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Metaheuristic nature-based algorithm for optimal reactive power planning

Author

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  • Swetha Shekarappa Gudadappanavar

    (Alliance University)

  • Sheila Mahapatra

    (Alliance University)

Abstract

An oppositional based Harris Hawks optimization technique enthralled is suggested and implemented to reactive power optimization planning in power systems in this research. As transmission loss minimization is a fundamental criterion for secured power system operation, Var planning has become increasingly important for improved coordination in modern power systems. The Oppositional based Harris Hawk Optimizer (OHHO) algorithm, which is implemented on the IEEE 57 bus system, is proposed in this paper as an enhanced meta-heuristic nature inspired approach. The suggested algorithm is based on the Harris Hawk Optimizer (HHO) algorithm, which is a speculative algorithm with no intrinsic dependent variables. To get improved estimation for the predominant approach, the search space is subsequently altered by combining HHO with the Oppositional Based Learning (OBL) technique. In the present study, the OHHO is proposed for reducing transmission losses, operating costs, and improving voltage profile at buses. The impact of the optimizers' update technique on the objective functions is examined. The research focuses on issues such as reactive power provided by generator buses, shunt capacitors, and transformer tap position changes. The simulation outcomes gained on typical test systems demonstrate that the proposed OHHO outperforms HHO, and other optimization techniques recently published in the state-of-the-art literature. Graphical Abstract

Suggested Citation

  • Swetha Shekarappa Gudadappanavar & Sheila Mahapatra, 2022. "Metaheuristic nature-based algorithm for optimal reactive power planning," 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. 13(3), pages 1453-1466, June.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:3:d:10.1007_s13198-021-01489-x
    DOI: 10.1007/s13198-021-01489-x
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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. Yuan, Guanghui & Yang, Weixin, 2019. "Study on optimization of economic dispatching of electric power system based on Hybrid Intelligent Algorithms (PSO and AFSA)," Energy, Elsevier, vol. 183(C), pages 926-935.
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