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Keywords = solar thermal energy

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21 pages, 7149 KiB  
Article
Experimental Testing Results on Critical Components for Molten Salt-Based CSP Systems
by Valeria Russo, Giuseppe Petroni, Francesco Rovense, Mauro Giorgetti, Giuseppe Napoli, Gianremo Giorgi and Walter Gaggioli
Energies 2025, 18(1), 198; https://doi.org/10.3390/en18010198 (registering DOI) - 5 Jan 2025
Abstract
Concentrated Solar Power (CSP) plants integrated with Thermal Energy Storage (TES) represent a promising renewable energy source for generating heat and power. Binary molten salt mixtures, commonly referred to as Solar Salts, are utilized as effective heat transfer fluids and storage media due [...] Read more.
Concentrated Solar Power (CSP) plants integrated with Thermal Energy Storage (TES) represent a promising renewable energy source for generating heat and power. Binary molten salt mixtures, commonly referred to as Solar Salts, are utilized as effective heat transfer fluids and storage media due to their thermal stability and favorable thermophysical properties. However, these mixtures pose significant challenges due to their high solidification temperatures, around 240 °C, which can compromise the longevity and reliability of critical system components such as pressure sensors and bellows seal globe valves. Thus, it is essential to characterize their performance, assess their reliability under various conditions, and understand their failure mechanisms, particularly in relation to temperature fluctuations affecting the fluid’s viscosity. This article discusses experimental tests conducted on a pressure sensor and a bellows seal globe valve, both designed for direct contact with molten salts in CSP environments, at the ENEA Casaccia Research Center laboratory in Rome. The methodology for conducting these experimental tests is detailed, and guidelines are outlined to optimize plant operation. The findings provide essential insights for improving component design and maintenance to minimize unplanned plant downtime. They also offer methodologies for installing measurement instruments and electrical heating systems on the components. Full article
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<p>(<b>a</b>) Comprehensive view of the MoSE laboratory-scale test loop; (<b>b</b>) view of the plant from the control room.</p>
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<p>Overview of process showing lines and main components of the plant. In red circles the Pressure Sensor and the Bellows Seal Globe Valve considered in this analysis.</p>
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<p>A detail view of the piping line containing the pressure sensor and the bellows seal globe valve considered in the study.</p>
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<p>(<b>a</b>) Preparation phase of the molten salt mixture before the tank filling; (<b>b</b>) a view inside the tank during the installation of some thermocouples on the electric heaters external casings.</p>
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<p>(<b>a</b>) A schematic section drawing of the bellows seal globe vale; (<b>b</b>) the valve during the electric cables assembly and the thermocouples welding on its casing; (<b>c</b>) the Bellows Seal Globe Valve after the final assembly.</p>
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<p>(<b>a</b>) schematic drawing of the pressure sensor; (<b>b</b>) view of the instrument during electric tracing assembly and thermocouples installation; (<b>c</b>) the instrument after the final assembly.</p>
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<p>(<b>a</b>) detail view of the bellows seal globe valve; (<b>b</b>) schematic drawing of the bellows seal globe valve with indication of the thermocouples position on its casing.</p>
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<p>(<b>a</b>) A detailed view of the pressure sensor; (<b>b</b>) a schematic drawing of the pressure sensor with indication of the thermocouples position on its casing.</p>
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<p>Measured temperature profiles of the salt in the piping line and on the bellows seal globe valve casing. Test I (<b>a</b>). Test II (<b>b</b>).</p>
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<p>Measured temperature profiles of the salt in the piping line and on the pressure sensor casing. Test III (<b>a</b>). Test IV (<b>b</b>).</p>
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<p>Temperature trends on the bellows seal globe valve body vs time. (<b>a</b>) Test V. (<b>b</b>) Test VI.</p>
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20 pages, 5958 KiB  
Article
Scalable Fabrication of Light-Responsive Superhydrophobic Composite Phase Change Materials via Bionic-Engineered Wood for Solar–Thermal Energy Management
by Yang Meng, Jiangyu Zhang, Yuchan Li, Hui Jiang and Delong Xie
Molecules 2025, 30(1), 168; https://doi.org/10.3390/molecules30010168 (registering DOI) - 4 Jan 2025
Viewed by 260
Abstract
The growing demand for sustainable energy storage solutions has underscored the importance of phase change materials (PCMs) for thermal energy management. However, traditional PCMs are always inherently constrained by issues such as leakage, poor thermal conductivity, and lack of solar energy conversion capacity. [...] Read more.
The growing demand for sustainable energy storage solutions has underscored the importance of phase change materials (PCMs) for thermal energy management. However, traditional PCMs are always inherently constrained by issues such as leakage, poor thermal conductivity, and lack of solar energy conversion capacity. Herein, a multifunctional composite phase change material (CPCM) is developed using a balsa-derived morphology genetic scaffold, engineered via bionic catechol surface chemistry. The scaffold undergoes selective delignification, followed by a simple, room-temperature polydopamine (PDA) modification to deposit Ag nanoparticles (Ag NPs) and graft octadecyl chains, resulting in a superhydrophobic hierarchical structure. This superhydrophobicity plays a critical role in preventing PCM leakage and enhancing environmental adaptability, ensuring long-term stability under diverse conditions. Encapsulating stearic acid (SA) as the PCM, the CPCM exhibits exceptional stability, achieving a high latent heat of 175.5 J g−1 and an energy storage efficiency of 87.7%. In addition, the thermal conductivity of the CPCM is significantly enhanced along the longitudinal direction, a 2.1-fold increase compared to pure SA, due to the integration of Ag NPs and the unidirectional wood architecture. This synergy also drives efficient photothermal conversion via π-π stacking interactions of PDA and the surface plasmon effects of Ag NPs, enabling rapid solar-to-thermal energy conversion. Moreover, the CPCM demonstrates remarkable water resistance, self-cleaning ability, and long-term thermal reliability, retaining its functionality through 100 heating–cooling cycles. This multifunctional balsa-based CPCM represents a breakthrough in integrating phase-change behavior with advanced environmental adaptability, offering promising applications in solar–thermal energy systems. Full article
(This article belongs to the Special Issue Recent Advances in Superhydrophobic Materials and Their Application)
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Graphical abstract
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<p>Schematic diagram of the preparation of CPCMs encapsulated by balsa-derived morphology genetic superhydrophobic scaffold.</p>
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<p>(<b>a</b>) Digital photograph of the bioinspired superhydrophobic modification process of the balsa-derived scaffold; (<b>b</b>) water-repellent mirror effect on the superhydrophobic balsa-derived scaffold; (<b>c</b>) durability of the superhydrophobic interface on the balsa-derived scaffold.</p>
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<p>SEM images of balsa-derived scaffolds at different resolutions, showing both cross-sectional views and tracheid surfaces: (<b>a1</b>–<b>a3</b>) RW, (<b>b1</b>–<b>b3</b>) DW, (<b>c1</b>–<b>c3</b>) PW@Ag, and (<b>d1</b>–<b>d3</b>) PW@Ag-O.</p>
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<p>(<b>a</b>) FTIR spectra, (<b>b</b>) XRD patterns, and (<b>c</b>) XPS survey spectra of raw balsa wood (RW), delignified balsa wood (DW), PDA-modified balsa wood (PW), and ODA/PDA/Ag NP hybrid-modified DW (PW@Ag-O). High-resolution XPS spectrum of PW@Ag-O: (<b>d</b>) O1s, (<b>e</b>) N1s, and (<b>f</b>) Ag3d.</p>
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<p>(<b>a1</b>) Binary distribution map and (<b>a2</b>) pore size distribution statistics of the RW cross-sectional microtopography; (<b>b1</b>) binary distribution map and (<b>b2</b>) pore size distribution statistics of the PW@Ag-O cross-sectional microtopography; (<b>c</b>) FTIR spectra and (<b>d</b>) TGA curves of pure SA, modified balsa-derived scaffolds, and their composites; microstructures of CPCMs at different resolutions: (<b>e1</b>,<b>e2</b>) DW/SA, (<b>f1</b>,<b>f2</b>) hygroscopic DW/SA, and (<b>g1</b>,<b>g2</b>) PW@Ag-O/SA; (<b>h</b>) digital image of underwater superoleophobic test of DW; (<b>i</b>) schematic of interfacial enhancement mechanism in CPCMs.</p>
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<p>Pure SA and balsa-based CPCMs: (<b>a</b>) DSC thermograms during the cooling process; (<b>b</b>) DSC thermograms during the heating process; (<b>c</b>) statistical analysis of phase-change enthalpy; (<b>d</b>) long thermal conductivity; (<b>e</b>) longitudinal thermal conductivity; and (<b>f</b>) DSC thermograms of PW@Ag-O/SA over 100 thermal cycling tests.</p>
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<p>(<b>a</b>) Digital image of the photothermal conversion testing system for balsa-based CPCMs and the mechanism of photothermal conversion pathways; (<b>b</b>) heating and (<b>c</b>) cooling profiles of DW/SA and PW@Ag-O/SA during solar–thermal energy utilization; (<b>d</b>) infrared thermographic images of DW/SA and PW@Ag-O/SA under one-sun irradiation.</p>
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<p>(<b>a</b>) Water contact angles and corresponding digital photographs of DW, SA, DW/SA, and PW@Ag-O/SA; (<b>b</b>) digital photographs of water absorption experiments for DW/SA and PW@Ag-O/SA; (<b>c</b>) water absorption curves of DW, SA, DW/SA, and PW@Ag-O/SA; (<b>d</b>) water contact angles of PW@Ag-O/SA under different operating temperatures and after 100 cycles; (<b>e</b>) self-cleaning behavior of PW@Ag-O/SA captured in digital images.</p>
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43 pages, 11380 KiB  
Review
Thermoelectric Generators Applied as a Power Source in CubeSats: State of the Art
by Gabriel Brugues Soares, Jorge Javier Gimenez Ledesma, Eder Andrade da Silva and Oswaldo Hideo Ando Junior
Energies 2025, 18(1), 173; https://doi.org/10.3390/en18010173 - 3 Jan 2025
Viewed by 281
Abstract
This systematic review outlines the application of thermoelectric generators (TEGs) as energy sources in CubeSats. While CubeSats currently rely on solar cells with efficiencies between 16.8% and 32.2%, their performance diminishes with increased distance from the Sun. TEGs, although used in radioisotope thermoelectric [...] Read more.
