Improving the resilience of large-scale power systems using distributed static series compensators

Abstract

Natural disasters such as hurricanes can cause severe damages at the transmission level, resulting in widespread power outages and renewable energy curtailment. To reduce such power outages and renewable curtailment, this study takes advantage of the power flow control capability of distributed static series compensators (DSSC) and proposes a model to optimally deploy DSSC in face of natural disasters. The model is based on stochastic optimization and can determine the optimal locations and quantities of the DSSC modules in power systems considering transmission contingencies. With a high computational efficiency, the model can meet the time frame requirement for DSSC redeployment after natural disasters to improve the resilience of large-scale, real-world power systems. The model was implemented on a modified Texas 2000-bus test system under different conditions, and results show that the proposed model can optimally allocate DSSC to mitigate transmission congestions in both normal operations and emergent situations after natural disasters. By optimally redeploying DSSC using the proposed model after natural disasters, load shedding and renewable energy curtailment can be reduced up to 100% and 90%, respectively, improving the resilience of the power system.