Integrated Intelligent Energy ›› 2023, Vol. 45 ›› Issue (1): 49-57.doi: 10.3969/j.issn.2097-0706.2023.01.006

• Power System Planning • Previous Articles     Next Articles

Optimized configuration of distributed photovoltaic and energy storage system based on improved particle swarm algorithm

HU Zuyuan1, JIN Xianlin1, TAN Yazhi2,*(), FAN Jingyi2   

  1. 1. Guohua Energy Investment Company Limited, Beijing 100007,China
    2. School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
  • Received:2022-07-20 Revised:2022-09-05 Published:2023-01-25
  • Supported by:
    National Natural Science Foundation of China(51977074)

Abstract:

The proposal of the goals of carbon peaking and carbon neutrality makes a further request on the grid connection of distributed energy systems. To address the uncertainty triggered by the grid-connected distributed photovoltaic (PV) systems, the optimal configuration of distributed PV and energy storage systems is studied. Based on the typical PV output scenarios selected by clustering process, a hybrid integral non-linear programming model for the optimal configuration of a photovoltaic and energy storage system was established while taking economic benefits, load fluctuation and peak-shaving rates into consideration. The model was solved by adaptive particle swarm optimization algorithm, and the influence of different loads and electricity prices on energy storage capacity and on the operation of the system was analyzed. The results show that the energy storage system can effectively stabilize the photovoltaic output, optimize the load curve and improve the overall operating performance of the system, which verifies the feasibility of the model and the effectiveness of the solution.

Key words: carbon neutrality, distributed photovoltaic, energy storage system, clustering, improved particle swarm algorithm, capacity allocation, distributed power source, distribution network

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