Stochastic Optimal Transmission Switching Considering Voltage Stability Index with Distributed Generation Uncertainty

Optimal Transmission Switching (OTS) is a strategic way of removing or connecting a transmission line to alter the network topology to optimize an objective such as cost reduction and power loss minimization. A deterministic optimization model and a DCOTS solution were utilized in earlier investigations of OTS. However, the uncertainty induced by the increasing penetration of renewable energy sources in the system must not be neglected, while inaccuracy lies in the DCOTS solution. Also, the voltage collapse point of the transmission line must be considered without sacrificing the system’s reliability. Hence, this research study aims to assess the impact of reducing the Expected Total Generation Cost (ETGC) using Stochastic AC Optimal Transmission Switching on the reliability and voltage stability of the power system with distributed generation uncertainty. The result of the study shows that Stochastic ACOTS reduced the expected generation cost by 2.19% for low demand, 7.03% for high demand, and 7.15% for very-high demand. Furthermore, in terms of the voltage stability index-LSI, ETGC savings due to OTS action have a low positive link with LSImax reduction. Then, the result shows that removing the top candidate line will not compromise the line stability index since the maximum LSI for low demand is 0.534, 0.696 for high demand, and 0.743 for very-high demand. Lastly, the proposed three-stage Stochastic ACOTS that ranks the line for removal shows that removing top candidate lines for all power demand levels does not produce immense Expected Demand Not Supplied (EDNS), which reveals the system’s reliability is not compromised. The optimization framework used in this study is the Python Optimization Model (Pyomo) while utilizing the open-source software IPOPT as the solver for non-linear problems.