Hybrid Particle Swarm Optimization–Simulated Annealing OPF for Lombok Generation Cost Reduction - MUHAMMAD RIVALDI HARJIAN; AGUNG BUDI MULJONO; AKBAR TAWAQQAL; RAJA RESKI EKA PUTRA (Institut Teknologi Nasional, Bandung, 2025)
This study proposes the application of Optimal Power Flow (OPF) in the Lombok Electricity System consisting of 19 buses and 7 generating units, with the main objective of reducing production costs under peak load conditions. The method used is a hybrid optimization method that combines two methods, namely the Particle Swarm Optimization and Simulated Annealing algorithms. Particle Swarm Optimization and Simulated Annealing (PSO–SA) method. Combining PSO and SA algorithms can improve the weaknesses of PSO with its jumping feature. In other words, the use of the PSO-SA algorithm is more effective than the PSO method. The simulation results show a generation cost of USD 31,158. The total generated power is 193,736 MW, which is equivalent to a total load of 193.34 MW. In addition, the voltage profile of all buses is at 0.95–1.05 pu and the power flow of all lines is below the thermal capacity. This finding confirms that the use of the PSO–SA algorithm effectively reduces operating costs without violating the system's operating constraints.