Joint optimal sizing and placement of renewable distributed generation and energy storage for energy loss minimization

Large integration of renewable distributed generation (RDG) and energy storage (ES) in distribution networks provides an opportunity for energy loss minimization. This paper proposes a method for joint optimum allocation of RDG and distributed ES for energy loss minimization. The main contribution of the paper is formulation of probabilistic generation model and ES model to perform a combined optimization. Also, it presents integration of generation model, storage model, and load model into an optimal power flow to obtain loss minimization. A highly competitive algorithm called Grey Wolf Optimizer (GWO) is implemented to solve the nonlinear constrained optimization. The results are also compared with other heuristic algorithms, i.e., Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Symbiotic Organisms Search Algorithm (SOS) and Firefly Algorithm (FFA). Two cases studies for joint optimal sizing and placement of RDG (i.e., solar RDG-ES and wind RDG-ES) are presented. Here, a 34-bus test system is used and optimizations are carried out in M ATLAB
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