p>The waveforms of the active and reactive power in experiment III: (<b>a</b>) The proposed method; (<b>b</b>) The traditional method.</p> Full article ">Figure 15
<p>Current and voltage experimental waveforms of proposed method in experiment III: (<b>a</b>) in a long time scale; (<b>b</b>) during T<sub>1</sub>; (<b>c</b>) during T<sub>2</sub>.</p> Full article ">Figure 16
<p>The performance of power sharing with a time delay difference in communication system.</p> Full article ">
20 pages, 5284 KiB  
Article
Improvements of the Starting Performance of A Novel Brushless Doubly-fed Motor Based on the Composite Coils
by Zhiwei Ruan, Chaohao Kan, Chenglong Chu, Taian Ren and Qiuming Chen
Energies 2019, 12(6), 1157; https://doi.org/10.3390/en12061157 - 25 Mar 2019
Viewed by 2991
Abstract
Brushless doubly-fed motor (BDFM) has well applicable potentials in the speed control driving field due to its excellent speed regulation performance. However, the poor starting performance becomes a shortage that still limits the development and application of wound BDFM. To solve the problem, [...] Read more.
Brushless doubly-fed motor (BDFM) has well applicable potentials in the speed control driving field due to its excellent speed regulation performance. However, the poor starting performance becomes a shortage that still limits the development and application of wound BDFM. To solve the problem, this paper presents a novel BDFM adopted rotor winding based on the principle of the composite coil. Both the principle of the composite coil and the designed example of the rotor winding are analyzed in detail in this content, and the stator winding designed by the change-pole method is described. The performance of the prototype was tested by simulation and experiments, both results reveal that this method can effectively improve the starting performance of BDFM, the system is simplified, and the stability of it is prompted. Full article
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<p>The T-s curve.</p> Full article ">Figure 2
<p>A rotor winding branch composed separately of common coils and composite coils.</p> Full article ">Figure 3
<p>Running condition.</p> Full article ">Figure 4
<p>Starting condition.</p> Full article ">Figure 5
<p>The connection of rotor windings.</p> Full article ">Figure 6
<p>Slot electrical potential star Vectogram (<span class="html-italic">p</span> = 4).</p> Full article ">Figure 7
<p>Slot electrical potential star Vectogram (<span class="html-italic">p</span> = 3).</p> Full article ">Figure 8
<p>The wiring structure of the stator winding.</p> Full article ">Figure 8 Cont.
<p>The wiring structure of the stator winding.</p> Full article ">Figure 9
<p>Stator and rotor winding wiring diagram under different working conditions.</p> Full article ">Figure 9 Cont.
<p>Stator and rotor winding wiring diagram under different working conditions.</p> Full article ">Figure 10
<p>The port wiring diagram of the prototype when it is overall running.</p> Full article ">Figure 11
<p>Stator, rotor structures, and test platform of the prototype.</p> Full article ">Figure 12
<p>The torque-speed curve.</p> Full article ">Figure 13
<p>The fitting curve of transient torque-speed.</p> Full article ">Figure 14
<p>The phase current of the stator winding under no load.</p> Full article ">Figure 15
<p>Cloud map of magnetic flux density.</p> Full article ">Figure 15 Cont.
<p>Cloud map of magnetic flux density.</p> Full article ">Figure 16
<p>Tooth magnetic density distribution map of stator winding corresponding to different starting modes.</p> Full article ">Figure 16 Cont.
<p>Tooth magnetic density distribution map of stator winding corresponding to different starting modes.</p> Full article ">Figure 17
<p>Test waveforms of stator winding phase current of BDFM prototype (mode 1).</p> Full article ">Figure 18
<p>Test waveforms of the phase current of the stator winding in asynchronous mode.</p> Full article ">Figure 19
<p>Original waveform and fitting curve.</p> Full article ">Figure 20
<p>Comparison of peak fitting curves of starting current.</p> Full article ">Figure 20 Cont.
