Comparative Analysis of Multi Optimization Techniques under Load Variations in Optimal Reactive Power Dispatch

Power System Compensation Schemes encompass a range of strategies, including the integration of distributed generation (DG), flexible AC transmission system (FACTs) devices, power scheduling, capacitor bank placement, and optimal reactive power dispatch (ORPD). ORPD, a current trend, also involves optimizing transformer tap changer settings (TTCS). However, the efficacy of TTCS optimization is questioned due to its potential impact on transmission line parameters. To avoid over-compensation and under-compensation, these schemes necessitate optimization. Evolutionary Programming (EP) and Artificial Immune System (AIS) are widely employed in power system optimization, yet their susceptibility to getting stuck at local optima limits their effectiveness. This hybrid, termed Integrated Accelerated Clonal Evolutionary Programming (ICAEP), exhibits promising results in optimizing ORPD under load variations. The paper introduces the implementation of the accelerated mutation technique in ICAEP, showcasing exceptional performance compared to standalone EP and AIS methods. ICAEP can be adapted for various optimization problems, marking a significant advancement in addressing challenges associated with power system compensation, particularly in optimizing ORPD under varying loads.