Optimization of hybrid energy storage system providing power curve smoothening in grid scale

Abstract

Efficient supply of electric energy, maintaining power quality, and addressing intermittency of renewable energy and unpredictable demand fluctuations are challenges of a modern power grid. An individual energy storage technology seldom provides all the desired characteristics expected. A Hybrid Energy Storage System (HESS) including different types of energy storage systems can address these challenges. In this work a new formulation and algorithm was developed that optimally designs a grid-scale HESS for desired performances such as peak load shaving and power demand curve smoothening at the least capital cost. The proposed HESS comprised of a combination of Lithium Ion batteries, Flywheels, and Ultracapacitor based Energy Storage Systems. Real and synthetic power demand dataset representing different types of demand fluctuations were used in the analysis. The proposed formulation and algorithm was able to optimally size HESS such that it costs the least while performing in the desired manner.