Abstract

The increasing demand for electricity presents substantial challenges in power system planning, particularly optimizing the Optimal Power Flow (OPF) problem. The OPF problem entails establishing the best settings for control variables in a power system to reduce objectives such as generating cost and transmission losses while meeting operational restrictions. This research introduces an upgraded RIME optimization algorithm (WDNMRIME) to address these challenges. WDNMRIME integrates a dual-weight decay mechanism and the Nelder-Mead simplex (NMs), enhancing population diversity and mitigating the risk of local optima. Additionally, NMs expedites convergence by refining the population's optimal solution set. Experimental validation on the IEEE 30-bus test system demonstrates that WDNMRIME achieves a generation cost of $806.00298 per hour and reduces total power loss from 1.43 MW to 1.39 MW. These results surpass the performance of the original RIME algorithm, showcasing a 15% improvement in convergence speed. The algorithm effectively optimizes multiple concurrent Flexible Alternating Current Transmission Systems (FACTS) devices, even under the uncertain nature of wind energy resources modeled using the Weibull probability density function. These findings highlight WDNMRIME's significant contribution to improving OPF optimization in dynamic power systems.

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