Modified dragonfly optimisation for distributed energy mix in distribution networks

Singh, P., Meena, N. K., Yang, J. , Bishnoi, S. K., Vega-Fuentes, E. and Lou, C. (2021) Modified dragonfly optimisation for distributed energy mix in distribution networks. Energies, 14(18), 5690. (doi: 10.3390/en14185690)

[img] Text
251944.pdf - Published Version
Available under License Creative Commons Attribution.

373kB

Abstract

This article presents a two-stage optimization model aiming to determine optimal energy mix in distribution networks, i.e., battery energy storage, fuel cell, and wind turbines. It aims to alleviate the impact of high renewable penetration on the systems. To solve the proposed complex optimization model, a standard variant of the dragonfly algorithm (DA) has been improved and then applied to find the optimal mix of distributed energy resources. The suggested improvements are validated before their application. A heuristic approach has also been introduced to solve the second stage problem that determines the optimal power dispatch of battery energy storage as per the size suggested by the first stage. The proposed framework was implemented on a benchmark 33-bus and a practical Indian 108-bus distribution network over different test cases. The proposed model for energy mix and modified DA technique has significantly enhanced the operational performance of the network in terms of average annual energy loss reduction, node voltage profiles, and demand fluctuation caused by renewables.

Item Type:Articles
Keywords:Battery energy storage system, distribution networks, fuel cells, optimization, wind turbines.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Yang, Dr Jin and Vega, Mr Eduardo and Lou, Chengwei
Authors: Singh, P., Meena, N. K., Yang, J., Bishnoi, S. K., Vega-Fuentes, E., and Lou, C.
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:Energies
Publisher:MDPI
ISSN:1996-1073
ISSN (Online):1996-1073
Published Online:10 September 2021
Copyright Holders:Copyright © 2021 The Authors
First Published:First published in Energies 14(18): 5690
Publisher Policy:Reproduced under a Creative Commons License

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
309634Street2Grid - An Electricity Blockchain Platform for P2P Energy TradingJin YangEngineering and Physical Sciences Research Council (EPSRC)EP/S001778/2ENG - Systems Power & Energy