Affiliation:
1. School of Electronics and Information Engineering Shanghai Electric Power University Shanghai 201306 China
2. Hangzhou Chun'an Power Supply Company State Grid Zhejiang Electric Power Co., LTD Hangzhou 311700 China
3. Shaoxing Xinchang Power Supply Company State Grid Zhejiang Electric Power Co., LTD Shaoxing 312500 China
Abstract
The increasing penetration rate of distributed energy brings more complex problems of voltage quality, safety and stability to the distribution network. A single optimal configuration of reactive power or energy storage is difficult to meet the increasingly diversified needs of modern power grids. This paper proposes a configuration strategy combining energy storage and reactive power to meet the needs of new energy distribution networks in terms of active power regulation and reactive power compensation, and to achieve tradeoff optimization in flexibility, voltage quality and economy, so as to adapt to the influence of new energy with different permeability. Firstly, the safety and stability evaluation system of distribution network is established with the target of flexibility demand and reactive power demand. Secondly, considering the coupling of planning layer and operation layer, a two‐layer model of energy‐reactive power optimization is established. After that, the gray wolf algorithm is used to solve the model, which enhances the global space exploration ability and reduces the possibility of falling into the local optimal. Finally, the improved IEEE33 node power distribution system is used for simulation test to verify the rationality and effectiveness of this scheme. The simulation results show that the scheme proposed in this paper can effectively improve the economy, security and stability of the distribution network, and can obtain an optimal configuration scheme with multi‐objective considerations under different new energy penetration rates. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.
Funder
Natural Science Foundation of Shanghai Municipality
Subject
Electrical and Electronic Engineering
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