<p>Comparison of peak fitting curves of starting current.</p> Full article ">
14 pages, 5473 KiB  
Article
MPC with Constant Switching Frequency for Inverter-Based Distributed Generations in Microgrid Using Gradient Descent
by Hyeong-Jun Yoo, Thai-Thanh Nguyen and Hak-Man Kim
Energies 2019, 12(6), 1156; https://doi.org/10.3390/en12061156 - 25 Mar 2019
Cited by 11 | Viewed by 3822
Abstract
Variable switching frequency in the finite control set model predictive control (FCS-MPC) method causes a negative impact on the converter efficiency and the design of the output filters. Several studies have addressed the problem, but they are either complicated or require heavy computation. [...] Read more.
Variable switching frequency in the finite control set model predictive control (FCS-MPC) method causes a negative impact on the converter efficiency and the design of the output filters. Several studies have addressed the problem, but they are either complicated or require heavy computation. This study proposes a new model predictive control (MPC) method with constant switching frequency, which is simple to implement and needs only a small computation time. The proposed MPC method is based on the gradient descent (GD) method to find the optimal voltage vector. Since the cost function of the MPC method is represented in the strongly convex function, the optimal voltage vector could be found quickly by using the GD method, which reduces the computation time of the MPC method. The design of the proposed MPC method based on GD (GD-MPC) is shown in this study. The feasibility of the proposed GD-MPC is evaluated in the real-time simulation using OPAL-RT technologies. The performance of the proposed method in the case of single inverter operation or parallel inverter operation is shown. A comparison study on the proposed GD-MPC and the MPC with the concept of the virtual state vector (VSV-MPC) is presented to demonstrate the effectiveness of the proposed predictive control. Real-time simulation results show that the proposed GD-MPC method performs better with a low total harmonic distortion (THD) value of output current and short computation time, compared to the VSV-MPC method. Full article
(This article belongs to the Special Issue Control in Power Electronics)
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<p>Space vector diagram in <span class="html-italic">αβ</span> frame including virtual states.</p> Full article ">Figure 2
<p>Space vector diagram in the <span class="html-italic">αβ</span> frame, including virtual states.</p> Full article ">Figure 3
<p>Example of a gradient search for a stationary point.</p> Full article ">Figure 4
<p>Space vector diagram in the <span class="html-italic">αβ</span> frame, including virtual vector states.</p> Full article ">Figure 5
<p>Flowchart of the proposed control strategy.</p> Full article ">Figure 6
<p>Effect of learning rate <span class="html-italic">γ</span> on the control performance of the converter.</p> Full article ">Figure 7
<p>The effect of uncertain parameters on the control performance.</p> Full article ">Figure 8
<p>Performance of the proposed model predictive control (MPC) in the condition of nonlinear load.</p> Full article ">Figure 9
<p>Computation time of the proposed gradient descent model predictive control (GD-MPC), virtual state vector model predictive control (VSV-MPC), and conventional model predictive control (MPC).</p> Full article ">Figure 10
<p>Comparison on the proposed GD-MPC method and the VSV-MPC method.</p> Full article ">Figure 11
<p>Tested microgrid (MG) system with two parallel inverters.</p> Full article ">Figure 12
<p>Control performance of the proposed GD-MPC and VSV-MPC in the MG system with two parallel inverters.</p> Full article ">
13 pages, 1802 KiB  
Article
Comparison of Bioethanol Preparation from Triticale Straw Using the Ionic Liquid and Sulfate Methods
by Małgorzata Smuga-Kogut, Bartosz Walendzik, Daria Szymanowska-Powalowska, Joanna Kobus-Cisowska, Janusz Wojdalski, Mateusz Wieczorek and Judyta Cielecka-Piontek
Energies 2019, 12(6), 1155; https://doi.org/10.3390/en12061155 - 25 Mar 2019
Cited by 16 | Viewed by 3578
Abstract
Triticale straw constitutes a potential raw material for biofuel production found in Poland in considerable quantities. Thus far, production of bioethanol has been based on food raw materials such as cereal seeds, sugar beets or potatoes, and the biofuel production methods developed for [...] Read more.
