Static Var Generators (SVG) have been widely adopted in renewable power systems to improve voltage stability. The capacity and location of SVG installation in a renewable power system both impact the improvement effect. In this paper, we investigate the optimal SVG configuration that cost-effectively improves the voltage stability of power systems with high renewable energy penetration. First, recognizing the short-circuit ratio as a key and simple indicator of system voltage stability levels, a multi-objective optimization model is established, with objectives of improving the short-circuit ratio of renewable generators and minimizing the overall SVG installation cost. Then, we propose a modified NSGA-II algorithm to solve this model, thus obtaining the number and location for installing the SVGs in a power system. Experiments conducted on the SG118 system, which integrates renewable energy, validate the effectiveness of our proposed method. Our work presents power system operators with an effective measure to maintain the voltage stability of power systems with high penetrations of renewable energy.

With the increasing deployment of electric vehicles, transportation networks have been more closely coupled with power networks via charging stations. The functionality of the coupled system can be significantly damaged by extreme events, like man-made attacks and natural disasters. In this paper, we propose a metric to quantify network resilience and a method to dispatch electric vehicles to suitable charging stations in power grid-coupled transportation networks after being disrupted by extreme events. The emergent dispatching problem is expressed by a linear programming model which is computationally tractable. The optimization variables are binary and represent the charging stations selected for electric vehicles. The optimization objective is to minimize the sum of queue time and travel time of electric vehicles. Simulation results conducted on a synthesized power-transportation coupling system that is composed by a modified real-world transportation network and the IEEE 39 Bus test case demonstrate the efficacy of the proposed method in enhancing network resilience. Our work contributes to the advancement of more resilient modern transportation networks under extreme events.