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Optimal reactive power management through a hybrid BOA–GWO–PSO algorithm for alleviating congestion

Author

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  • Manjulata Badi

    (ACED, Alliance University)

  • Sheila Mahapatra

    (ACED, Alliance University)

Abstract

In today's deregulated energy market, improving grid management in generating power with load optimization is a critical challenge. It is also perilous that the system does not have any problems owing to transmission line clogs. The Butterfly Optimization Algorithm is used for load balancing and load optimization in electricity markets. The proposed approach integrates Particle Swarm Optimization and Grey Wolf Optimizer, merging them with Butterfly Optimization Algorithm as a hybridised form to enhance exploration and exploitation skills. The benefit of the Butterfly Optimization Algorithm in general, as well as when it is employed to address difficult optimization issues, is validated using the New England 39 bus test system. The amalgamated algorithm approach was compared to other established meta-heuristic algorithms for the reactive power management under variable loading conditions. Using the realistic New England 39 bus system, the suggested algorithm minimizes transmission losses by 6.344% and operating costs by 6.347% with respect to the base case, respectively. The research work reveals that proposed amalgamated algorithm employing Butterfly Optimization Algorithm, Grey Wolf Optimizer, and Particle Swarm Optimization performs better and offers more potential in a range of situations. The proposed technique mathematical validation indicated that it has the capacity to tackle complex optimization issues and compete with contemporary peer-reviewed literature solutions.

Suggested Citation

  • Manjulata Badi & Sheila Mahapatra, 2023. "Optimal reactive power management through a hybrid BOA–GWO–PSO algorithm for alleviating congestion," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(4), pages 1437-1456, August.
    • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:4:d:10.1007_s13198-023-01946-9
    DOI: 10.1007/s13198-023-01946-9
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    References listed on IDEAS

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    1. Saurav Raj & Sheila Mahapatra & Chandan Kumar Shiva & Biplab Bhattacharyya, 2021. "Implementation and Optimal Sizing of TCSC for the Solution of Reactive Power Planning Problem Using Quasi-Oppositional Salp Swarm Algorithm," International Journal of Energy Optimization and Engineering (IJEOE), IGI Global, vol. 10(2), pages 74-103, April.
    2. Manjulata Badi & Sheila Mahapatra & Bishwajit Dey & Saurav Raj, 2022. "A Hybrid GWO-PSO Technique for the Solution of Reactive Power Planning Problem," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 13(1), pages 1-30, January.
    3. Raj, Saurav & Mahapatra, Sheila & Babu, Rohit & Verma, Sumit, 2023. "Hybrid intelligence strategy for techno-economic reactive power dispatch approach to ensure system security," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    4. Seok, Hyesung & Chen, Chen, 2019. "An intelligent wind power plant coalition formation model achieving balanced market penetration growth and profit increase," Renewable Energy, Elsevier, vol. 138(C), pages 1134-1142.
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