Rini Nur Hasanah, Imam Robandi, Syafaruddin, Vita lystianingrum, Harus Laksana Guntur, Muhammad Ruswandi Djalal, Mohamad Almas Prakasa, Waseda Himawari
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. © (2025), (Intelligent Network and Systems Society). All rights reserved.
Department of Electrical Engineering, Universitas Brawijaya, Malang, 65145, Indonesia; Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia; Department of Electrical Engineering, Universitas Hasanuddin, Makassar, 90245, Indonesia; Department of Mechanical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia
