The Experts below are selected from a list of 136698 Experts worldwide ranked by ideXlab platform
Yimin Xuan - One of the best experts on this subject based on the ideXlab platform.
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a novel Optimal Design Method for concentration spectrum splitting photovoltaic thermoelectric hybrid system
Energy, 2018Co-Authors: Ershuai Yin, Yimin XuanAbstract:Abstract In this paper, a novel Optimal Design Method for the concentration spectrum splitting photovoltaic-thermoelectric hybrid system is proposed. The newly provided Optimal Design Method tries to optimize the solar energy distribution of the concentration spectrum splitting photovoltaic-thermoelectric hybrid system while maintaining the Optimal operating states of the subsystems, which has never been mentioned before. For the Optimal Design, the optimum operating temperature of the hybrid system is firstly determined. Then, a series of cutoff wavelengths of the spectral splitter is given, and the efficiencies of the coupling systems with all different cutoff wavelengths are calculated. The highest efficiency and the Optimal cutoff wavelength will be obtained by comparing the performances of the concentration spectrum splitting photovoltaic-thermoelectric hybrid systems with different cutoff wavelengths. The Optimal thermoelectric thermal resistance and structure factor related to the optimum operating temperature of the thermoelectric subsystems are finally acquired. The effects of the thermoelectric figure of merit and the convective heat transfer coefficient of the cooling system on the Optimal Design are also discussed. The results show that the Optimal temperature distribution of the thermoelectric subsystem can be obtained by regulating the thermoelectric structure factor. Although the solar energy transferred to the thermoelectric subsystem decreases, as the cutoff wavelength increases, the thermoelectric efficiency can be increased through optimization. The Optimal cutoff wavelength of the spectral splitter decreases with the increase of the thermoelectric figure of merit, and a thermoelectric module with smaller thermal resistance should be used to maintain its optimum operating temperature.
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Optimal Design Method for concentrating photovoltaic thermoelectric hybrid system
Applied Energy, 2018Co-Authors: Qiang Li, Yimin XuanAbstract:Utilizing the dissipated thermal energy by photovoltaic cells working as the heat source of thermoelectric module to generate extra electricity is an optional way to further improve the photoelectric conversion efficiency of concentrating photovoltaic system. However, there exists a confrontation between the efficiency temperature characteristics of the photovoltaic cell and the thermoelectric module. The photovoltaic efficiency decreases with the rise of its temperature while the thermoelectric efficiency increases with its temperature difference augmenting, which makes the Design of the concentrating photovoltaic-thermoelectric hybrid system crucial. In this paper, the selection principle of the coupling devices and a novel Optimal Design Method for the concentrating photovoltaic-thermoelectric coupling system are proposed. The minimum figure of merit of the thermoelectric generator that enables the efficiency of the concentrating photovoltaic-thermoelectric hybrid system to be larger than that of the concentrating photovoltaic system is calculated and regarded as the reference of evaluating the feasibility and selecting the coupling devices. For the Optimal Designs, the temperature distribution where the concentrating photovoltaic-thermoelectric hybrid system has the highest electric efficiency is firstly calculated. Then, the optimum thermal resistance of the thermoelectric generator, which keeps the photovoltaic-thermoelectric hybrid system operating at the Optimal temperature distribution, is calculated. Once the thermoelectric thermal resistance is obtained, the Optimal structure of the thermoelectric generator can be determined. The effects of reference efficiency, the efficiency temperature coefficient of the photovoltaic cell, the figure of merit of the thermoelectric module and the convective heat transfer coefficient of the cooling system on Optimal Designs of the concentrating photovoltaic-thermoelectric hybrid system are also discussed.
Qiang Li - One of the best experts on this subject based on the ideXlab platform.
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Optimal Design Method for concentrating photovoltaic thermoelectric hybrid system
Applied Energy, 2018Co-Authors: Qiang Li, Yimin XuanAbstract:Utilizing the dissipated thermal energy by photovoltaic cells working as the heat source of thermoelectric module to generate extra electricity is an optional way to further improve the photoelectric conversion efficiency of concentrating photovoltaic system. However, there exists a confrontation between the efficiency temperature characteristics of the photovoltaic cell and the thermoelectric module. The photovoltaic efficiency decreases with the rise of its temperature while the thermoelectric efficiency increases with its temperature difference augmenting, which makes the Design of the concentrating photovoltaic-thermoelectric hybrid system crucial. In this paper, the selection principle of the coupling devices and a novel Optimal Design Method for the concentrating photovoltaic-thermoelectric coupling system are proposed. The minimum figure of merit of the thermoelectric generator that enables the efficiency of the concentrating photovoltaic-thermoelectric hybrid system to be larger than that of the concentrating photovoltaic system is calculated and regarded as the reference of evaluating the feasibility and selecting the coupling devices. For the Optimal Designs, the temperature distribution where the concentrating photovoltaic-thermoelectric hybrid system has the highest electric efficiency is firstly calculated. Then, the optimum thermal resistance of the thermoelectric generator, which keeps the photovoltaic-thermoelectric hybrid system operating at the Optimal temperature distribution, is calculated. Once the thermoelectric thermal resistance is obtained, the Optimal structure of the thermoelectric generator can be determined. The effects of reference efficiency, the efficiency temperature coefficient of the photovoltaic cell, the figure of merit of the thermoelectric module and the convective heat transfer coefficient of the cooling system on Optimal Designs of the concentrating photovoltaic-thermoelectric hybrid system are also discussed.
