• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

ELECTRIC POWER CONSTRUCTION ›› 2022, Vol. 43 ›› Issue (8): 87-101.doi: 10.12204/j.issn.1000-7229.2022.08.009

• Research and Application of Key Technologies for Distribution Network Planning and Operation Optimization under New Energy Power Systems•Hosted by Professor WANG Shouxiang and Dr. ZHAO Qianyu• • Previous Articles     Next Articles

Optimal Configuration of Microgrid Considering Static Voltage Stability of Distribution Network

XU Yanchun1(), ZHANG Jin1(), WANG Ping1(), MI Lu2()   

  1. 1. Hubei Key Laboratory of Cascaded Hydropower Stations Operation & Control (China Three Gorges University), Yichang 443002, Hubei Province, China
    2. Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas 77840, USA
  • Received:2021-12-23 Online:2022-08-01 Published:2022-08-05
  • Contact: ZHANG Jin E-mail:xyc7309@163.com;sxdxzj@126.com;22813766@qq.com;mlu@ee.tamu.edu
  • Supported by:
    National Natural Science Foundation of China(51707102)


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.

Key words: distribution network, static voltage stability, multi-objective optimization, distributed generation, multi-scenario analysis, microgrid

CLC Number: