Time Series Based Co-optimization Model of Active and Reactive Power with PV-wind and Storage

Pengyu Wei, Dongsheng Cai, Olusola Bamisile, Linlin Li, Qixing Huang
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Abstract

With the increasing penetration of renewable energy, the application of distributed power sources is becoming more and more widespread. Distributed generators are involved in the traditional distribution network applications. Energy storage, as a key factor in regulating the voltage load curve, also affects the flow of reactive power and tide through the charging and discharging of electrical energy, and thus plays a critical role in reactive-active co-optimization. This paper propses a time series based co-optimization stratege for energy regulation of distributed power network. Firstly, reactive generators are added and a stage of energy storage siting and capacity setting is carried out. Then active-reactive co-optimization is carried out on this basis, and no energy storage is set as the reference quantity to increase the comparability. Finally, simulation experiment are conducted for a improved system of traditional IEEE33 node. The results show that energy storage has unique advantages in reducing active network loss. And the active-reactive co-optimization has a better performance in reducing network loss and voltage deviation under the state of renewable energy participation.
基于时间序列的PV-wind - Storage有功无功协同优化模型
随着可再生能源的日益普及,分布式电源的应用也越来越广泛。分布式发电机是传统配电网应用的一部分。储能作为调节电压负荷曲线的关键因素,也通过电能的充放电影响无功潮流和潮流,在无功协同优化中起着至关重要的作用。提出了一种基于时间序列的分布式电网能量调节协同优化策略。首先,增加无功发电机,进行储能选址和容量设定阶段。然后在此基础上进行有功-无功协同优化,不设置储能作为参考量,增加可比性。最后,对传统IEEE33节点的改进系统进行了仿真实验。结果表明,储能在降低有功网络损耗方面具有独特的优势。在可再生能源参与状态下,有功-无功协同优化在降低网损和电压偏差方面具有较好的效果。
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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