Optimal Allocation of Multiple Distributed Generation Using an Enhanced Whale Optimization Algorithm

The integration of distributed generation (DG) into the distribution system is a complex problem that requires an efficient optimization technique. To maximize benefits while minimizing disadvantages, it is crucial to determine optimal locations and capacities for DG installations. Despite the frequent use of recently developed optimization algorithms, their enhanced counterparts are rarely investigated. Moreover, most research relied on peak loads, which do not accurately reflect real-world demand. We proposed using the enhanced whale optimization algorithm (E-WOA) for optimal DG allocation in a radial distribution system, aiming to minimize power and energy losses. This study also developed representative variable load profiles based on real-world consumption data. The backward/forward sweep algorithm is used for load flow analysis, with the IEEE 33-Bus radial distribution system serving as the test system. The optimization was simulated over 100 independent runs, each with 200 iterations and a population of 50. Results demonstrated that E-WOA effectively solves the optimal DG allocation problem, achieving a power loss of 72.785 kW for three DGs at unity power factor, outperforming the standard WOA and several recent algorithms, and matching the performance of hybrid algorithms. Comparison with WOA across different loading scenarios showed that E-WOA consistently produced higher quality solutions at the cost of slower convergence speeds, longer runtimes, and poor scalability. These suggest E-WOA’s limitations in addressing large-scale optimization tasks.