Integrated Intelligent Energy ›› 2025, Vol. 47 ›› Issue (6): 74-84.doi: 10.3969/j.issn.2097-0706.2025.06.008

• Source-grid Coordination • Previous Articles     Next Articles

Optimal power allocation for electrochemical energy storage power stations based on MOIBKA algorithm

WANG Cheng1(), SHAO Chong2(), HE Xin2(), DONG Haiying1,*()   

  1. 1. School of New Energy and Power Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China
    2. State Grid Gansu Electric Power Company,Lanzhou 730030,China
  • Received:2024-06-03 Revised:2024-10-08 Published:2025-06-25
  • Contact: DONG Haiying E-mail:weijinwangcheng@163.com;shaoch_dkzx@gs.sgcc.com.cn;122468126@qq.com;hydong@mail.lzjtu.cn
  • Supported by:
    Gansu Province Major Science and Technology Project(23ZDGA005)

Abstract:

To address the power allocation issue of electrochemical energy storage stations under the influence of multiple factors,an optimal power allocation strategy for electrochemical energy storage power stations based on the multi-objective improved black-winged kite algorithm (MOIBKA) is proposed. The topology of the electrochemical energy storage power station is established,and three evaluation indicators for the operation of the power station are proposed. Based on the traditional power allocation model for energy storage stations,a multi-objective power allocation model is established,aiming to achieve the lowest total operating cost of energy storage power stations,the smallest state of health loss of energy storage units,and the best state of charge (SOC) consistency. The model is solved using the MOIBKA through multiple strategies. Comparative simulation analysis and operational evaluation indicators prove that the proposed strategy could effectively reduce the number of charging and discharging cycles and the state of health loss of energy storage units while improving SOC consistency. This achieves optimal power allocation for energy storage power stations.

Key words: new power system, electrochemical energy storage power station, power allocation, multi-objective optimization, black-winged kite algorithm, evaluation indicator, state of charge, state of health loss

CLC Number: