Planning strategies of source-storage considering wind-photovoltaic-load time characteristics
DOI:DOI: 10.19783/j.cnki.pspc.191493
Key Words:wind-photovoltaic-load time characteristics  consumption level  source-storage planning strategy  time scenarios
Author NameAffiliation
ZHANG Yonghui 1. Jilin Baishan Power Plant, Songhuajiang Hydropower Co., Ltd., Jilin 132012, China
2. School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China 
LU Li 1. Jilin Baishan Power Plant, Songhuajiang Hydropower Co., Ltd., Jilin 132012, China
2. School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China 
PAN Chao 1. Jilin Baishan Power Plant, Songhuajiang Hydropower Co., Ltd., Jilin 132012, China
2. School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China 
ZHANG Yapu 1. Jilin Baishan Power Plant, Songhuajiang Hydropower Co., Ltd., Jilin 132012, China
2. School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China 
LUO Yuanxiang 1. Jilin Baishan Power Plant, Songhuajiang Hydropower Co., Ltd., Jilin 132012, China
2. School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China 
BAO Feng 1. Jilin Baishan Power Plant, Songhuajiang Hydropower Co., Ltd., Jilin 132012, China
2. School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China 
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Abstract:In order to improve the permeability of wind turbines and photovoltaics in an active distribution network, an active distribution network source-storage planning strategy is proposed considering wind-photovoltaic-load timing characteristics. Aiming at the time series fluctuation characteristics of distributed generation and load, the improved fuzzy C-means clustering algorithm is used to synthesize the wind-photovoltaic-load time scenarios. A multi-objective planning model that comprehensively considers distributed generation permeability, consumption level, economy, and voltage stability indicators is established. To solve the multi-objective planning model, the chaotic particle swarm optimization algorithm is used to improve and optimize the global optimization ability by introducing a congestion degree calculation strategy and an elite retention strategy. By simulating a 47-node power distribution system in a certain area, a source-storage multi-objective planning strategy is obtained, and the optimization scheme is evaluated based on the cumulative voltage density. The results verify the correctness and feasibility of the proposed method. This work is supported by National Key Research and Development Program of China (No. 2016YFB0900100).
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