Application of Battery Energy Storage for network vulnerability mitigation

Abstract

To comply with modern power system regulatory standards, new security strategies and resiliency efforts are required. This work proposes application of Battery Energy Storage (BES) for network vulnerability mitigation. First, a novel disturbance-based vulnerability index is introduced to quantify the robustness of the network. The network vulnerability index (NVI) is a function of the current power flow variables, related distances from security limits and those of post contingency situations, caused by lines and generators outages. Next, Non dominated Sorting Genetic Algorithm II (NSGA-II) is coded on a computing cluster, taking advantage of a massively distributed environment, to optimally allocate BES units while minimizing total size of BES and NVI simultaneously. Study results on IEEE Reliability Test System 1996 (RTS96) prove the effectiveness of NVI to measure the level of network vulnerability. Moreover, it is shown that BES units, if optimally sited and sized, can contribute to the grid resiliency.