Optimization method for capacity of BESS considering charge-discharge cycle and renewable energy penetration rate

Energy Storage Pub Date : 2024-07-14 DOI:10.1002/est2.70003
Yu Zhao, Zhongge Luo, Yi Zhang, Mengjing Wu, Li Wen, Gen Li
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引用次数: 0

Abstract

In order to achieve the “carbon peaking and carbon neutrality” goals, we must vigorously develop renewable energy power generation. As the penetration of renewables progressively escalates, the corresponding demand for battery energy storage systems (BESS) within the power grid rises concomitantly. This paper presents an innovative optimization approach for configuring BESS, taking into account the incremental variations in renewable energy penetration levels and BESS charge-discharge cycles. Employing incremental analytical techniques and pivotal metrics such as capacity elasticity, the proposed method determines the optimal penetration rate and corresponding BESS capacity outcomes for deploying energy storage systems. An example analysis of a rural power distribution benchmark is carried out by using the method in this paper, which proves the effectiveness of the method in this paper. This methodology was substantiated through its application to a case study of a rural power distribution benchmark, thereby validating its efficacy. Furthermore, it was compared with the particle swarm optimization, providing a comparative assessment of their relative performance.

考虑充放电循环和可再生能源渗透率的 BESS 容量优化方法
为了实现 "碳调峰和碳中和 "的目标,我们必须大力发展可再生能源发电。随着可再生能源渗透率的逐步提高,电网对电池储能系统(BESS)的需求也相应增加。考虑到可再生能源渗透水平和 BESS 充放电周期的增量变化,本文提出了一种创新的 BESS 配置优化方法。该方法采用增量分析技术和容量弹性等关键指标,确定了部署储能系统的最佳渗透率和相应的 BESS 容量结果。本文使用该方法对农村配电基准进行了实例分析,证明了本文方法的有效性。通过对农村配电基准的案例研究,证明了该方法的有效性。此外,本文还将该方法与粒子群优化法进行了比较,对两者的相对性能进行了比较评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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