徐艳春, 张进, 汪平, MI Lu. 考虑配电网静态电压稳定性的微电网优化配置[J]. 电力建设, 2022, 43(8): 87-101.
引用本文: 徐艳春, 张进, 汪平, MI Lu. 考虑配电网静态电压稳定性的微电网优化配置[J]. 电力建设, 2022, 43(8): 87-101.
XU Yan-chun, ZHANG Jin, WANG Ping, MI Lu. Optimal Configuration of Microgrid Considering Static Voltage Stability of Distribution Network[J]. Electric Power Construction, 2022, 43(8): 87-101.
Citation: XU Yan-chun, ZHANG Jin, WANG Ping, MI Lu. Optimal Configuration of Microgrid Considering Static Voltage Stability of Distribution Network[J]. Electric Power Construction, 2022, 43(8): 87-101.

考虑配电网静态电压稳定性的微电网优化配置

Optimal Configuration of Microgrid Considering Static Voltage Stability of Distribution Network

  • 摘要: 考虑到风机、光伏两种分布式电源出力在时间上具有互补的特征,利用储能装置功率双向流动的特点,将可再生能源和储能装置以微电网的形式接入配电网实现可再生能源的高比例接入。对现有的配电网静态电压稳定性指标进行改进,以配电网的静态电压稳定性和运行经济性为目标研究微电网系统的定容选址问题。采用基于K-means++方法的多场景技术处理可再生能源出力不确定性问题,针对配电网不同地区的可再生能源出力特点,计算出风光储三种装置不同的最佳容量配置比例。对平衡优化器(equilibrium optimizer, EO)算法进行改进,利用Tent映射产生的混沌序列代替随机生成的初始种群,根据拥挤度和非支配排序实现多目标问题寻优。最后,在由三种地形组成的IEEE 33节点系统和PG&E-69系统中验证了所提模型和算法的有效性。

     

    Abstract: Considering that the output of photovoltaic and wind power is complementary in time, and that the energy storage devices may provide bidirectional power flow, the renewable energy and storage devices are often connected to the distribution grid in the form of microgrid to realize the high proportion of renewable energy access. The static voltage stability index of the existing distribution grid is improved, and the static voltage stability and operation economy of the distribution network are used as the target to study the location and capacity determination of the energy storage in the microgrid. The multi-scenario technology based on K-means++ method is used to deal with the uncertainty of renewable energy output, and the optimal capacity allocation ratio of three types of scenery storage devices is calculated for the renewable energy output characteristics of the distribution network in different areas. The equilibrium optimizer(EO) algorithm is improved by using chaotic sequences generated by Tent mapping instead of randomly generated initial populations to achieve multi-objective problem solution according to congestion and non-dominated ranking. The effectiveness of the model and algorithm in this paper is verified by simulation in the IEEE 33-node and PG&E-69 system.

     

/

返回文章
返回