Hybrid metaheuristic optimization-based solution for reactive power dispatch in dynamic power systems

Optimal Reactive Power Dispatch (ORPD) is essential for maintaining voltage stability and minimizing power losses in dynamic power systems. However, frequent load changes and uncertain generation sources, such as photovoltaics (PV) and wind turbines (WT), increase the complexity of the ORPD problem and pose challenges for an optimal solution. Addressing this research gap, this research study introduces a novel hybrid metaheuristic optimization technique for the optimal solution of ORPD in dynamic power systems. The proposed hybrid technique combines the Educational Competition Optimizer and the Dhole Optimization Algorithm (ECO-DOA) to optimally solve the reactive dispatch problem. The hybridization of algorithms leverages the strengths of both the ECO and DOA algorithms, aiming to enhance the efficiency, reliability, and convergence of the distribution network by reducing active power losses and voltage fluctuations while satisfying the system’s power flow constraints. The proposed ORPD approach and the solution method are verified on the IEEE 30-, 57-, and 118-bus test systems. The robustness and efficiency of the proposed ECO-DOA algorithm for solving the ORPD problem are evaluated by comparing it with other well-established metaheuristic optimization methods using the same system data, control variables, and constraints. Simulation results demonstrate that the ECO-DOA algorithm achieves higher accuracy and faster convergence than existing methods, providing reliable solutions to the ORPD problem while ensuring the system’s sustainability. To minimize power loss, the proposed hybrid ECO-DOA method achieved an improvement of up to 11.12% over other methods. For the 118-bus network, the algorithm achieved improvements of up to 10% in minimizing voltage deviation compared to other methods. Statistical analysis was also conducted over 30 independent trials for each scenario. The results demonstrate that the proposed algorithm achieves better solutions for minimizing power loss and voltage deviation compared to other methods.