Optimising operation management for multi-micro-grids control

IET Cyber-Physical Systems

Kazuhiko Sato¹  Jay Kishigami¹  Mianxiong Dong¹  Teerawat Kumrai¹  Kaoru Ota¹ 

[1] Muroran Institute of Technology;

关键词: power system management;    distributed power generation;    power generation control;    game theory;    particle swarm optimisation;    covariance matrices;    genetic algorithms;    photovoltaic power systems;    wind turbines;    battery storage plants;    operation management optimisation;    multi microgrids control;    renewable energy sources;    photovoltaic units;    wind turbine units;    battery energy storage;    MG central controller;    total energy expenses reduction;    fitness-based modified game particle swarm optimisation algorithm;    FMGPSO algorithm;    pollutant emissions;    multi mMG system;    nondominated sorting genetic algorithm-III;    multiobjective covariance matrix adaptation evolution strategy;    speed-constrained multiobjective particle swarm optimisation;   

DOI  :  10.1049/iet-cps.2017.0079

来源: DOAJ

【 摘 要 】

Nowadays, renewable energy sources in a micro-grid (MG) system have increased challenges in terms of the irregularly and fluctuation of the photovoltaic and wind turbine units. It is necessary to develop battery energy storage. The MG central controller is helping to develop it in the MG system for improving the time of availability. Thus, reducing the total energy expenses of MG and improving the renewable energy sources (battery energy storage) are considered together with the operation management of the MG system. This study proposes fitness-based modified game particle swarm optimisation (FMGPSO) algorithm to optimise the total costs of operation and pollutant emissions in the MG and multi-MG system. The optimal size of battery energy storage is also considered. A non-dominated sorting genetic algorithm-III, a multi-objective covariance matrix adaptation evolution strategy, and a speed-constrained multi-objective particle swarm optimisation are compared with the proposed FMGPSO to show the performance. The results of the simulation show that the FMGPSO outperforms both the comparison algorithms for the minimisation operation management problem of the MG and the multi-MG system.

【 授权许可】

Unknown