This systematic review outlines the application of thermoelectric generators (TEGs) as energy sources in CubeSats. While CubeSats currently rely on solar cells with efficiencies between 16.8% and 32.2%, their performance diminishes with increased distance from the Sun. TEGs, although used in radioisotope thermoelectric generators (RTGs) for satellites, remain underutilized in CubeSats. A literature review revealed 33 relevant articles, with 21.2% employing simulation software to evaluate thermal behavior. Among 34 patents, only one mentioned micro-TEGs, with most focusing on structural improvements. Patent activity peaked between 2016 and 2020, emphasizing structural and thermal optimization, but no patents addressed TEGs as energy sources for CubeSats, highlighting a significant research gap. TEGs present a viable solution for harnessing residual heat in CubeSats. Full article
(This article belongs to the Special Issue Advanced Research on Heat Exchangers Networks and Heat Recovery)
18 pages, 9711 KiB  
Article
Cr3+-Doped Anatase-Phase TiO2 Nanocrystals with (101) and (004) Dominant Facets: Synthesis and Characterization
by Rayhan Hossain and Allen Apblett
Catalysts 2025, 15(1), 33; https://doi.org/10.3390/catal15010033 - 2 Jan 2025
Viewed by 262
Abstract
Anatase-phase rod-shaped TiO2 nanocrystals are prepared by the solvothermal method, the surface is metalated, and doped nanocrystals are achieved by thermal diffusion of surface metal ions. Incorporation of dopant ions into TiO2 lattice enhances the visible light absorption of the material [...] Read more.
Anatase-phase rod-shaped TiO2 nanocrystals are prepared by the solvothermal method, the surface is metalated, and doped nanocrystals are achieved by thermal diffusion of surface metal ions. Incorporation of dopant ions into TiO2 lattice enhances the visible light absorption of the material and in some cases can increase the rate of photocatalysis. Even though there are overflowing studies on the preparation of doped TiO2 materials, there are no methods that enable the precise control of dopant concentration in TiO2 nanocrystals. We have developed a method to load the surface of oleic acid stabilized anatase-phase rod-shaped TiO2 nanocrystals (approx. 3 ± 1 nm diameter and 40 ± 10 nm long) with transition metal ions followed by ion diffusion to prepare metal-doped nanocrystals with exact control of the dopant concentration. Specifically, in this work, Cr3+ adsorbs TiO2 nanorods to yield a green colloid, followed by ion diffusion at elevated temperature. After removal of any remaining surface Cr3+, tan-colored chromium-doped TiO2 nanorods can be obtained. Electron microscopy and powder X-ray diffraction indicate no change in nanocrystal size and morphology throughout the process. The TiO2 nanorods play an important role in photocatalysis owing to their excellent chemical and physical properties. Titanium dioxide is a low-cost, non-toxic, highly stable, chemically robust material. Doped TiO2 materials have found application in photocatalysis (oxidative degradation of organic molecules, hydrogen evolution), photovoltaics, solar cells, lithium-ion batteries, supercapacitors, and sensors. TiO2 photocatalysis is also the basis for clean energy technologies, such as dye-sensitized solar cells and photoelectrochemical cells. In photocatalysis applications, nanocrystalline TiO2 presents advantages of a high surface area, ability to control the surface facet, and minimized bulk recombination. Full article
(This article belongs to the Special Issue TiO2 Photocatalysts—Towards Sustainable Chemistry)
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<p>TEM images of (<b>A</b>) synthesized TiO<sub>2</sub> and of (<b>B</b>) 7% Cr<sup>3+</sup><sub>(doped)</sub>-TiO<sub>2</sub> nanorods. The scale bar is 100 nm (<b>A</b>,<b>B</b>). (<b>C</b>) High-resolution TEM image of anatase TiO<sub>2</sub> nanorods with a scale bar of 5 nm. (<b>D</b>) The high-resolution image of the boxed region is shown by fast Fourier transform (FFT).</p>
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<p>XRD pattern of (<b>A</b>) TiO<sub>2</sub> nanorods and (<b>B</b>) Cr<sup>3+</sup><sub>(doped)</sub>-TiO<sub>2</sub> samples with different dopant concentrations. The labels indicate the theoretical ratio of Cr:TiO<sub>2</sub> in the preparation of Cr<sup>3+</sup><sub>(surface)</sub>-TiO<sub>2</sub>.</p>
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<p>UV–visible absorption spectra of (<b>A</b>) synthesized TiO<sub>2</sub> and (<b>B</b>) 7% Cr<sup>3+</sup><sub>(doped)</sub>-TiO<sub>2</sub> nanorods dispersed in hexane.</p>
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<p>SEM images of prepared 7% Cr<sup>3+</sup><sub>(doped)</sub>-TiO<sub>2</sub> nanorods.</p>
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<p>Energy dispersive spectroscopy (EDS) spectrum of anatase-phase Cr<sup>3+</sup><sub>(doped)</sub>-TiO<sub>2</sub> nanorods. The EDS analysis shows the peaks from both Ti and Cr and thus indicates the presence of both particles. EDS mapping shows single-particle EDS analysis. Scale bars: 10 μm.</p>
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<p>PL spectra of undoped and Cr<sup>3+</sup><sub>(doped)</sub>-TiO<sub>2</sub> nanocrystals with different dopant concentrations. PL spectra measured with the excitation wavelength at 290 nm (<b>left</b>) and 350 nm (<b>right</b>).</p>
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<p>UV–visible absorption spectrum of Cr<sup>3+</sup><sub>(doped)</sub>-TiO<sub>2</sub> after treatment with 8-HQ.</p>
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<p>UV–visible absorption spectrum of Cr-doped TiO<sub>2</sub> after treatment with TPP.</p>
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<p>Tauc plot for prepared Cr-doped TiO<sub>2</sub> nanorods. The plot shows a bandgap range of 2.2–2.7 eV, narrowed by Cr doping, enhancing visible light absorption for photocatalytic and solar applications.</p>
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<p>Resistance versus film thickness plot for thin-film samples of TiO<sub>2</sub>- and Cr-doped TiO<sub>2</sub> on ITO-coated glass substrate.</p>
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<p>Time-dependent photocatalytic hydrogen production. Rate of hydrogen generation using 200 W Xe Arc lamp as light source.</p>
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39 pages, 7824 KiB  
Article
The Building Energy Performance Gap in Multifamily Buildings: A Detailed Case Study Analysis of the Energy Demand and Collective Heating System
by Stijn Van de Putte, Marijke Steeman and Arnold Janssens
Sustainability 2025, 17(1), 252; https://doi.org/10.3390/su17010252 - 1 Jan 2025
Viewed by 459
Abstract
The building energy performance gap, resulting from a discrepancy between the actual energy use and theoretical calculations, remains a persistent issue in building design. This study examines the energy performance of three multifamily buildings with a collective heating system powered by gas boilers [...] Read more.
