Optimal Allocation and Planning of Distributed Power Generation Resources in a Smart Distribution Network Using the Manta Ray Foraging Optimization Algorithm

In this study, optimal allocation and planning of power generation resources as distributed with scheduling capability (DGSC) is presented in a smart environment the objective reducing losses considering enhancing voltage profile performed using manta ray foraging optimization (MRFO) algorithm. The DGSC refers to that can be scheduled their determined based on network requirements. main purpose study schedule intelligent distribution DGSCs conventional enhance its operation. First, done weighted coefficient method then implemented 69-bus network. effect by providing real load minimizing daily energy compared includes (estimated three-level load). simulation results cleared improved operation also profile. obtained confirmed superiority MRFO well-known particle swarm (PSO) allocation. showed increasing number reduces more improves achieved demonstrated loss less than load. other words, any error forecasting demand leads non-optimal operating point losses.