Optimal energy management of microgrid using advanced multi-objective particle swarm optimization

被引:16
作者
Anh, Ho Pham Huy [1 ]
Kien, Cao Van [2 ]
机构
[1] Ho Chi Minh City Univ Technol VNU HCM, FEEE, Ho Chi Minh City, Vietnam
[2] Ind Univ Ho Chi Minh City, Fac Elect Technol, Ho Chi Minh City, Vietnam
关键词
Optimal energy management; Hybrid microgrid; Multi-objective genetic algorithm; Multi-objective particle swarm optimization algorithm; 24-hour optimal energy management simulations; Bio-inspired optimization methods; SYSTEM;
D O I
10.1108/EC-05-2019-0194
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Purpose The purpose of this paper is to propose an optimal energy management (OEM) method using intelligent optimization techniques applied to implement an optimally hybrid heat and power isolated microgrid. The microgrid investigated combines renewable and conventional power generation. Design/methodology/approach Five bio-inspired optimization methods include an advanced proposed multi-objective particle swarm optimization (MOPSO) approach which is comparatively applied for OEM of the implemented microgrid with other bio-inspired optimization approaches via their comparative simulation results. Findings Optimal multi-objective solutions through Pareto front demonstrate that the advanced proposed MOPSO method performs quite better in comparison with other meta-heuristic optimization methods. Moreover, the proposed MOPSO is successfully applied to perform 24-h OEM microgrid. The simulation results also display the merits of the real time optimization along with the arbitrary of users' selection as to satisfy their power requirement. Originality/value This paper focuses on the OEM of a designed microgrid using a newly proposed modified MOPSO algorithm. Optimal multi-objective solutions through Pareto front demonstrate that the advanced proposed MOPSO method performs quite better in comparison with other meta-heuristic optimization approaches.
引用
收藏
页码:2085 / 2110
页数:26
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