The building energy performance gap, resulting from a discrepancy between the actual energy use and theoretical calculations, remains a persistent issue in building design. This study examines the energy performance of three multifamily buildings with a collective heating system powered by gas boilers and solar collectors: two that underwent deep renovation and one newly built. An extensive on-site monitoring system provides detailed data on both the heating demand and the final energy use. To ensure comparability, the total energy use of each unit is normalised using the energy signature method. The findings show the large spread of actual energy demands due to a wide variation in user profiles. The majority of dwellings have an actual energy use that is significantly higher than calculated, which is largely attributable to space heating. The gap is further exacerbated by substantial heat losses within the building’s heating system and by limited gains from the solar collectors, indicating discrepancies between design models and operational realities. To bridge this gap, there is a need for rigorous commissioning processes, at least during the initial operation phase start-up and ideally continuously. This can ensure more effective utilisation of renewable energy sources and reduce energy inefficiencies. Full article
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<p>The increasing concave relation between the theoretical (<span class="html-italic">Q<sub>theo</sub></span>) and the actual (<span class="html-italic">Q<sub>act</sub></span>) energy use illustrating the difference between theoretical, anticipated and actual energy savings (resp. <span class="html-italic">ΔQ<sub>theo</sub></span>, <span class="html-italic">ΔQ<sub>antic</sub></span> and <span class="html-italic">ΔQ<sub>act</sub></span>) due to an energy performance improvement.</p>
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<p>Flowchart of the research procedure to evaluate the building energy performance gap (BEPG) and the energy savings deficit (ESD).</p>
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<p>Three building blocks of project ‘Drie Hofsteden’, with (<b>a</b>) the original building blocks DH IV (left) and DH V (right) and (<b>b</b>) the renovated DH IV (left), newly constructed DH VI (middle) and renovated DH V (right) after completion of the works.</p>
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<p>Three building blocks of project ‘Drie Hofsteden’, with (<b>a</b>) the original building blocks DH IV (left) and DH V (right) and (<b>b</b>) the renovated DH IV (left), newly constructed DH VI (middle) and renovated DH V (right) after completion of the works.</p>
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<p>Occupant characteristics for the three building blocks with (<b>a</b>) the occupancy of the apartments and (<b>b</b>) the cumulative age distribution of the heads of household.</p>
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<p>Measured energy use intensity for SH and DHW of a fully enclosed apartment in DH V monitored in detail between April 2017 and April 2022.</p>
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<p>Graphical representation of the regression coefficients for the energy signature of a building, based on (<b>a</b>) a simple linear regression and (<b>b-1</b>) a multiple linear regression with two explanatory variables, with (<b>b-2</b>) showing how the interaction between the solar irradiation and the exterior temperature defines the base point.</p>
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<p>Energy signature of each building based on 1 explanatory variable for (<b>a</b>) the theoretical calculations and (<b>b</b>) the actual measurements.</p>
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<p>Normalised theoretical and actual monthly energy demand with an indication of the share of SH and DHW during one year for (<b>a</b>) DH IV, (<b>b</b>) DH V and (<b>c</b>) DH VI.</p>
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<p>Actual energy demand as a function of the theoretical energy demand (<b>a</b>) in total, (<b>b</b>) for DHW and (<b>c</b>) for SH, with the diagonals representing the size of the BEPG.</p>
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<p>Volume-weighted daily average temperature of the whole dwelling before (DH IV, blue) and after refurbishment (DH V, red).</p>
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<p>Theoretical monthly heat losses, heat gains and net energy demand for SH for a single, fully enclosed apartment (<span class="html-italic">q<sub>SH,net</sub></span> = 0.94 kWh/(m<sup>2</sup>·a)).</p>
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<p>Sankey diagram with normalised annual heat flows in DH IV–VI.</p>
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<p>Actual and theoretical energy use of DH IV–VI and DH V after renovation.</p>
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<p>Actual energy use of DH IV before renovation and theoretical and actual energy use after renovation.</p>
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<p>Hydraulic scheme of the heating system of DH V.</p>
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<p>Hydraulic scheme of the heating system of DH IV–VI.</p>
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<p>Launch of the calorimeters, subdivided by building (DH IV: blue, DH V: red, DH VI: green) and by vertical core.</p>
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<p>Monthly actual, normal and theoretical climate parameters for Beitem with (<b>a</b>) the annual exterior temperature variation and (<b>b</b>) its relation with total solar irradiation.</p>
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28 pages, 30828 KiB  
Article
Experimental Evaluation of the Power Output and Efficiency of a Small Solar-Boosted OTEC Power Plant
by Reemal D. Prasad, Muzammil Ali and Mohammed Rafiuddin Ahmed
Energies 2025, 18(1), 127; https://doi.org/10.3390/en18010127 - 31 Dec 2024
Viewed by 311
Abstract
Ocean thermal energy is an emerging energy source that holds great promise, especially for tropical countries. Ocean thermal energy conversion (OTEC) efficiency can be improved by raising the temperature difference between the hot water and the cold water. In the work reported here, [...] Read more.
Ocean thermal energy is an emerging energy source that holds great promise, especially for tropical countries. Ocean thermal energy conversion (OTEC) efficiency can be improved by raising the temperature difference between the hot water and the cold water. In the work reported here, a laboratory-scale closed-cycle OTEC system was constructed and tested for power output and efficiency. A solar heating system heated the water up to 70 °C. Experiments were conducted at cold water inlet temperatures of 5 °C, 8 °C, and 11 °C. The mass flow rate of the hot water was varied, while that of the cold water was kept constant. Increasing the hot water inlet temperature from 30 °C to 70 °C while keeping the cold water inlet temperature constant at 5 °C at the highest mass flow rate of hot water increased the power output from 32.07 W to 66.68 W (107.9% increase) and the thermal efficiency from 1.96% to 4.37% (123% increase). The pressure drop across the turbine was higher for a larger temperature difference between the hot water and cold water, indicating a higher transfer of energy to the working fluid. Increasing the mass flow rate of the hot water for the increasing temperature difference between the hot water and cold water increased the power output and efficiency due to the increase in the energy transfer from the hot water to the working fluid. Experimental works on solar-boosted OTEC systems are very rare, and this work should pave the way for practical implementation. Full article
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<p>A photograph of the evacuated-tube solar water-heating system.</p>
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<p>Layout of the evacuated tubes and the header manifold.</p>
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<p>Schematic diagram of the solar-boosted OTEC system.</p>
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<p>T-s diagram of the closed OTEC cycle.</p>
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<p>A photograph of the small OTEC power plant setup.</p>
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<p>A photograph of the turbine housing.</p>
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<p>A closer view of the shell-and-tube heat exchanger that was used as a condenser.</p>
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<p>Variation of water temperature in the evacuated tubes and the storage tank over a day.</p>
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<p>Variation of water temperature in the storage tank from 6.00 a.m. to 12.00 a.m. at different daily averaged solar insolations.</p>
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<p>Thermal efficiency of the system and power output against the hot water flow rates at hot water inlet temperatures of 30 °C (<b>A</b>) to 70 °C (<b>E</b>).</p>
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<p>Variation of the thermal efficiency and the power output with the cold water inlet temperature at different hot water flow rates at hot water inlet temperatures of 30 °C (<b>A</b>) to 70 °C (<b>E</b>).</p>
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<p>Thermal efficiency of the system and power output against the hot water inlet temperature at cold water inlet temperatures of 5 °C (<b>A</b>) to 7 °C (<b>C</b>).</p>
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<p>Turbine inlet pressure against the operating temperature difference for different cold water inlet temperatures.</p>
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<p>Pressure drop across the turbine against the operating temperature difference for different cold water inlet temperatures.</p>
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<p>Turbine inlet pressure and turbine pressure drop against the operating temperature difference.</p>
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<p>Effect of operating temperature difference on the thermal efficiency at different mass flow rates of the warm water.</p>
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<p>Effect of operating temperature difference on the power output at different mass flow rates of the warm water.</p>
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<p>Variation of the thermal efficiency and the power output against the pressure drop across the turbine.</p>
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<p>Thermal efficiency of the cycle and power output against the turbine inlet pressure.</p>
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<p>Thermal efficiency and power output at different turbine inlet temperatures.</p>
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<p>Thermal efficiency as a function of the temperature drop of the hot water at different flow rates at cold water inlet temperatures of 5 °C (<b>A</b>) to 11 °C (<b>C</b>).</p>
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<p>Power output of the system against the temperature drop of the hot water at different flow rates at cold water inlet temperatures of 5 °C (<b>A</b>) to 11 °C (<b>C</b>).</p>
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17 pages, 5313 KiB  
Article
Thermofluidics in Water-in-Glass Evacuated-Tube Solar Collectors Analysis Based on the Symmetry Conditions of Heat Flux and Tilt Angle
by Elder M. Mendoza Orbegoso, Josmell Alva Alcántara, Luis Julca Verástegui, Juan Carlos Bengoa, Daniel Marcelo-Aldana, Raúl La Madrid Olivares and Konstantinos G. Kyprianidis
Symmetry 2025, 17(1), 44; https://doi.org/10.3390/sym17010044 - 29 Dec 2024
Viewed by 372
Abstract
This research aims to determine the primary thermofluidic correlations describing the thermosiphon effect under idealized steady-state conditions, considering water-in-glass evacuated-tube geometry, tilt angle, and heat flux. A numerical model based on Computational Fluid Dynamics (CFD) was developed to obtain these correlations for water-in-glass [...] Read more.
