Transmission network investment with probabilistic security and corrective control

This paper demonstrates that the growth in application of corrective actions to enhance network utilization will require a probabilistic treatment of network security for determining efficient levels of investment in network reinforcement. A Benders decomposition based two-stage probabilistic optimization model for the operational and investment problems is proposed. For selecting relevant contingencies (beyond N-1 criteria), a novel filtering technique for efficient elimination of redundant outages is presented and successfully tested. In 2 numerical examples we compare efficiency of network reinforcement propositions under both deterministic and probabilistic frameworks, while optimizing available preventive and corrective control actions, and in particular focusing on the application of generation reserve in combination with special protection schemes (SPS) for network congestion management purposes. We highlight the inadequacies of the deterministic approach with respect to its inherent inability to optimize accurately the portfolio of pre-fault post-fault actions since the impacts of corrective actions (in the form of SPS, demand response) and occurrence of "non-credible" events require explicit consideration of the likelihood of various outages. We conclude that deterministic approach drives less efficient and potentially more risky system operation that ultimately leads to inefficient network investment.