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

Ho Pham Huy Anh (Faculty of Electrical Electronics Engineering (FEEE), Ho Chi Minh City University of Technology – VNU-HCM, Ho Chi Minh City, Vietnam)
Cao Van Kien (Faculty of Electronics Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam)

Engineering Computations

ISSN: 0264-4401

Article publication date: 7 February 2020

Abstract

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.

Keywords

Acknowledgements

This paper is totally funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED), under grant MDT 107.01-2018.10.

Citation

Anh, H.P.H. and Kien, C.V. (2020), "Optimal energy management of microgrid using advanced multi-objective particle swarm optimization", Engineering Computations, Vol. 37 No. 6, pp. 2085-2110. https://doi.org/10.1108/EC-05-2019-0194

Publisher

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Emerald Publishing Limited

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