This research aims to determine the primary thermofluidic correlations describing the thermosiphon effect under idealized steady-state conditions, considering water-in-glass evacuated-tube geometry, tilt angle, and heat flux. A numerical model based on Computational Fluid Dynamics (CFD) was developed to obtain these correlations for water-in-glass evacuated-tube solar collectors. Initial validation against experimental velocity and temperature profiles was necessary. With a validated CFD model, thermofluidic correlations were determined, expressed as dimensionless parameters such as Re, Gr, and Pr, water-in-glass evacuated-tube dimensions, and tilt angle. Symmetry was exploited in the water-in-glass evacuated-tube geometry for both validation simulations and the development of thermofluidic correlations. Contrary to correlations recorded in the literature, the correlations obtained in this study indicate an increase in water flow and a decrease in mean temperature with increasing tilt angle. These correlations are crucial for the energy–exergy balance formulations used in the analysis and design of such thermal systems. Full article
(This article belongs to the Special Issue Symmetry in Thermal Fluid Sciences and Energy Applications)
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<p>Geometric and construction scheme used by Budihardjo [<a href="#B12-symmetry-17-00044" class="html-bibr">12</a>]. (<b>a</b>) Geometric and constructive arrangement of the copper tube and (<b>b</b>) location of the simple thermocouples in the transverse plane of the copper tube opening.</p>
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<p>3D geometric representation of the computational domain that will be used for the validation of the model based on Computational Fluid Dynamics (<b>a</b>) front view and (<b>b</b>) 3D perspective.</p>
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<p>Discretization of the computational subdomains “WATER” and “COPPER” comprising the computational domain. (<b>a</b>) computational domain; (<b>b</b>) Enlarged view of the computational domain showing the mesh refinement near the wall.</p>
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<p>Discretization of the computational subdomains “WATER” and “COPPER” comprising the computational domain.</p>
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<p>Water velocity fields entering and exiting at the opening of the tube connected to the tank. Left—instantaneous snapshot taken over the analysis region using the PIV technique. Center—velocity vector obtained using the PIV technique. Right—result obtained from the CFD simulation.</p>
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<p>Comparison of velocity magnitude profiles crossing the tube opening connecting to the tank, obtained with the CFD model and compared with experimental PIV techniques and CFD simulation by Budihardjo [<a href="#B12-symmetry-17-00044" class="html-bibr">12</a>].</p>
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<p>Comparison of temperature profiles crossing the tube opening connecting to the tank, obtained with the CFD model and compared with experimental techniques performed by Budihardjo (2005) and with CFD simulation by Budihardjo [<a href="#B12-symmetry-17-00044" class="html-bibr">12</a>] considering, and not considering, three-dimensional conduction.</p>
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<p>Mesh sensitivity analysis for (<b>a</b>) top face wall temperature and (<b>b</b>) entrance water mass flow.</p>
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<p>Axial velocity contours of water within the water-in-glass evacuated-tube solar collectors subjected to 1000 W/m<sup>2</sup> on the upper surface of the internal tube for angles of 5°, 15°, 30°, and 45° with respect to the horizontal.</p>
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<p>Temperature contours of water within the water-in-glass evacuated-tube solar collectors subjected to 1000 W/m<sup>2</sup> on the upper surface of the internal tube for angles of 5°, 15°, 30°, and 45° with respect to the horizontal.</p>
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<p>Flow structure in a 48 mm diameter and 1800 mm length of a single-ended tube tilted at 15° and heated from the top at 1000 W/m<sup>2</sup>.</p>
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<p>Correlation of dimensionless thermofluidic parameters obtained from CFD simulation.</p>
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36 pages, 10648 KiB  
Article
An Integrated Electricity–Gas–Heat Energy System Based on the Synergy of Long- and Short-Term Energy Storage
by Min Zhang, Jinhao Wang, Huiqiang Zhi, Jun Zhao, Xiao Chang, Shifeng Zhang, Xiangyu Guo and Tengxin Wang
Energies 2025, 18(1), 55; https://doi.org/10.3390/en18010055 - 27 Dec 2024
Viewed by 260
Abstract
New energy sources, such as wind and solar energy, have been widely adopted; however, their volatility and instability have become the key issues restricting their utilization. To cope with this challenge, hybrid energy storage systems, as flexible regulation schemes, are capable of balancing [...] Read more.
New energy sources, such as wind and solar energy, have been widely adopted; however, their volatility and instability have become the key issues restricting their utilization. To cope with this challenge, hybrid energy storage systems, as flexible regulation schemes, are capable of balancing the supply and demand of the power system according to different timescales and power demands, and enhancing the efficiency and utilization of new energy sources. Therefore, this paper proposes an integrated energy system planning and optimization method based on hybrid energy storage. Firstly, an adaptive noise integration empirical modal decomposition method based on the optimization improvement of the grey wolf algorithm is designed for the power allocation strategy of the hybrid energy storage system; secondly, for the electric–gas system, an energy management strategy for the hybrid electric–gas energy storage system, taking into account the operating characteristics of the alkaline electrolyzer, is proposed in order to strengthen the complementary mechanism between electric energy storage and gas energy storage. Finally, a multi-objective planning and optimization model for a comprehensive energy system based on a hybrid energy storage system is constructed. The combined configuration of long-term and short-term energy equipment can flexibly adjust energy supply and storage strategies according to demand changes on different timescales, achieve optimal resource allocation, and ensure the stability, economy, and reliability of the system. This paper uses a park in Shanxi, China, as a case study to validate the effectiveness of the methodology proposed in this paper. The example shows that the configuration of the electrical–thermal hybrid energy storage system proposed in this paper leads to a significant improvement in the economy, with an increase in annual profit of CNY 3.78 million, or 22.96%. At the same time, environmental protection is significantly enhanced, and total annual carbon emissions are reduced by 7.4 tons, with a reduction of 19.23%. Full article
(This article belongs to the Section J1: Heat and Mass Transfer)
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<p>Architecture diagram of an integrated electrical and thermal energy system based on hybrid energy storage.</p>
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<p>Flowchart of ICEEMDAN power decomposition strategy based on GWO.</p>
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<p>Flowchart of the grey wolf optimizer (GWO) algorithm.</p>
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<p>Logic diagram of energy management strategy.</p>
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<p>System planning strategy diagram.</p>
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<p>Process of NSGA-II algorithm optimization.</p>
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<p>Electricity–gas–heat integrated energy system structure.</p>
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<p>Annual light intensity and wind speed curves: (<b>a</b>) annual solar radiation profile; (<b>b</b>) wind speed graph for the whole year.</p>
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<p>Electric heat requirements: (<b>a</b>) electricity demand curve; (<b>b</b>) heat demand curve.</p>
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<p>Timesharing tariff curve.</p>
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<p>Diagram of the model solving process.</p>
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<p>Plot of IMF component curves and residuals by order.</p>
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<p>Typical summer day supply/demand balance for the electric system.</p>
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<p>Typical daily supply and demand balance for the electric system in winter.</p>
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<p>Typical daily supply and demand balance for the electric system in transitional seasons.</p>
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<p>Typical summer day supply and demand balance of thermal system.</p>
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<p>Typical daily supply and demand balance of thermal system in winter.</p>
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<p>Typical daily supply and demand balance of the thermal system in transitional seasons.</p>
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<p>Equipment output diagram before optimization.</p>
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<p>Optimized equipment output chart.</p>
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<p>Comparison of scenarios before and after optimization. Note: The data are sourced from simulation optimization results.</p>
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28 pages, 11065 KiB  
Article
Economic Optimization of a Hybrid Power Plant with Nuclear, Solar, and Thermal Energy Conversion to Electricity
by Stylianos A. Papazis
J. Nucl. Eng. 2025, 6(1), 2; https://doi.org/10.3390/jne6010002 - 26 Dec 2024
Viewed by 383
Abstract
This research presents a new solution for optimizing the economics of energy produced by a hybrid power generation plant that converts nuclear, solar, and thermal energy into electricity while operating under load-following conditions. To achieve the benefits of cleaner electricity with minimal production [...] Read more.
