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Modified Dragonfly Optimisation for Distributed Energy Mix in Distribution Networks

Author

Listed:
  • Pushpendra Singh

    (Department of Electrical Engineering, Rajasthan Technical University, Kota 324010, India
    Department of Electrical Engineering, Government Women Engineering College, Ajmer 305002, India)

  • Nand Kishor Meena

    (College of Engineering and Applied Science, Aston University, Birmingham B4 7ET, UK)

  • Jin Yang

    (James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK)

  • Shree Krishna Bishnoi

    (Department of Electronics and Communication, Government Engineering College, Bikaner 334004, India)

  • Eduardo Vega-Fuentes

    (James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK)

  • Chengwei Lou

    (James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK)

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.

Suggested Citation

  • Pushpendra Singh & Nand Kishor Meena & Jin Yang & Shree Krishna Bishnoi & Eduardo Vega-Fuentes & Chengwei Lou, 2021. "Modified Dragonfly Optimisation for Distributed Energy Mix in Distribution Networks," Energies, MDPI, vol. 14(18), pages 1-19, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5690-:d:632536
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    References listed on IDEAS

    as
    1. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2018. "Battery energy storage system size determination in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 109-125.
    2. Kumar, Abhishek & Meena, Nand K. & Singh, Arvind R. & Deng, Yan & He, Xiangning & Bansal, R.C. & Kumar, Praveen, 2019. "Strategic integration of battery energy storage systems with the provision of distributed ancillary services in active distribution systems," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    3. Singh, Pushpendra & Meena, Nand K. & Yang, Jin & Vega-Fuentes, Eduardo & Bishnoi, Shree Krishna, 2020. "Multi-criteria decision making monarch butterfly optimization for optimal distributed energy resources mix in distribution networks," Applied Energy, Elsevier, vol. 278(C).
    4. Theo, Wai Lip & Lim, Jeng Shiun & Ho, Wai Shin & Hashim, Haslenda & Lee, Chew Tin, 2017. "Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 531-573.
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    Cited by:

    1. Balvender Singh & Adam Slowik & Shree Krishan Bishnoi & Mandeep Sharma, 2023. "Frequency Regulation Strategy of Two-Area Microgrid System with Electric Vehicle Support Using Novel Fuzzy-Based Dual-Stage Controller and Modified Dragonfly Algorithm," Energies, MDPI, vol. 16(8), pages 1-24, April.

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