Joint optimal allocation of battery storage and hybrid renewable distributed generation

Large scale integration of grid scale energy storage has changed the scenario of distributed generation. Distributed energy storage can be used for energy loss minimization. Hybrid renewable distributed generation (HRDG) is employed for energy reliable operation of the system. This paper proposes a methodology of optimal allocation of energy storage for energy loss minimization in coordination with HRDG. Probabilistic generation models are developed for solar distributed generation (SDG) and wind distributed generation (WDG). Generation model and load model is suitably integrated with storage model and optimal power flow model. The proposed nonlinear constrained optimization problem is solved by a robust and competitive algorithm called Grey Wolf Optimizer (GWO) to obtain energy loss minimization. The results are compared with genetic algorithm (GA), particle swarm optimization(PSO), symbiotic organisms search (SOS) and firefly algorithm(FFA). Significant loss minimization is obtained by the proposed joint optimal allocation methodology when solved with GWO optimization.