Integrated Intelligent Energy ›› 2022, Vol. 44 ›› Issue (6): 52-58.doi: 10.3969/j.issn.2097-0706.2022.06.006

• Integrated Energy System • Previous Articles     Next Articles

Optimal allocation of a wind‒PV‒battery hybrid system in smart microgrid based on particle swarm optimization algorithm

WANG Xin1(), CHEN Zucui2(), BIAN Zaiping1(), WANG Yeyao1(), WU Yumiao2()   

  1. 1. Hainan Zhonghongxin Engineering Consulting Company Limited,Haikou 571100,China
    2. Hainan Electric Power Design & Research Institute,Haikou 571100,China
  • Received:2022-03-11 Revised:2022-05-13 Online:2022-06-25 Published:2022-06-27

Abstract:

With the proposal of the goals of carbon peaking and carbon neutrality,constructing clean energy generators on roof tops is widely recommended in different regions of China.The microgrid consisting of wind power,photovoltaic power and energy storage devices,can reduce carbon emissions from regional production activities through new energy generation,and improve the power supply reliability of living and office areas.To optimize the return of the investment on microgrid,the ratio of wind power,photovoltaic power and energy storage capacity of a hybrid system has been the focus of researches.According to the light condition,wind speed and other unique geographical features in Hainan Province,the optimal allocation of a wind?PV?battery hybrid system in smart microgrid is calculated by particle swarm optimization algorithm.Data collected from the living and office areas of the smart microgrid demonstrative project are used in an economic analysis,which provide theoretical basis and data resources for the further energy efficiency retrofit of smart microgrids.

Key words: smart microgrid, particle swarm optimization algorithm, carbon neutrality, capacity ratio, multi-objective optimization, wind power, photovoltaic power generation, energy storage, energy conservation and emission reduction, electric energy substitution

CLC Number: