Optimal Economic Dispatch Using Mayfly Optimization Algorithm in Sulbagsel Electricity System with Integrated Renewable Energy Sources

Rini Nur Hasanah, Imam Robandi*, Syafaruddin, Vita lystianingrum, Harus Laksana Guntur, Muhammad Ruswandi Djalal, Mohamad Almas Prakasa, Waseda Himawari

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This study focuses on optimizing generation costs for thermal power plants in the Southern Sulawesi (Sulbagsel) electricity system by incorporating Renewable Energy Sources (RESs). The Improved Mayfly Algorithm (IMA), inspired by the mating and flight behaviors of adult mayflies and enhanced with Exponent Decreasing Inertia Weight (EDIW) to adjust inertia variations, is applied to minimize generation costs. The effectiveness of the proposed IMA is evaluated through comparisons with other methods, such as the Quadratic Time Optimization (QTO) and the standard MA. Statistical analysis of the benchmarking results demonstrates that IMA outperforms comparable other algorithms. For the first case, mid-day peak load, the optimization results show that QTO reduces costs by 24.24%, MA by 24.25%, and the proposed IMA by 24.28%. In the second case, nighttime peak load, the cost reductions achieved are 25.96% for QTO, 26.28% for MA, and 26.72% for IMA.

Original languageEnglish
Pages (from-to)894-903
Number of pages10
JournalInternational Journal of Intelligent Engineering and Systems
Volume18
Issue number1
DOIs
Publication statusPublished - 2025

Keywords

  • Cost
  • Economic dispatch
  • Improved mayfly algorithm
  • Sulbagsel system
  • Swarm intelligence

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