4.7 Article

A green hydrogen energy storage concept based on parabolic trough collector and proton exchange membrane electrolyzer/fuel cell: Thermodynamic and exergoeconomic analyses with multi-objective optimization

期刊

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
卷 47, 期 62, 页码 26468-26489

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijhydene.2022.03.021

关键词

Hydrogen storage; PEM electrolyzer; fuel cell; Parabolic trough collector; Thermodynamic and; exergoeconomic analyses; Grey wolf multi-objective

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The need for utility-scale energy storage technologies is growing globally, with hydrogen storage emerging as a powerful alternative due to its environmental benefits and ability to store large amounts of energy. This research aims to introduce a novel configuration of green hydrogen production for power generation during peak demand periods, optimizing for the lowest cost rate and maximum exergy efficiency by combining neural network and grey wolf optimization algorithms. DowthermTM A synthetic oil is identified as the best working fluid for the proposed system, which can generate significant power output during off-peak, mid-peak, and peak demand periods.
With the continuous penetration of renewable energy plants into energy markets and their surplus power generation during off-peak periods, the need for utility-scale energy storage technologies is globally prioritized. Among the existing large-scale energy storage technologies, hydrogen storage has appeared as a powerful alternative due to its environmental benefits and the ability to store a large amount of energy for several hours to months. The major objective of the proposed research is to introduce a novel configuration of green hydrogen production for power generation during peak demand periods. In this regard, an innovative hybridization of a solar unit based on a parabolic trough collector with a protonexchange membrane electrolyzer and a fuel cell is introduced and analyzed from the thermodynamic and exergoeconomic perspectives. Moreover, a sensitivity analysis and a multi-objective optimization based on the combination of neural network and grey wolf optimization algorithms are conducted to select the best working fluid of the solar unit and ideal operating conditions according to the minimum cost rate and the maximum exergy efficiency. The results indicate that DowthermTM A synthetic oil is the best working fluid, and the proposed system can generate 9,14.9, and 20.1 MW of power during off-, mid-, and

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