Energy loss minimization through peak shaving using energy storage

This paper presents an optimal placement methodology of energy storage to improve energy loss minimization through peak shaving in the presence of renewable distributed generation. Storage sizing is modelled by considering the load profile and desired peak shaving. This storage is suitably divided into multiple storage units and optimally allocated at multiple sites with suitable charge discharge strategy. Thus the peak shaving for maximum loss reduction is explored here. Renewable distributed generation (RDG) is modelled based on the seasonal variations of renewable resources e.g., solar or wind and these RDGs are placed at suitable locations. A high-performance Grey Wolf Optimization (GWO) algorithm is applied to the proposed methodology. The results are compared with the well-known genetic algorithm. The proposed methodology is illustrated by various case studies on a 34-bus test system. Significant loss minimization is obtained by optimal location of multiple energy storage units through peak shaving.