This research presents a new solution for optimizing the economics of energy produced by a hybrid power generation plant that converts nuclear, solar, and thermal energy into electricity while operating under load-following conditions. To achieve the benefits of cleaner electricity with minimal production costs, multi-criteria management decisions are applied. The investigation of a hybrid system combining nuclear, solar, and thermal energy generation demonstrates the impact of such technology on the optimal price of generated energy; the introduction of nuclear reactors in hybrid systems reduces the cost of electricity production compared to the equivalent cost of energy produced by solar systems and compared to fossil fuel thermal systems. This method can be applied to hybrid energy systems with nuclear, solar, and thermal power generation plants of various sizes and configurations, making it a useful tool for engineers, researchers, and managers in the energy sector. Full article
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<p>Hybrid nuclear–solar–thermal energy generation system.</p>
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<p>Total varying load demands during 24 h.</p>
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<p>Solar irradiance during 24 h.</p>
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<p>Scenario 1. The minimal cost powers (Th1 blue, Th2 red, Th3 yellow, Th4 magenta, Th5 green) and the reserves of power (light blue with *) versus <math display="inline"><semantics> <mi>λ</mi> </semantics></math>. During 24 h, the optimal value of <math display="inline"><semantics> <mrow> <msub> <mi>λ</mi> <mi>λ</mi> </msub> </mrow> </semantics></math> changes from <math display="inline"><semantics> <mrow> <msub> <mi>λ</mi> <mi>λ</mi> </msub> </mrow> </semantics></math> = 186.7 to <math display="inline"><semantics> <mrow> <msub> <mi>λ</mi> <mi>λ</mi> </msub> </mrow> </semantics></math> = 187.35. The power outputs of Th1 and Th3 are equal and shown superposed.</p>
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<p>Scenario 1. Minimal cost powers generated by the five thermal units Th1–Th5, by the solar unit, and by the nuclear power unit during 24 h. The power generated from Th1 and Th3 are equal, shown superposed. The power of Th2 is equal to Th5 between the hours of 6:45 a.m. and 17:45 p.m. The power of Th4 is equal to the minimum limit of operation <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mrow> <mn>4</mn> <mo>,</mo> <mi>min</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Scenario 1. Total minimal costs of power generated by the solar unit (power unit 1), nuclear unit (power unit 2), and five thermal units (power units 3, 4, 5, 6, and 7) during 24 h.</p>
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<p>Scenario 2. The minimal cost powers generated by Th1–Th5 versus lambda (Th1 blue, Th2 red, Th3 yellow, Th4 magenta, Th5 green) and reserves of power (light blue with *) during 24 h. The solar unit is enabled. The nuclear unit is disabled. The optimal value of <math display="inline"><semantics> <mrow> <msub> <mi>λ</mi> <mi>λ</mi> </msub> </mrow> </semantics></math> increases from <math display="inline"><semantics> <mrow> <msub> <mi>λ</mi> <mi>λ</mi> </msub> </mrow> </semantics></math> = 188.3 to <math display="inline"><semantics> <mrow> <msub> <mi>λ</mi> <mi>λ</mi> </msub> </mrow> </semantics></math> = 189.2. The power outputs of Th1 and Th3 are equal and shown superposed.</p>
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<p>Scenario 2. Minimal cost powers generated by Th1–Th5 and by the solar unit over 24 h. The nuclear unit is disabled. The thermal unit Th1 operates at <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>P</mi> <mrow> <mn>1</mn> <mo>,</mo> <mi>max</mi> </mrow> </msub> </mrow> </semantics></math>, Th3 at <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mn>3</mn> </msub> <mo>=</mo> <msub> <mi>P</mi> <mrow> <mn>3</mn> <mo>,</mo> <mi>max</mi> </mrow> </msub> </mrow> </semantics></math>, and Th4 at <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mn>4</mn> </msub> <mo>=</mo> <msub> <mi>P</mi> <mrow> <mn>4</mn> <mo>,</mo> <mi>min</mi> </mrow> </msub> </mrow> </semantics></math>. The power outputs of Th1 and Th3 are equal and shown superposed.</p>
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<p>Scenario 2. Total minimal costs of generated power from the solar (power unit 1) and five thermal units (power units 3, 4, 5, 6, and 7) during 24 h. The nuclear unit (power unit 2) is disabled.</p>
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<p>Scenario 3. The minimal cost powers generated by Th1–Th5 and the reserves of power versus lambda (Th1 blue, Th2 red, Th3 yellow, Th4 magenta, Th5 green, reserves light blue with *) during 24 h. The nuclear unit and the solar unit are disabled. The optimal values of <math display="inline"><semantics> <mrow> <msub> <mi>λ</mi> <mi>λ</mi> </msub> </mrow> </semantics></math> increase from <math display="inline"><semantics> <mrow> <msub> <mi>λ</mi> <mi>λ</mi> </msub> </mrow> </semantics></math> = 189.10 to <math display="inline"><semantics> <mrow> <msub> <mi>λ</mi> <mi>λ</mi> </msub> </mrow> </semantics></math> = 189.135. The power outputs of Th1 and Th3 are equal and shown superposed.</p>
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<p>Scenario 3. Minimal cost powers generated by Th1–Th5 over 24 h. The nuclear unit is disabled. The solar unit is disabled. The thermal unit Th1 operates at <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>P</mi> <mrow> <mn>1</mn> <mo>,</mo> <mi>max</mi> </mrow> </msub> </mrow> </semantics></math>, Th3 at <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mn>3</mn> </msub> <mo>=</mo> <msub> <mi>P</mi> <mrow> <mn>3</mn> <mo>,</mo> <mi>max</mi> </mrow> </msub> </mrow> </semantics></math>, and Th4 at <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mn>4</mn> </msub> <mo>=</mo> <msub> <mi>P</mi> <mrow> <mn>4</mn> <mo>,</mo> <mi>min</mi> </mrow> </msub> </mrow> </semantics></math>. The power outputs of Th1 and Th3 are equal and shown superposed.</p>
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<p>Scenario 3. Total minimal costs of generated powers from the five thermal units (power units 3, 4, 5, 6, and 7) during 24 h. The solar unit (power unit 1) and the nuclear unit (power unit 2) are disabled.</p>
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<p>Scenario 1. Powers generated by hybrid nuclear, solar and thermal system during 24 h.</p>
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<p>Optimal powers generated in the three scenarios during 24 h.</p>
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<p>Powers generated by the nuclear reactor in the three scenarios during 24 h. Scenario 1, nuclear reactor enabled; Scenarios 2 and 3, nuclear reactor disabled. (Details of <a href="#jne-06-00002-f014" class="html-fig">Figure 14</a>).</p>
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<p>Power generated by the solar unit in the three scenarios during 24 h. Scenarios 1 and 2, solar unit enabled; Scenario 3, solar unit disabled. (Details of <a href="#jne-06-00002-f014" class="html-fig">Figure 14</a>).</p>
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<p>Power generated by the five thermal units in the three scenarios during 24 h. Scenarios 1, 2, and 3, thermal units enabled. (Details of <a href="#jne-06-00002-f014" class="html-fig">Figure 14</a>).</p>
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20 pages, 2386 KiB  
Article
Capacity Planning Method for Wind–Solar–Thermal-Storage Bundled HVDC Sending System Considering Transient Overvoltage Constraints
by Changling Li, Zhongzheng Li, Shibo Jing, Jiawen Sun, Zhiyong Yu and Gaohang Zhang
Processes 2025, 13(1), 19; https://doi.org/10.3390/pr13010019 - 25 Dec 2024
Viewed by 371
Abstract
High-voltage direct current (HVDC) sending systems have been the main means of renewable power cross-regional sharing and consumption. However, the transient overvoltage problems restrict the transmission capacity and renewable energy accommodation. The allocation of wind–solar–thermal storage capacity has become an important factor affecting [...] Read more.
High-voltage direct current (HVDC) sending systems have been the main means of renewable power cross-regional sharing and consumption. However, the transient overvoltage problems restrict the transmission capacity and renewable energy accommodation. The allocation of wind–solar–thermal storage capacity has become an important factor affecting the safety and stability of renewable energy sending. A capacity planning method is proposed for a wind–solar–thermal-storage bundled HVDC sending system considering transient overvoltage constraints. Firstly, based on quantile regression analysis and Gaussian mixture modeling, the typical scenario generation method is proposed to depict the uncertainty of renewable energy. Then, the transient overvoltage characteristics of the integrated HVDC transmission system are analyzed. The relationship between the power output of power sources and the system short-circuit capacity is derived. Meanwhile, the calculation method of the minimum short-circuit capacity of the HVDC system is proposed. Based on the calculation method, the transient overvoltage constraint corresponding to the voltage support strength is constructed. Finally, considering the transient overvoltage constraints, the capacity planning model of the wind–solar–thermal storage is established. The upper-layer model optimizes the configuration scheme of the wind–solar–thermal storage to minimize the total system cost. The lower-layer model optimizes the operation scheduling under the typical operation scenarios of renewable energy and delivery load. The optimal capacity planning scheme for the wind–solar–thermal storage is determined through the coordinated optimization of the two-layer model. The feasibility and effectiveness of the proposed method are verified through a case analysis. The results show that the proposed planning method can effectively maintain a higher short-circuit ratio and improve the voltage support strength under the premise of completing the sending plan. Full article
(This article belongs to the Section Energy Systems)
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<p>Schematic diagram of wind–solar–thermal-storage HVDC sending system.</p>
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<p>Equivalent schematic diagram of the wind farm.</p>
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<p>The framework of the planning method for wind–solar–thermal-storage bundled HVDC sending system.</p>
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<p>Typical curves of the sending load demand.</p>
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<p>Typical scenarios of wind power output.</p>
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<p>Typical scenarios of solar power output.</p>
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<p>Transient overvoltage case under DC system faults.</p>
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<p>Operation results of Scheme 1 planning result.</p>
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<p>Operation results of Scheme 2 planning result.</p>
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<p>Transient overvoltage conditions of different schemes under DC faults.</p>
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<p>Comparison of short-circuit ratio results for different planning schemes.</p>
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24 pages, 12079 KiB  
Article
Estimation of the Effect of Oblique Positioned Obstacle Placement on Thermal Performance of a Horizontal Mantle Hot Water Tank with Machine Learning
by Aslı Durmuşoğlu, Buket Turgut, Yusuf Tekin and Burak Turgut
Appl. Sci. 2025, 15(1), 48; https://doi.org/10.3390/app15010048 - 25 Dec 2024
Viewed by 326
Abstract
Due to the growing popularity of vacuum tube solar collectors and their more esthetically pleasing look, horizontal hot water tanks are increasingly being used in solar hot water systems. In order to improve the thermal performance of a horizontal mantled hot water tank, [...] Read more.
