A Hybrid Optimization Method for Distribution System Expansion Planning with Lithium-ion Battery Energy Storage Systems

Andrej Trpovski, Prabal Banerjee, Yan Xu, T. Hamacher
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引用次数: 2

Abstract

The accelerating trend of mobility electrification and the constantly increasing accessibility of distributed energy resources (DERs) play an important role in the changing landscape of the modern power system. To maintain the reliability and continuity of supply under the newly encountered EV charging demand, it is a necessity for the planning engineers to use economically viable planning strategies. Traditionally, the expansion of the distribution system, is accomplished using additional lines, cables, transformers, switchgear, or substations. Modern expansion planning is further advanced to consider widespread use of centralized and/or distributed energy storage systems due to their cost competitiveness. In this paper, a robust distribution system expansion planning approach for a combined installation of new lines and energy storage systems is proposed. A hybrid optimization method using a meta-heuristic Genetic Algorithm (GA) and a mixed integer quadratically constrained program (MIQCP) is defined. The solution encompasses a cost-effective line expansion strategy combined with the placement of new energy storage systems and their optimal sizing. The proposed model is tested on a modified 45 bus case study of a Singaporean synthetic grid model. The results are shown and analyzed to conclude the benefits of using energy storage systems as an additional strategy in the expansion planning approach.
锂离子电池储能配电网扩容规划的混合优化方法
汽车电气化的加速发展趋势和分布式能源可及性的不断提高在现代电力系统格局的变化中发挥着重要作用。在新遇到的电动汽车充电需求下,为了保持供电的可靠性和连续性,规划工程师必须采用经济可行的规划策略。传统上,配电系统的扩展是通过额外的线路、电缆、变压器、开关设备或变电站来完成的。由于集中式和/或分布式储能系统的成本竞争力,现代扩展计划进一步推进,考虑广泛使用集中式和/或分布式储能系统。本文提出了一种用于新线路和储能系统联合安装的配电系统扩展规划方法。提出了一种基于元启发式遗传算法(GA)和混合整数二次约束规划(MIQCP)的混合优化方法。该解决方案包括具有成本效益的线路扩展策略,结合新储能系统的布局及其最佳尺寸。以新加坡综合网格模型为例,对改进后的45辆客车模型进行了验证。结果显示和分析,以总结使用储能系统作为扩展规划方法中的附加策略的好处。
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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