Composite system reliability assessment to reduce the curtailment risk using the storage systems

The rapidly changing demand requires more flexible power generation to meet the load. At this point, energy storage systems can play a critical role as a supply-demand balancer. This paper introduces a probabilistic and cost-effective storage integration assessment method to achieve a more reliable power system operation. For this purpose, probabilistic power flow values and the load levels, determined by Monte Carlo simulations, are used to calculate the load curtailments (LCs). After obtaining the riskiest load busses for individual and total LCs, the reliability analysis is performed, and the contingency cases are classified using the k-means clustering algorithm. At the final step of the study, the impacts of the storage system on the system reliability and cost-effectivity are compared to identify the best alternative. The proposed assessment is applied to the IEEERTS-96 test system, and the results are discussed.