Journal of Shanghai Jiao Tong University ›› 2022, Vol. 56 ›› Issue (10): 1294-1307.doi: 10.16183/j.cnki.jsjtu.2021.371

• New Type Power System and the Integrated Energy • Previous Articles     Next Articles

Peafowl Optimization Algorithm Based Bi-Level Multi-Objective Optimal Allocation of Energy Storage Systems in Distribution Network

YANG Bo1, WANG Junting1, YU Lei1, CAO Pulin1(), SHU Hongchun1, YU Tao2,3   

  1. 1. Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650500, China
    2. College of Electric Power, South China University of Technology, Guangzhou 510640, China
    3. Guangdong Provincial Key Laboratory of Intelligent Measurement and Advanced Metering of Power Grid, Guangzhou 510640, China
  • Received:2021-09-24 Online:2022-10-28 Published:2022-11-03
  • Contact: CAO Pulin


Based on the relation between battery energy storage systems (BESSs) planning and operation, a multi-objective optimal allocation model that takes into account both economic and technical requirements is established, and a bi-level optimization structure is constructed to ensure effective planning and high-efficient operation of BESSs. In the inner layer, a peafowl optimization algorithm (POA) is employed to solve the BESSs charge-discharge operation strategy with the purpose of BESSs operation benefit maximization. In the outer layer, a multi-objective peafowl optimization algorithm (MOPOA) is devised to solve the Pareto solution set of BESSs siting and sizing scheme, which aims at minimizing BESSs cost, as well as voltage fluctuation and load fluctuation in distribution network. Furthermore, a typical scenario set is obtained via the clustering algorithm considering uncertain operating conditions. The simulation is performed based on the extended IEEE-33 bus system. The results show that the proposed algorithm achieves a trade-off between local search and global search, thus obtains a high-quality solution. It can obtain a more widely distributed and uniform Pareto front, which not only achieves the best investment benefit, but also improves voltage quality and power stability.

Key words: battery energy storage systems (BESSs), bi-level optimal allocation model, peafowl optimization algorithm (POA), Pareto based multi-objective optimization

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