4.6 Article

Optimal structure design of a PV/FC HRES using amended Water Strider Algorithm

期刊

ENERGY REPORTS
卷 7, 期 -, 页码 2057-2067

出版社

ELSEVIER
DOI: 10.1016/j.egyr.2021.04.016

关键词

Hybrid renewable energy system; Photovoltaic; Fuel cell; Overall net present value; Loss of power supply probability; Amended Water Strider Algorithm

资金

  1. Project of Technology Innovation and Application Demonstration of Chongqing, China [cstc2018jscx-msybX0339]
  2. Science and Technology Research Program of Chongqing Municipal Education Commission, China [KJQN201800822, KJQN201800816, KJZD-K201800801, KJZD-M201900802]

向作者/读者索取更多资源

A techno-economic study on an off-grid combined renewable energy system (HRES) has been proposed, utilizing the Amended Water Strider Algorithm (AWSA) to optimize the estimation of various components for cost reduction. The study considers loss of power supply probability (LPSP) and conducts sensitivity analysis and comparison with other algorithms to demonstrate the effectiveness of the proposed method.
A techno-economic study has been proposed for an off-grid combined renewable energy system (HRES) by photovoltaic (PV) and fuel cell (FC) systems. The proposed HRES has been studied to provide electricity for a remote area in Jiaju Tibetan Village, Danba, Sichuan Province China The main idea is formulated according to the Total Annual Cost (TAC). The study uses a new improved metaheuristic, called Amended Water Strider Algorithm (AWSA) to optimal estimation of the photovoltaic panels' number, electrolyzer, fuel cells, and hydrogen storage tanks to get the minimum value of the overall net present value (ONPV). For increasing the system efficiency, the loss of power supply probability (LPSP) has been considered. Sensitivity analysis is used on the changing of the proposed HRES according to Levelized cost of energy (LCOE). Also, a comparison of the algorithm with several techniques from the literature is performed to illustrate its effectiveness. The results showed that the proposed method has further proper results than the other algorithms. (C) 2021 The Author(s). Published by Elsevier Ltd.

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