Yantong Li - One of the best experts on this subject based on the ideXlab platform.
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a multi objective Optimal Design Method for thermal energy storage systems with pcm a case study for outdoor swimming pool heating application
Journal of energy storage, 2020Co-Authors: Yantong Li, Zhixiong Ding, Mohammad Shakerin, Nan ZhangAbstract:Abstract Traditional Design Methods for thermal energy storage systems (TES) with phase change material (PCM) are mostly based on worst-case scenario, which causes too large size of main components. Current Optimal Design Methods for these systems mainly focus on single optimization objective, which only satisfies the unilateral requirement. A multi-objective Optimal Design Method for these systems is urgently needed, and therefore this paper remedies this knowledge gap. The response surface Methodology is adopted to develop the surrogated models of the optimization objectives to improve the computational efficiency. Then, the non-dominated sorting genetic algorithm II is used to perform the double-objective and triple-objective optimization for acquiring the Pareto Optimal solutions. Finally, the final decision-making Methods that includes LINMAP and TOPSIS are adopted to identify the final Optimal solutions. A case study of optimizing the Design for an outdoor swimming pool (OSP) heating system with PCM storage tank, is conducted to illustrate the proposed approach. Eight final Optimal solutions were identified, and the sp of the system in these solutions was 1.05, 1.24, 1.04, 1.22, 1.06, 1.06, 1.07, and 0.88 years, respectively. Results indicate that the proposed approach is effective to conduct the multi-objective optimization for the OSP heating systems and guide the Design optimization for the TES systems with PCM.
Borui Cui - One of the best experts on this subject based on the ideXlab platform.
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model based Optimal Design of active cool thermal energy storage for maximal life cycle cost saving from demand management in commercial buildings
Applied Energy, 2017Co-Authors: Fu Xiao, Borui Cui, Diance Gao, Shengwei WangAbstract:This paper provides a Method to evaluate the cost-saving potential of active cool thermal energy storage (CTES) integrated with HVAC system for demand management in commercial building. Active storage is capable of shifting peak demand for peak load management (PLM) as well as providing longer duration and larger capacity for demand response (DR). In this research, a model-based Optimal Design Method using genetic algorithm is developed to optimize the capacity of active CTES for maximizing the life-cycle cost saving including capital cost associated with storage capacity as well as incentives from both fast DR and PLM. In the Method, the active CTES operates under a fast DR control strategy during DR events and under the storage-priority operation mode to shift peak demand during normal days. The Optimal storage capacities, maximum annual net cost saving and corresponding power reduction set-points during DR events are obtained by using the proposed Optimal Design Method. This research provides guidance in comprehensive evaluation of the cost-saving potential of active CTES integrated with HVAC system for building demand management including both fast DR and PLM.
Kazuhiko Komamura - One of the best experts on this subject based on the ideXlab platform.
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Optimal Design Method for building energy systems using genetic algorithms
Building and Environment, 2009Co-Authors: Ryozo Ooka, Kazuhiko KomamuraAbstract:Abstract In this paper, a new Optimal Design Method for building energy systems is proposed. This Method provides the most efficient energy system, best combination of equipment capacity and best operational planning for cooling, heating, and power simultaneously with respect to certain criteria such as energy consumption, CO 2 emission, etc. Specifically for this paper, the authors apply this Method to a sample building as a case study. The “Genetic Algorithms (GA)” optimization Method, which can resolve nonlinear optimization problems, is adopted for this optimization analysis. Also its applicability is analyzed in a case study. In order to validate the accuracy of this Method, the correct optimum solution based on comprehensive inquiries is also calculated. A comparison of the GA solution with the correct solution demonstrates fairly good agreement. The results show that the proposed Method is sufficiently capable of determining the Optimal Design and has the potential to be applied to very complex energy systems with appropriate modifications.
