Optimal renewable energy farm and energy storage sizing method for future hybrid power system

This paper proposes a novel optimization method for sizing a renewable energy farm consisting of batteries and ultra-capacitors in a hybrid power system. The combination of ultra-capacitors with batteries is an emerging practice in advanced power electronic systems and a superior configuration scheme is crucial to deploy them effectively with the high penetration of renewable energy sources and critical loads in future power systems. The proposed sizing method fully utilizes the energy generated from the renewable energy farm and limits power fluctuation within the utility grid, improving grid stability and reducing construction and maintenance costs. This two-step optimization process appropriately sizes the renewable energy farm and the energy storage system by using a genetic algorithm (GA). Regional historical data of the solar irradiance, wind speed, and local load profile of Key West, Florida is used to establish the first cost function for optimizing the combination of PV and wind power based on the entire year's daily energy difference between the renewable energy farm and twenty percent of the local load. With the optimized renewable energy farm size, a second cost function is designed to get the optimal combination of battery and ultra-capacitor sizes to smooth the impact caused by the renewable energy farm. A case study of a hybrid power system located in Key West, Florida is presented to verify the advantages of the proposed optimal sizing method.