期刊
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
卷 42, 期 43, 页码 26789-26803出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijhydene.2017.08.186
关键词
Concentrated photovoltaic; Optimization; Micro genetic algorithm; CPV; Hydrogen storage; Electrolyser
资金
- International Research Scholarship of Mechanical Engineering Department, National University of Singapore
- King Abdullah University of Science and Technology, Saudi Arabia
Despite highest energy potential, solar energy is only available during diurnal period with varying intensity. Therefore, owing to solar intermittency, solar energy systems need to operate in standalone configuration for steady power supply which requires reliable and sustainable energy storage. Hydrogen production has proved to be the most reliable and sustainable energy storage option for medium and long term operation. However, at the first priority, solar energy must be captured with high efficiency, in order to reduce the overall size of the system and energy storage. Multi-junction solar cells (MJCs) provide highest energy efficiency among all of the photovoltaic technologies and the concentrated photovoltaic (CPV) system concept makes their use cost effective. However, literature is lacking the performance model and optimization strategy for standalone operation of the CPV-hydrogen system. In addition, there is no commercial tool available that can analyze CPV performance, utilizing multi-junction solar cell. This paper proposes the performance model for the CPV-hydrogen systems and the multi-objective optimization strategy for its standalone operation and techno-economic analysis, using micro genetic algorithm (micro-GA). The electrolytic hydrogen production with compression storage and fuel cell, is used as energy storage system. The CPV model is verified for the experimental data of InGaP/InGaAs/Ge triple junction solar cell. An optimal CPV system design is provided for uninterrupted power supply, even under seasonal weather variations. Such approach can be easily integrated with commercial tools and the presented performance data can be used for the design of individual components of the system. (C) 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
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