Stochastic optimal transmission Switching: A novel approach to enhance power grid security margins through vulnerability mitigation under renewables uncertainties

In this paper, a stochastic optimal transmission switching (SOTS) model is developed considering the uncertainty of load, wind power and photovoltaic generation, while minimizing the grid vulnerability. Scenario reduction technique is used for alleviating computational burden of the developed SOTS model. A three-step procedure, named the vulnerability-oriented SOTS (VO-SOTS), is proposed to consider the set of critical transmission lines, i. e., lines whose outage imposes the largest load curtailment. Moreover, to control the negative impacts of the uncertainties, conditional value at risk (CVaR) is used as the risk measure. The proposed VO-SOTS model is formulated as a mixed integer non-linear programming optimization problem and solved using GAMS optimization package. Also, the VO-SOTS model is implemented on the IEEE 118-bus, IEEE 300-bus, and large-scale IEEE 2869-bus standard test systems. Simulation results for these cases show that considering the set of critical lines allows the proposed VO-SOTS model to reduce generation costs while effectively minimizing system vulnerability and risk. In addition, it is shown through extensive case studies that switching off a line based on the proposed three-step VO-SOTS does not increase the grid's exposure to vulnerability, in contrast to the conventional OTS.

Automated summary

This research presents a stochastic optimal transmission switching (SOTS) model that considers uncertainty to minimize grid vulnerability and risk. By using scenario reduction technique, the computational burden is alleviated in the developed model. The proposed VO-SOTS model reduces generation costs, effectively minimizes system vulnerability and risk by considering the set of critical transmission lines.