Optimal Allocation and Sizing of PV Generation Units in Distribution Networks via the Generalized Normal Distribution Optimization Approach

The problem of optimal siting and dimensioning photovoltaic (PV) generators in medium-voltage distribution networks is addressed this research from the perspective combinatorial optimization. exact mixed-integer programming (MINLP) model solved using a master–slave (MS) optimization approach. In master stage, generalized normal (GNDO) with discrete–continuous codification used to represent locations sizes PV generators. slave generalization backward/forward power method, known as successive approximation flow adopted. Numerical simulations IEEE 33-bus 69-bus systems demonstrated that GNDO approach most efficient method for solving MINLP model, it obtained better results than genetic algorithm, vortex-search Newton-metaheuristic optimizer, solution General Algebraic Modeling System (GAMS) software BONMIN solver. Simulations showed that, on average, proposed MS optimizer reduced total annual operative costs by approximately 27% both test feeders when compared reference case. addition, variations renewable generation availability 30% ahead, positive reductions respect case were obtained.