access icon openaccess Optimising operation management for multi-micro-grids control

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.

Inspec keywords: photovoltaic power systems; power system management; wind turbines; covariance matrices; particle swarm optimisation; genetic algorithms; power generation control; game theory; battery storage plants; distributed power generation

Other keywords: nondominated sorting genetic algorithm-III; multiobjective covariance matrix adaptation evolution strategy; renewable energy sources; battery energy storage; operation management optimisation; total energy expenses reduction; FMGPSO algorithm; pollutant emissions; wind turbine units; MG central controller; multi microgrids control; fitness-based modified game particle swarm optimisation algorithm; photovoltaic units; speed-constrained multiobjective particle swarm optimisation; multi mMG system

Subjects: Power system management, operation and economics; Distributed power generation; Optimisation techniques; Optimisation techniques; Control of electric power systems; Game theory; Solar power stations and photovoltaic power systems; Wind power plants

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