Abstract ▼ AI-Helper

This paper presents an algorithm for determining an optimum size of Energy Storage System (ESS) via the principles of exhaustive search for the purpose of local-level load shifting including peak shaving (PS) and load leveling (LL) operations in the electric power system. An exhaustive search method...

This paper presents an algorithm for determining an optimum size of Energy Storage System (ESS) via the principles of exhaustive search for the purpose of local-level load shifting including peak shaving (PS) and load leveling (LL) operations in the electric power system. An exhaustive search method is employed to perform the ESS capacity (QESS) and power (PESS) optimization. The sizing process involves two distinct steps. In the first step the search for a feasible ESS parameter space in which the requirements of PS and LL are fulfilled and in the second step the search for an optimum point in the feasible space with respect to the cost benefit. Finally, the search is expanded to find a set of storage capacity, QESS and peak power limits, Plimit's for each month, in order to perform the load shifting throughout a one year. To validate the ESS size optimization, an appropriate model is created for time-domain simulations. The model consists of variable load, a simple state-space ESS model and a rule-based controller which operates the ESS using a set of rules. A number of time-domain simulations were performed to validate the correctness of the ESS size optimization. It appears that the proposed optimization algorithm produces results that meet the requirements in the peak shaving and load leveling operations.