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

Muhammet Demirbas (), Serhat Duman, Burcin Ozkaya, Yunus Balci, Deniz Ersoy, M. Kenan Döşoğlu, Ugur Guvenc, Bekir Emre Altun, Hasan Uzel and Enes Kaymaz
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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

Energies, 2025, vol. 18, issue 12, 1-41

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.

Keywords: fuzzy fitness–distance balance method; optimization; snow ablation optimizer; economic dispatch; power system planning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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