Due to the growing popularity of vacuum tube solar collectors and their more esthetically pleasing look, horizontal hot water tanks are increasingly being used in solar hot water systems. In order to improve the thermal performance of a horizontal mantled hot water tank, this work numerically examines the impact of positioning inclination barriers parallel or coincident to one another at varying angles. The main input provided the velocity V = 0.036, 0.073, 0.11, and 0.147 m/s, and analysis were performed for each speed. The study concluded that V = 0.073 m/s was the ideal mains input velocity for each scenario and that raising the speed typically resulted in a lower mains outlet temperature. According to the study’s findings, the tank design with the first obstacle 150 mm away and the two obstacles 100 mm apart achieves the best efficiency. The residential water temperature in this model is 312 K, while the storage water temperature is 309.5 K. In this study, a feed-forward artificial neural network (ANN) model based predictor was designed to estimate the mantle outlet and main outlet temperatures and the temperature of the stored water. Analyses were performed for different network inlet velocities and obstacle combinations, and ANN showed superior performance in estimating temperature parameters. Full article
(This article belongs to the Special Issue Multiscale Heat and Mass Transfer and Artificial Intelligence)
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<p>Schematic of the horizontal mantled hot water tank.</p>
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<p>(<b>a</b>) The model of a horizontal hot water tank for a = 60° and m = 50 mm, l = 200 mm, (<b>b</b>) Grid structure of a horizontal hot water tank.</p>
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<p>(<b>a</b>) The experimental system of horizontal hot water tank, (<b>b</b>) Schematic view of the experimental system.</p>
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<p>Experimental and numerical analysis results for the mantle outlet and main outlet temperature for the obstacle placed at a = 60°, m = 100 mm, l = 100 mm tank.</p>
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<p>Temperature distributions for normal (not obstacle) V<sub>mantle</sub> = 0.147 m/s (<b>a</b>) V<sub>main</sub> = 0.036 m/s, (<b>b</b>) V<sub>main</sub> = 0.073 m/s, (<b>c</b>) V<sub>main</sub> = 0.11 m/s, (<b>d</b>) V<sub>main</sub> = 0.147 m/s.</p>
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<p>Temperature distributions for a = 60°, m = 50 mm, l = 100 mm, V<sub>mantle</sub> = 0.147 m/s, (<b>a</b>) V<sub>main</sub> = 0.036 m/s, (<b>b</b>) V<sub>main</sub> = 0.073 m/s, (<b>c</b>) V<sub>main</sub> = 0.11 m/s, (<b>d</b>) V<sub>main</sub> = 0.147 m/s.</p>
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<p>Temperature distributions for a = 60°, m = 50 mm, l = 200 mm, V<sub>mantle</sub> = 0.147 m/s, (<b>a</b>) V<sub>main</sub> = 0.036 m/s, (<b>b</b>) V<sub>main</sub> = 0.073 m/s, (<b>c</b>) V<sub>main</sub> = 0.11 m/s, (<b>d</b>) V<sub>main</sub> = 0.147 m/s.</p>
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<p>Temperature distributions for a = 60°, m = 50 mm, l = 200 mm, V<sub>mantle</sub> = 0.147 m/s, (<b>a</b>) V<sub>main</sub> = 0.036 m/s, (<b>b</b>) V<sub>main</sub> = 0.073 m/s, (<b>c</b>) V<sub>main</sub> = 0.11 m/s, (<b>d</b>) V<sub>main</sub> = 0.147 m/s.</p>
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<p>Temperature distributions for a = 60°, m = 100 mm, l = 100 mm, V<sub>mantle</sub> = 0.147 m/s, (<b>a</b>) V<sub>main</sub> = 0.036 m/s, (<b>b</b>) V<sub>main</sub> = 0.073 m/s, (<b>c</b>) V<sub>main</sub> = 0.11 m/s, (<b>d</b>) V<sub>main</sub> = 0.147 m/s.</p>
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<p>Temperature distributions for a = 60°, m = 100 mm, l = 200 mm, V<sub>mantle</sub> = 0.147 m/s, (<b>a</b>) V<sub>main</sub> = 0.036 m/s, (<b>b</b>) V<sub>main</sub> = 0.073 m/s, (<b>c</b>) V<sub>main</sub> = 0.11 m/s, (<b>d</b>) V<sub>main</sub> = 0.147 m/s.</p>
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<p>Temperature distributions for a = 60°, m = 150 mm, l = 100 mm, V<sub>mantle</sub> = 0.147 m/s, (<b>a</b>) V<sub>main</sub> = 0.036 m/s, (<b>b</b>) V<sub>main</sub> = 0.073 m/s, (<b>c</b>) V<sub>main</sub> = 0.11 m/s, (<b>d</b>) V<sub>main</sub> = 0.147 m/s.</p>
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<p>Temperature distributions for a = 60°, m = 150 mm, l = 200 mm, V<sub>mantle</sub> = 0.147 m/s, (<b>a</b>) V<sub>main</sub> = 0.036 m/s, (<b>b</b>) V<sub>main</sub> = 0.073 m/s, (<b>c</b>) V<sub>main</sub> = 0.11 m/s, (<b>d</b>) V<sub>main</sub> = 0.147 m/s.</p>
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<p>Change over time of the average storage temperature water for all cases.</p>
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<p>Change over time of the average storage temperature water for all cases.</p>
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<p>The value at the end of the 120 min mantle output and main output temperatures for all cases.</p>
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<p>Schematic representation of feed forward neural network structure.</p>
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<p>Prediction results for a = 60°, m = 50 mm, l = 100 mm (<b>a</b>) T<sub>main</sub>, (<b>b</b>) T<sub>mantle</sub>, (<b>c</b>) T<sub>storage</sub>.</p>
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<p>Prediction results for a = 60°, m = 100 mm, l = 100 mm (<b>a</b>) T<sub>main</sub>, (<b>b</b>) T<sub>mantle</sub>, (<b>c</b>) T<sub>storage</sub>.</p>
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<p>Prediction results for a = 60°, m = 150 mm, l = 100 mm (<b>a</b>) T<sub>main</sub>, (<b>b</b>) T<sub>mantle</sub>, (<b>c</b>) T<sub>storage</sub>.</p>
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<p>Prediction results for a = 60°, m = 50 mm, l = 200 mm (<b>a</b>) T<sub>main</sub>, (<b>b</b>) T<sub>mantle</sub>, (<b>c</b>) T<sub>storage</sub>.</p>
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<p>Prediction results for a = 60°, m = 100 mm, l = 200 mm (<b>a</b>) T<sub>main</sub>, (<b>b</b>) T<sub>mantle</sub>, (<b>c</b>) T<sub>storage</sub>.</p>
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<p>Prediction results for a = 60°, m = 150 mm, l = 200 mm (<b>a</b>) T<sub>main</sub>, (<b>b</b>) T<sub>mantle</sub>, (<b>c</b>) T<sub>storage</sub>.</p>
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32 pages, 5622 KiB  
Article
Performance Enhancement of a Building-Integrated Photovoltaic/Thermal System Coupled with an Air Source Heat Pump
by Edward Vuong, Alan S. Fung and Rakesh Kumar
Energies 2025, 18(1), 12; https://doi.org/10.3390/en18010012 - 24 Dec 2024
Viewed by 258
Abstract
This study explores the improvement of building integrated photovoltaic–thermal (BIPV/T) systems and their integration with air source heat pumps (ASHPs). The BIPV/T collector needs a method to effectively extract the heat it collects, while ASHP can boost their efficiency utilizing preheated air from [...] Read more.
