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Hybrid intelligence strategy for techno-economic reactive power dispatch approach to ensure system security

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  • Raj, Saurav
  • Mahapatra, Sheila
  • Babu, Rohit
  • Verma, Sumit

Abstract

This work consolidates chaotic maps into a contemporary heuristic approach called Chimp Optimization Algorithm (COA). Augmentation of ten chaotic maps to COA forms the hybrid Chaotic COA (CCOA) which generates solutions in search space with enhanced mobility. A bi-level strategy of validating the robustness of the proposed hybrid method is adopted by first benchmarking it on eighteen assorted benchmark test functions and later by performing statistical analysis. The result obtained candidly establishes that merging of chaotic maps (dominantly Chaotic 4 Iterative type-CCOA4) enhances the performance of COA. The inferences congregated from the benchmark functions and statistical analysis facilitates the application of the recommended algorithm to obtain techno-economic solution in reactive power dispatch (RPD) problem which is manifested as a challenging issue in power system operation. The RPD problem is analyzed implementing the proposed approach with series-shunt compensation in a competitive electricity market for secured operation and the proposed Iterative type-CCOA4 reduces the total operating cost by 3.3450 × 103$ with respect to initial operating cost.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:chsofr:v:170:y:2023:i:c:s0960077923002643
    DOI: 10.1016/j.chaos.2023.113363
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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. Ibrahim Attiya & Laith Abualigah & Doaa Elsadek & Samia Allaoua Chelloug & Mohamed Abd Elaziz, 2022. "An Intelligent Chimp Optimizer for Scheduling of IoT Application Tasks in Fog Computing," Mathematics, MDPI, vol. 10(7), pages 1-18, March.
    3. 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.
    4. Wen-Tung Lee & Shih-Cheng Horng & Chi-Fang Lin, 2019. "Application of Ordinal Optimization to Reactive Volt-Ampere Sources Planning Problems," Energies, MDPI, vol. 12(14), pages 1-16, July.
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    Cited by:

    1. 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.

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