Optimal utilization of large-scale battery storage systems for microgrid applications

The integration of energy storage system (ESS) provides various benefits to microgrids such as mitigating renewable generation variability and reducing operation cost. One challenge in designing a microgrid system is determining the optimal size of ESS. Sizing of ESS has become more complex due to the independent power and energy ratings inherent in battery storage systems (BSS). Sizing a BSS for both required power output and energy storage capacity requires an in-depth analysis to produce both optimal scheduling capabilities and minimum investment costs. This thesis proposed a framework to determine the optimal ratings of BSS based on an optimal scheduling analysis and cost-benefit analysis for a set of given constraints both in the islanded and grid connected microgrid expansion applications. Mixed integer linear programing (MILP) algorithm was developed to solve the optimal sizing and scheduling problem to minimize the total cost and increase microgrid reliability. The viability and effectiveness of the proposed framework was validated by numerical simulations