A Probabilistic Renewable Energy Allocation Applying Metaheuristics Optimization Methodologies

The optimal installation and size of renewable distributed generation (RDG) in a distribution network has always been challenging for utilities and consumers, considering environmental, economic, and technological factors in order to extract the greatest possible benefits, especially in remote and small areas. In order to maximize their potential benefits, this has prompted the investigation of several techniques for determining their optimal location and size, which minimizes system losses, improves the voltage profile, and enhances system dependability and stability. In this work, an objective function is developed to optimally size two types of RDG using two modern meta-heuristic algorithms for optimal loss reduction in radial power distribution networks. Grey Wolf Optimization (GWO) and Whale Optimization Algorithms (WOA) are tested to minimize the power losses and enhancing the voltage profile of the standard IEEE 69 bus system. The study compares both algorithms for different scenarios of various RDG penetration levels. The obtained results clarifies the superiority of GWO algorithm over WOA in achieving a global optimal solution for minimizing power loss with a small sized RDG.