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

doi:10.3390/en14185690

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

College of Engineering and Physical Sciences

Department of Electrical Engineering, Rajasthan Technical University, Kota 324010, India; Department of Electrical Engineering, Government Women Engineering College, Ajmer 305002, India
Department of Electronics and Communication, Government Engineering College, Bikaner 334004, India
James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK
University of Glasgow

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

18 Downloads (Pure)

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.

Original language	English
Article number	5690
Journal	Energies
Volume	14
Issue number	18
DOIs	https://doi.org/10.3390/en14185690
Publication status	Published - 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://
creativecommons.org/licenses/by/
4.0/).

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.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

battery energy storage system
distribution networks
fuel cells
optimization
wind turbines

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10.3390/en14185690Licence: CC BY 3.0

Modified Dragonfly Optimisation
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:// creativecommons.org/licenses/by/ 4.0/).
Final published version, 365 KBLicence: CC BY 3.0

Cite this

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title = "Modified Dragonfly Optimisation for Distributed Energy Mix in Distribution Networks",

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.",

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N2 - 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.

AB - 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.

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JO - Energies

JF - Energies

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Modified Dragonfly Optimisation for Distributed Energy Mix in Distribution Networks

Abstract

Bibliographical note

UN SDGs

Keywords

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