Modified Dragonfly Optimisation for Distributed Energy Mix in Distribution Networks

Pushpendra Singh*, Nand Kishor Meena*, Jin Yang*, Shree Krishna Bishnoi, Eduardo Vega-Fuentes, Chengwei Lou

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Article number5690
Issue number18
Publication statusPublished - 10 Sept 2021

Bibliographical note

Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://

Funding: This research was supported by project “Street2Grid—An electricity blockchain platform for P2P energy trading” (Reference: EP/S001778/2), funded by the Engineering and Physical Sciences Research Council (EPSRC), UK. The Author, Nand K. Meena would like to acknowledge the funding received from the European Union’s Horizon 2020 research and innovation program under the Marie
Sklodowska-Curie grant agreement No. 713694.


  • battery energy storage system
  • distribution networks
  • fuel cells
  • optimization
  • wind turbines


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