Triticale straw constitutes a potential raw material for biofuel production found in Poland in considerable quantities. Thus far, production of bioethanol has been based on food raw materials such as cereal seeds, sugar beets or potatoes, and the biofuel production methods developed for these lignocellulose raw materials can threaten the environment and are inefficient. Therefore, this study aimed to compare of methods for pretreatment of triticale straw using 1-ethyl-3-methylimidazolium acetate and the sulfate method in the aspect of ethanol production intended for fuel. Based on the conducted experiments it has been determined that the use of 1-ethyl-3-methylimidazolium acetate for the pretreatment of triticale straw resulted in an increase of reducing sugars after enzymatic hydrolysis and ethyl alcohol after alcoholic fermentation. Furthermore, the study compared the efficiency of enzymatic hydrolysis of triticale straw without pretreatment, after processing with ionic liquid, recycled ionic liquid and using sulfate method, allowing a comparison of these methods. The more favorable method of lignocellulose material purification was the use of ionic liquid, due to the lower amount of toxic byproducts formed during the process, and the efficiency test results of bioethanol production using pretreatment with ionic liquid and sulfate method were similar. Ionic liquid recycling after pretreatment of rye straw using lyophilization allowed us to reuse this solvent to purify rye straw, yet the efficiency of this method remained at a low level. As a result of the conducted study it was determined that the use of ionic liquid-1-ethyl-3-methylimidazolium acetate enhanced the yield of bioethanol from triticale straw from 1.60 g/dm3 after processing without pre-treatment to 10.64 g/dm3 after pre-treatment. Full article
(This article belongs to the Special Issue Advanced Technologies of Lignocellulosic Biomass Conversion)
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<p>The concentration of sugars obtained after the enzymatic hydrolysis process of triticale straw: 1—control sample, without pretreatment; 2—after pretreatment with ionic liquid; 3—after chemical pretreatment (sulfate method); 4—after pretreatment using recycled ionic liquid.</p> Full article ">Figure 2
<p>Screen for variables describing enzymatic hydrolysis process.</p> Full article ">Figure 3
<p>PCA scores plot of triticale straw pretreated with ionic liquid, recycled ionic liquid, sulfate method, untreated (control).</p> Full article ">Figure 4
<p>Concentration of ethyl alcohol after 96 h of alcoholic fermentation of triticale straw: 1—control sample; 2—pretreated with ionic liquid; 3—pretreated with white bleach (sulfate method); 4—pretreated with recycled ionic liquid.</p> Full article ">Figure 5
<p>Screen for variables describing the changes in the concentration of ethyl alcohol after fermentation.</p> Full article ">Figure 6
<p>PCA scores plot of triticale straw pretreatment by ionic liquid, recycled ionic liquid or sulfate method, untreated (control).</p> Full article ">
22 pages, 1226 KiB  
Article
Quantitative and Qualitative Assessment of Job Role Localization in the Oil and Gas Industry: Global Experiences and National Differences
by Jack Pegram, Gioia Falcone and Athanasios Kolios
Energies 2019, 12(6), 1154; https://doi.org/10.3390/en12061154 - 25 Mar 2019
Cited by 2 | Viewed by 4344
Abstract
Job role localization is the replacement of expatriates by competent host country nationals. This study investigates the viability of localizing job roles in the oil and gas industry in two stages. The first stage addresses the global level using a survey about local [...] Read more.
Job role localization is the replacement of expatriates by competent host country nationals. This study investigates the viability of localizing job roles in the oil and gas industry in two stages. The first stage addresses the global level using a survey about local content issues. The second stage focuses on the national level using interviews to investigate how national factors can affect job role localization in Ghana, one of Africa’s oil and gas producing nations. The findings show that different stakeholders often share opinions about local content issues. At the national level there are many national context specific factors that affect job role localization including legislations, culture, attitudes and experience within the labour market. This study finds that localization is becoming increasingly prevalent worldwide. Oil and gas companies must adapt their localization strategies to the national context where they are operating. Full article
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<p>Responses by organization type to “all job roles should be localized rather than using expatriate labour”.</p> Full article ">Figure 2
<p>Responses by organization type to “national and local governments are completely aligned in their national development strategies”.</p> Full article ">Figure 3
<p>Responses by organization type to “the socio-economic benefits from oil and gas projects are evenly distributed across the economy”.</p> Full article ">Figure 4
<p>Responses by organization type to “investing early in local education institutions will ensure local people are trained to industry standards”.</p> Full article ">
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