Multi-criteria decision making monarch butterfly optimization for optimal distributed energy resources mix in distribution networks

Singh, P., Meena, N. K., Yang, J. , Vega-Fuentes, E. and Bishnoi, S. K. (2020) Multi-criteria decision making monarch butterfly optimization for optimal distributed energy resources mix in distribution networks. Applied Energy, 278, 115723. (doi: 10.1016/j.apenergy.2020.115723)

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Abstract

The optimal integration of distributed energy resources (DERs) is a multiobjective and complex combinatorial optimization problem that conventional optimization methods cannot solve efficiently. This paper reviews the existing DER integration models, optimization and multi-criteria decision-making approaches. Further to that, a recently developed monarch butterfly optimization method is introduced to solve the problem of DER mix in distribution systems. A new multiobjective DER integration problem is formulated to find the optimal sites, sizes and mix (dispatchable and non-dispatchable) for DERs considering multiple key performance objectives. Besides, a hybrid method that combines the monarch butterfly optimization and the technique for order of preference by similarity to ideal solution (TOPSIS) is proposed to solve the formulated large-scale multi-criteria decision-making problem. Whilst the meta-heuristic optimization method generates non-dominated solutions (creating Pareto-front), the TOPSIS approach selects that with the most promising outcome from a large number of alternatives. The effectiveness of this approach is verified by solving single and multiobjective dispatchable DER integration problems over the benchmark 33-bus distribution system and the performance is compared with the existing optimization methods. The proposed model of DER mix and the optimization technique significantly improve the system performance in terms of average annual energy loss reduction by 78.36%, mean node voltage deviation improvement by 9.59% and average branches loadability limits enhancement by 50%, and minimized the power fluctuation induced by 48.39% renewable penetration. The proposed optimization techniques outperform the existing methods with promising exploration and exploitation abilities to solve engineering optimization problems.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Vega, Mr Eduardo and Yang, Dr Jin
Creator Roles:
Yang, J.Visualization, Investigation, Formal analysis, Writing – review and editing
Vega-Fuentes, E.Writing – review and editing, Formal analysis
Authors: Singh, P., Meena, N. K., Yang, J., Vega-Fuentes, E., and Bishnoi, S. K.
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:Applied Energy
Publisher:Elsevier
ISSN:0306-2619
ISSN (Online):1872-9118
Published Online:14 September 2020
Copyright Holders:Copyright © 2020 The Authors
First Published:First published in Applied Energy 278:115723
Publisher Policy:Reproduced under a Creative Commons license

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