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Fuzzy-Based Fitness–Distance Balance Snow Ablation Optimizer Algorithm for Optimal Generation Planning in Power Systems

Author

Listed:
  • Muhammet Demirbas

    (Department of Electrical and Energy, Tosya Vocational School, Kastamonu University, 37302 Kastamonu, Turkey)

  • Serhat Duman

    (Department of Electrical Engineering, Faculty of Engineering and Natural Sciences, Bandirma Onyedi Eylul University, 10200 Bandirma, Turkey)

  • Burcin Ozkaya

    (Department of Electrical Engineering, Faculty of Engineering and Natural Sciences, Bandirma Onyedi Eylul University, 10200 Bandirma, Turkey)

  • Yunus Balci

    (Department of Electrical Engineering, Faculty of Engineering and Natural Sciences, Bandirma Onyedi Eylul University, 10200 Bandirma, Turkey)

  • Deniz Ersoy

    (Postgraduate Education Institute, Bandirma Onyedi Eylül University, 10200 Bandirma, Turkey)

  • M. Kenan Döşoğlu

    (Department of Electrical and Electronics Engineering, Faculty of Engineering, Duzce University, 81620 Duzce, Turkey)

  • Ugur Guvenc

    (Department of Electrical and Electronics Engineering, Faculty of Engineering, Duzce University, 81620 Duzce, Turkey)

  • Bekir Emre Altun

    (Department of Electrical and Energy, Amasya Technical Sciences Vocational School, Amasya University, 05000 Amasya, Turkey)

  • Hasan Uzel

    (Department of Electrical and Energy, Akdagmadeni Vocational School, Yozgat Bozok University, 66100 Yozgat, Turkey)

  • Enes Kaymaz

    (Department of Electrical and Electronics Engineering, Faculty of Engineering, Duzce University, 81620 Duzce, Turkey)

Abstract

Economic dispatch (ED) is one of the most important problems in terms of energy planning, management, and operation in power systems. This study presents a snow ablation optimizer (SAO) algorithm developed with the fuzzy-based fitness–distance balance (FFDB) method for solving ED problems in small-, medium- and large-scale electric power systems and determining the optimal operating values of fossil fuel thermal generation units. The FFDB-based SAO algorithm (FFDBSAO) controls early convergence problems through balancing exploration–exploitation and improves the solving of high-dimensional optimization problems. In the light of extensive experimental studies conducted on CEC2020, CEC2022, and classical benchmark test functions, the FFDBSAO2 algorithm has shown superior performance against its competitors. Wilcoxon and Friedman’s statistical analysis results confirm the performance and efficiency of the algorithm. Moreover, the proposed algorithm significantly reduces total fuel cost by optimizing fossil fuel thermal generation units. According to the results, the scalability and robustness of the algorithm make it a valuable tool for solving large-scale optimization problems in the planning of electric power systems.

Suggested Citation

  • Muhammet Demirbas & Serhat Duman & Burcin Ozkaya & Yunus Balci & Deniz Ersoy & M. Kenan Döşoğlu & Ugur Guvenc & Bekir Emre Altun & Hasan Uzel & Enes Kaymaz, 2025. "Fuzzy-Based Fitness–Distance Balance Snow Ablation Optimizer Algorithm for Optimal Generation Planning in Power Systems," Energies, MDPI, vol. 18(12), pages 1-41, June.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:12:p:3048-:d:1675048
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    References listed on IDEAS

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