Multi-objective capacity optimization of renewable energy power system considering techno-economic comparisons of various energy storage technologies

被引：0
|
作者：
Guo S. [1 ]
He Y. [2 ]
Aynur K. [1 ]
Song G. [1 ]
Wang H. [1 ]
Pei H. [1 ]
机构：
[1] College of Energy and Electrical Engineering, Hohai University, Nanjing
[2] College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing
来源：
Taiyangneng Xuebao/Acta Energiae Solaris Sinica | 2022年 / 43卷 / 10期
关键词：
Electric power system planning; Energy storage; Multiobjective optimization; Renewable energy;
D O I：
10.19912/j.0254-0096.tynxb.2021-0314
中图分类号：
学科分类号：
摘要：
This paper conducted the multi-objective capacity optimization of renewable energy power system considering techno-economic comparisons of battery, thermal energy storage, pumped hydro storage and hydrogen storage. The multi-objective capacity optimization model considers the minimization of levelized cost of energy and loss probability of power supply, which is solved by four representative multi-objective evolutionary algorithms. This paper also proposes a comprehensive metric of algorithms based on hypervolume, and the device operation characteristics and resources uncertainties are considered to improve the accuracy of simulation. The comparative results of algorithms show that the average rank of non-dominated sorting genetic algorithm is 1.6, which has the best comprehensive performance. The quantitative techno-economic comparative results of energy storage show that thermal energy storage is the most cost-effective under different reliability conditions. The sensibility analyses of different load profile and different resource level verify the effectiveness of techno-economic comparative results. © 2022, Solar Energy Periodical Office Co., Ltd. All right reserved.
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页码：424 / 431
页数：7
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