This study explores the improvement of building integrated photovoltaic–thermal (BIPV/T) systems and their integration with air source heat pumps (ASHPs). The BIPV/T collector needs a method to effectively extract the heat it collects, while ASHP can boost their efficiency utilizing preheated air from the BIPV/T collectors. Combining these two systems presents a valuable opportunity to enhance their performance. This paper discusses technological improvements and integration through a comprehensive modelling analysis. Two versions of the BIPV/T systems were assessed using a modified version of EnergyPlus V8.0, a building energy simulation program. This study involved sensitivity analysis of the internal channel surface and cover emissivity parameters of the opaque BIPV/T (OBIPV/T), transparent BIPV/T (TBIPV/T), and building-integrated solar air heater collectors (BISAHs). Various arrangements of the collectors were also studied. A BIPV/T-BISAH array design was selected based on the analysis, and its integration with a net-zero energy house. The BIPV/T-BISAH coupled ASHP system decreased space heating electricity consumption by 6.5% for a net-zero house. These modest savings are mainly attributed to the passive design of the houses, which reduced heating loads during sunny hours/days. Full article
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<p>Schematics of (<b>a</b>) OBIPV/T, (<b>b</b>) TBIPV/T, and (<b>c</b>) BISAH.</p>
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<p>Schematic of working of BIPV/T with multispeed heat pump (MSHP).</p>
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<p>Heating season thermal and electrical generation of a row of TBIPV/T collectors with various internal channel emissivity values.</p>
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<p>Heating season thermal generation of each TBIPV/T collector of a row with 0.9 and 0.1 internal emissivity values.</p>
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<p>Hourly thermal generation and internal surface temperature differential of a TBIPV/T collector with 0.9 and 0.1 internal emissivity values.</p>
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<p>Heating season thermal and electrical generation of a single TBIPV/T collector with various cover emissivity values.</p>
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<p>Total convective and radiative heat loss of a TBIPV/T collector with 0.6 and 0.3 cover emissivity values.</p>
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<p>Heat flux from the PV layer to the upper surface of the air channel of a TBIPV/T collector with 0.6 and 0.3 cover emissivity values.</p>
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<p>Heating season thermal and electrical generation of a single OBIPV/T collector with various internal emissivity values.</p>
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<p>Heating season thermal and electrical generation of a single OBIPV/T collector with various cover emissivity values.</p>
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<p>Total convective and radiative heat loss of an OBIPV/T collector with 0.6 and 0.3 cover emissivity values.</p>
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<p>Heating season thermal generation of a single BISAH with various internal emissivity values.</p>
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<p>Hourly internal longwave radiation heat transfer from the lower surface to the upper surface in a BISAH with 0.9 and 0.1 internal emissivity values.</p>
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<p>Heating season thermal generation of each BISAH of a row with 0.9 and 0.1 internal emissivity values.</p>
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<p>Heating season thermal generation of a row of BISAH with various internal emissivity values.</p>
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<p>Heating season thermal generation of a single BISAH with various cover emissivity values.</p>
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<p>Hourly total convective and radiative heat loss of a BISAH with 0.9 and 0.1 cover emissivity values.</p>
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<p>Heating season thermal generation of each BISAH of a row with 0.9 and 0.1 cover emissivity values.</p>
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<p>Heating season thermal generation of a row of BISAH with various cover emissivity values.</p>
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<p>One row of (<b>a</b>) 5 OBIPV/T collectors (dark blue), (<b>b</b>) 5 OBIPV/T collectors (dark blue) with 1 BISAH (light blue), (<b>c</b>) 4 OBIPV/T collectors (dark blue) with 2 BISAH (light blue).</p>
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<p>Schematic of OBIPV/T + BISAH rows and the corresponding TBIPV/T rows (equivalent net glazing area). Solid dark blue denotes OBIPV/T collectors, light blue signifies BISAH, and dark blue grid-pattern represents TBIPV/T collectors.</p>
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<p>Array of 36 BIPV/T-BISAH collectors coupled with an MSHP. Dark blue grid-pattern denotes TBIPV/T collectors, while solid light blue signifies BISAH.</p>
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<p>Sketchup model of the NZE house.</p>
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<p>Hourly BIPV/T-BISAH array and outdoor air flowrate for 29 December.</p>
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<p>Hourly outdoor air temperature and the BIPV/T-BISAH array’s average outlet and mixed air temperatures for 29 December.</p>
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<p>Hourly BIPV/T-BISAH coupled MSHP and base case MSHP electricity consumption for 29 December.</p>
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8 pages, 1956 KiB  
Communication
Cuprous Halide Coordination Polymer for Efficient NIR-I Photothermal Effect and Photo-Thermo-Electric Conversion
by Ning-Ning Zhang, Xiang-Tong Liu, Ke Xu, Ya-Tong Liu, Lin-Xu Liu and Yong Yan
Molecules 2024, 29(24), 6034; https://doi.org/10.3390/molecules29246034 - 21 Dec 2024
Viewed by 332
Abstract
Photo-thermo-electric conversion devices represent a promising technology for converting solar energy into electrical energy. Photothermal materials, as a critical component, play a significant role in efficient conversion from solar energy into thermal energy and subsequently electrical energy, thereby directly influencing the overall system’s [...] Read more.
Photo-thermo-electric conversion devices represent a promising technology for converting solar energy into electrical energy. Photothermal materials, as a critical component, play a significant role in efficient conversion from solar energy into thermal energy and subsequently electrical energy, thereby directly influencing the overall system’s efficiency in solar energy utilization. However, the application of single-component photothermal materials in photo-thermo-electric conversion systems remains limited. The exploration of novel photothermal materials with broad-spectrum absorption, a high photothermal conversion efficiency (PCE), and a robust output power density is highly desired. In this study, we investigated a black cuprous halide compound, [Cu2Cl2PA]n (1, PA = phenazine), which exhibits broad-spectrum absorption extending into the near-infrared (NIR) region. Compound 1 demonstrated a high NIR-I PCE of 50% under irradiation with an 808 nm laser, attributed to the metal-to-ligand charge transfer (MLCT) from the Cu(I) to the PA ligands and the strong intermolecular π–π interactions among the PA ligands. Furthermore, the photo-thermo-electric conversion device constructed using compound 1 achieved a notable output voltage of 261 mV and an output power density of 0.92 W/m2 under the 1 Sun (1000 W/m2) xenon lamp. Full article
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Graphical abstract

Graphical abstract
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<p>(<b>a</b>) The 2D layer structure of compound <b>1</b> as viewed along the <span class="html-italic">b</span> axis. (<b>b</b>) A selected π–π stacking fragment within compound <b>1</b>, along with its calculated gradient isosurfaces (s = 0.5 a.u.). The surfaces are colored using a blue–green–red (BGR) scale based on the values of sign (λ<sub>2</sub>)<span class="html-italic">ρ</span>, which range from −0.04 to 0.02 a.u. In this scale, blue indicates strong attractive interactions, green represents moderate attractive interactions, and red signifies strong non-bonded overlaps.</p>
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<p>(<b>a</b>) Solid−state absorption spectra of <b>PA</b> and compound <b>1</b>. (<b>b</b>) TDOS and PDOS of <b>1</b>, with the Fermi level (<span class="html-italic">E</span><sub>F</sub>) set to zero as a reference.</p>
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<p>(<b>a</b>) Infrared images of a crystalline pellet of <b>1</b> under varying irradiation power densities. (<b>b</b>) Temperature variations in <b>1</b> under 808 nm laser irradiation at different power densities. (<b>c</b>) Cycling temperature profile of <b>1</b> under 808 nm laser irradiation with a constant power density of 0.75 W/cm<sup>2</sup>.</p>
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<p>(<b>a</b>) Schematic diagram of photo−thermo−electric conversion device. (<b>b</b>) The output power density of different photo−thermo−electric conversion systems when loading external resistances under irradiation of 1 Sun and 2 Suns. Open−circuit voltages (<b>c</b>–<b>e</b>) and currents (<b>f</b>–<b>h</b>) of different commercial thermo−electric generators after loading with compound <b>1</b> under irradiation of 1 Sun and 2 Suns, respectively.</p>
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14 pages, 2267 KiB  
Article
Pressure-Induced Assembly of Organic Phase-Change Materials Hybridized with Expanded Graphite and Carbon Nanotubes for Direct Solar Thermal Harvesting and Thermoelectric Conversion
by Jie Ji, Yizhe Liu, Xiaoxiang Li, Yangzhe Xu, Ting Hu, Zhengzheng Li, Peng Tao and Tao Deng
Nanomaterials 2024, 14(24), 2047; https://doi.org/10.3390/nano14242047 - 21 Dec 2024
Viewed by 453
Abstract
Direct harvesting of abundant solar thermal energy within organic phase-change materials (PCMs) has emerged as a promising way to overcome the intermittency of renewable solar energy and pursue high-efficiency heating-related applications. Organic PCMs, however, generally suffer from several common shortcomings including melting-induced leakage, [...] Read more.
