Electric Power ›› 2022, Vol. 55 ›› Issue (12): 78-85.DOI: 10.11930/j.issn.1004-9649.202208020

Previous Articles     Next Articles

Massive Scenario Reduction Based Distribution-Level Power System Planning Considering the Coordination of Source, Network, Load and Storage

LIU Jinsen1, LUO Ning1, WANG Jie1, XU Chang1, Cao Yi2, Liu Zhiwen2   

  1. 1. Power Grid Planning and Research Center, Guizhou Power Grid Co., Ltd., Guiyang 550003, China;
    2. Energy Research Institute of China Southern Power Grid Co., Ltd., Guangzhou 510663, China
  • Received:2022-08-04 Revised:2022-09-08 Published:2022-12-28
  • Supported by:
    This work is supported by the Key Science and Technology Project of China Southern Power Grid (No.GZKJXM20210368).

Abstract: The integration of high-proportion renewable power generation has brought great challenges to the efficiency of distribution network planning methods and the economy of planning results. In order to solve the problem of coordination between the massive operation data of renewable power generation and the coordinated planning of the source-network-load-storage, this paper proposes a coordinated planning method of the source-network-load-storage based on the massive scenario dimension reduction. Firstly, the dimensionality reduction clustering is carried out on the wind-light-load mass high-dimensional scenarios by the principal component Gaussian mixture clustering algorithm, and the typical scenario set of wind and power loads is obtained; then, a source-network-load-storage coordination planning model of distribution network for massive scenarios is constructed, and the second-order cone relaxation technique is adopted to convert the non-convex constraints to convex ones; finally, the effectiveness of the proposed massive scenario dimension reduction clustering method and distribution network planning model is verified on the Portugal 54-node distribution network.

Key words: distribution network, principal component analysis method, Gaussian mixed clustering, source-network-load-storage, coordinated planning