文献类型：期刊文献

英文题名：Capacity configuration optimization of a hybrid renewable energy system with hydrogen storage

作者：Li, Guoliang[3,4];Yuan, Benfeng[1,4];Ge, Min[1,2,4];Xiao, Guoping[1,2,4];Li, Tao[3];Wang, Jian-Qiang[1,2,4]

机构：[1]Chinese Acad Sci, Dalian Natl Lab Clean Energy, Dalian, Peoples R China;[2]Univ Chinese Acad Sci, Dalian Natl Lab Clean Energy, Beijing, Peoples R China;[3]East China Univ Sci & Technol, Engn Res Ctr Large Scale Reactor Engn & Technol, State Key Lab Chem Engn, Minist Educ, Shanghai, Peoples R China;[4]Chinese Acad Sci, Shanghai Inst Appl Phys, Key Lab Interfacial Phys & Technol, Shanghai 201800, Peoples R China

年份：2022

卷号：19

期号：14

起止页码：1583

外文期刊名：INTERNATIONAL JOURNAL OF GREEN ENERGY

收录：;EI(收录号：20220311482570);WOS:【SCI-EXPANDED(收录号:WOS:000744326600001)】；

基金：This work was partly supported by the Transformational Technologies for Clean Energy and Demonstration Strategic Priority Research Program of the Chinese Academy of Sciences (XDA2100000), the Youth Innovation Promotion Association of the Chinese Academy of Sciences (2018298).

语种：英文

外文关键词：Renewable energy; capacity allocation optimization; Reversible Solid Oxide Cell; energy storage system; particle swarm optimization algorithm

摘要：Different from low-temperature electrolysis systems, the large power consumption for the balance of plant (BOP) of the reversible solid oxide cell (RSOC) system for a high-temperature operating condition needs to be considered in the determination of the capacity configuration of the hybrid renewable energy (HRE) system. To address this issue, a power-based model of the RSOC system is developed and the corresponding capacity configuration strategy especially for the HRE system is also proposed in this paper. An optimization program of a hybrid energy system model composed of the wind turbines (WT), photovoltaic panels (PV), reversible solid oxide cell (RSOC) system, hydrogen storage tank (HST), and battery are presented to urge the minimization of the total system cost, power redundancy, and power shortage. Particle swarm optimization (PSO) algorithm is utilized to determine the optimum size and operational energy management within the system. The results show that after the regulation of the energy storage system, the power redundancy and shortage of the hybrid energy system are greatly reduced with the decreases by 85.08% and 64.42%, respectively. Moreover, the power mismatch is still significantly affected by seasons. It is also found that the energy storage efficiency of the RSOC system is within 20% due to the fact that part of the electric energy is consumed by the BOP to maintain the operation of the RSOC system. Thus, more improvements should focus on simplifying the BOP system of the RSOC system and reducing the excess power consumption in the future.