Direct harvesting of abundant solar thermal energy within organic phase-change materials (PCMs) has emerged as a promising way to overcome the intermittency of renewable solar energy and pursue high-efficiency heating-related applications. Organic PCMs, however, generally suffer from several common shortcomings including melting-induced leakage, poor solar absorption, and low thermal conductivity. Compounding organic PCMs with single-component carbon materials faces the difficulty in achieving optimized comprehensive performance enhancement. Herein, this work reports the employment of hybrid expanded graphite (EG) and carbon nanotubes (CNTs) to simultaneously realize leakage-proofness, high solar absorptance, high thermal conductivity, and large latent heat storage capacity. The PCM composites were prepared by directly mixing commercial high-temperature paraffin (HPA) powders, EG, and CNTs, followed by subsequent mechanical compression molding. The HPA-EG composites loaded with 20 wt% of EG could effectively suppress melting-induced leakage. After further compounding with 1 wt% of CNTs, the form-stable HPA-EG20-CNT1 composites achieved an axial and in-plane thermal conductivity of 4.15 W/m K and 18.22 W/m K, and a melting enthalpy of 165.4 J/g, respectively. Through increasing the loading of CNTs to 10 wt% in the top thin layer, we further prepared double-layer HPA-EG-CNT composites, which have a high surface solar absorptance of 92.9% for the direct conversion of concentrated solar illumination into storable latent heat. The charged composites could be combined with a thermoelectric generator to release the stored latent heat and generate electricity, which could power up small electric devices such as light-emitting diodes. This work demonstrates the potential for employing hybrid fillers to optimize the thermophysical properties and solar thermal harvesting performances of organic PCMs. Full article
(This article belongs to the Special Issue Nano-Based Advanced Thermoelectric Design)
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Figure 1
<p>Pressure-induced assembly of organic PCM hybridized with EG and CNT for high-performance direct solar thermal energy harvesting and thermoelectric conversion.</p>
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<p>(<b>a</b>) Schematic showing the preparation process of PCM composites through pressure-induced assembly. (<b>b</b>) Schematic structure of PCM composites. (<b>c</b>,<b>d</b>) SEM images of EG at low and high magnification. (<b>e</b>) SEM image showing adsorption of 20 wt% of HPA within EG after heating treatment. (<b>f</b>,<b>g</b>) SEM image of HPA-EG20-CNT1 composites at low and high magnification. (<b>h</b>) SEM image showing agglomeration of CNTs within the HPA-EG20-CNT2 composites.</p>
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<p>(<b>a</b>) Photographs comparing anti-leakage performance of HPA and HPA-EG composites with different loadings of EG. (<b>b</b>) Mass retention rate of HPA-EG composites during leakage tests. (<b>c</b>) Photographs showing leakage-proofness of HPA-EG20-CNT composites. (<b>d</b>) Axial and in-plane thermal conductivity of HPA-EG and HPA-EG-CNT composites. (<b>e</b>) Schematic showing enhancement of heat conduction of HPA-EG composites through further compounding with CNTs.</p>
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<p>(<b>a</b>) Endothermic DSC curves of HPA, HPA-EG20, and HPA-EG20-CNT composites. (<b>b</b>) Peak, onset, and offset melting temperature of HPA, HPA-EG20, and HPA-EG20-CNT composites. (<b>c</b>) Melting enthalpy of HPA, HPA-EG20, and HPA-EG20-CNT composites. (<b>d</b>) DSC curves of HPA-EG20-CNT1 composites before and after cycled melting/solidification.</p>
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<p>(<b>a</b>) Photograph of HPA-EG20 composites showing gray surfaces. (<b>b</b>) Photograph of double-layer structure HPA-EG20-CNT1-D composites. (<b>c</b>) Schematic structure of HPA-EG20-CNT1-D composites. (<b>d</b>) Optical absorption spectra of HPA-EG and HPA-EG-CNT composites. (<b>e</b>) Schematics comparing solar absorption by HPA, HPA-EG20, and HPA-EG20-CNT1-D composites.</p>
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<p>(<b>a</b>) Schematic of experimental setup for evaluating direct solar thermal harvesting performance. (<b>b</b>) Time-sequential infrared images showing charging process of HPA, HPA-EG20, and HPA-EG20-CNT composites. (<b>c</b>) Temperature evolution profiles during solar thermal charging and natural cooling discharging processes.</p>
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<p>(<b>a</b>) Schematic experimental setup for releasing solar thermal energy stored within HPA-EG20-CNT1-D composites and thermoelectric conversion. (<b>b</b>) Temperature evolution profile and corresponding output voltage during discharging. (<b>c</b>) Time-sequential photographs showing lighting up an LED bulb with generated electrical output.</p>
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25 pages, 6470 KiB  
Article
Thermal Energy Storage and Recovery in Fractured Granite Reservoirs: Numerical Modeling and Efficiency Analysis
by Nima Gholizadeh Doonechaly, Théo Halter, Alexis Shakas, Mahmoud Hefny, Maren Brehme, Marian Hertrich and Domenico Giardini
Geosciences 2024, 14(12), 357; https://doi.org/10.3390/geosciences14120357 - 20 Dec 2024
Viewed by 338
Abstract
Although Aquifer Thermal Energy Storage (ATES) systems are widely researched, Fractured Thermal Energy Storage (FTES) systems are comparatively underexplored. This study presents a detailed numerical model of a fractured granitic reservoir at the Bedretto underground laboratory in Switzerland, developed using COMSOL Multiphysics. Energy [...] Read more.
Although Aquifer Thermal Energy Storage (ATES) systems are widely researched, Fractured Thermal Energy Storage (FTES) systems are comparatively underexplored. This study presents a detailed numerical model of a fractured granitic reservoir at the Bedretto underground laboratory in Switzerland, developed using COMSOL Multiphysics. Energy efficiency was evaluated across different flow rates and well configurations, including single-well and doublet systems, as well as for two different temperatures, namely 60 °C and 120 °C. The doublet configuration at an injection temperature of 60 °C with a flow rate of 2 kg/s demonstrated the highest energy efficiency among the cases studied. Potential applications for the stored heat are discussed, with scenarios including district heating for the nearby village and greenhouse heating. The results show that although FTES is associated with unique challenges, it has significant potential as a reliable thermal energy storage method, particularly in regions without suitable aquifers. It can also be considered as a cost-effective and competitive approach for climate mitigation (assuming the system is solely powered by solar-PV). This study provides insights into the viability and optimization of FTES systems and highlights the role of fracture/fault properties in enhancing energy efficiency. Full article
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Figure 1
<p>Topographic map of the Bedretto valley including the Bedretto tunnel as well as the Furka railway tunnel (after [<a href="#B32-geosciences-14-00357" class="html-bibr">32</a>]) [<a href="#B36-geosciences-14-00357" class="html-bibr">36</a>,<a href="#B37-geosciences-14-00357" class="html-bibr">37</a>]. Coordinates correspond to the Swiss Grid (CH1903+).</p>
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<p>The geological cross-section of the Bedretto tunnel. The first unit on the southeast side of the tunnel is made of the gneisses and schists of the Tremola series, followed by the gneisses and schists of the Prato series to the northwest and by the Rotondo granite (after [<a href="#B31-geosciences-14-00357" class="html-bibr">31</a>,<a href="#B32-geosciences-14-00357" class="html-bibr">32</a>,<a href="#B39-geosciences-14-00357" class="html-bibr">39</a>,<a href="#B40-geosciences-14-00357" class="html-bibr">40</a>]).</p>
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<p>Three-dimensional visualization of the reservoir model showing the spatial configuration of faults/fractures and wellbores. The colored planes represent individual fault/fracture intersecting the wellbores at specific measured intervals/depths (at one-meter resolution), as indicated in the legend. The blue and red lines illustrate the trajectories of the two wells, ST1 and ST2, respectively.</p>
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<p>Influence of mesh size (<b>left</b>) and relative tolerance of the numerical solver (<b>right</b>) on the stability of temperature values for heat storage modeling. The temperature at the main well was evaluated at the end of a cycle for a single-well configuration with a flow rate of 2 kg/s and an injection temperature of 120 °C. The green diamond markers in both figures show the selected optimized configuration. The x-axes in both figures are presented in logarithmic scale.</p>
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<p>Three-dimensional temperature distribution profiles over the fault/fracture surfaces after 25 annual storage cycles of thermal energy storage modeling under different configurations. The presented simulation results compare single-well (<b>right</b>) and doublet-well (<b>left</b>) systems, with injection temperatures of 60 °C (<b>top</b>) and 120 °C (<b>bottom</b>) at a flow rate of 2 kg/s.</p>
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<p>Cyclic produced fluid temperature from the peripheral interval during the injection period (i.e., 91 days) over 25 annual cycles at the maximum flow rate of 2 kg/s: doublet (<b>left</b>) and single-well (<b>right</b>) setups at 60 °C (<b>top</b>) and 120 °C (<b>bottom</b>) injection temperature cases.</p>
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<p>Cyclic produced fluid temperature profiles from the main well during the winter production period over 25 annual cycles for different well setups and injection temperatures at the maximum flow rate of 2 kg/s: doublet (<b>left</b>) and single-well (<b>right</b>) setups at 60 °C (<b>top</b>) and 120 °C (<b>bottom</b>) injection temperature cases.</p>
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<p>Energy efficiency profiles over 25 annual cycles for different well setups, injection temperatures, and flow rates. The cases include doublet (<b>left</b>) and single-well (<b>right</b>) setups with 60 °C (<b>top</b>) and 120 °C (<b>bottom</b>) injection temperatures, each modeled at flow rates of 1.0, 1.5, and 2.0 kg/s.</p>
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<p>Cyclic delivered temperature and temperature loss profiles over 25 annual cycles for two delivery scenarios: Bedretto Village assuming 3600 m of pipe length (<b>left</b>) and the hypothetical greenhouse assuming 2200 m of pipe length (<b>right</b>). The shaded areas represent the temperature delivery and loss range, and the dashed lines indicate the mean corresponding values. A temperature of −4 °C is assumed for the outside air temperature [<a href="#B59-geosciences-14-00357" class="html-bibr">59</a>], and the temperature of 16.63 °C is assumed as the average winter temperature for inside the tunnel obtained from the fiber optic data.</p>
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<p>Energy efficiency comparison for single-well and doublet systems at 60 °C and 120 °C with variations in initial transmissivity (Base Case, −10%, and +10%) at a flow rate of 2 kg/s.</p>
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