A Scenario-Driven Planning for Transmission network Expansion to Enhance Available Transfer Capability

This paper describes a methodology for transmission expansion planning (TEP) which improves available transfer capability. Three objective functions are considered: investment cost (IC), operation cost (OC) and available transfer capability (ATC). Load uncertainty is modeled using Monte Carlo simulation (MCS). The presented scenario-driven planning forms a bilevel optimization problem in which in the first stage the planner minimizes the objective function subject to the prevailing constraints of the power system, while in the second stage ATC is calculated. Second level of the optimization problem is substituted by its Karush-Kuhn-Tucker (KKT) conditions which result in a one-level optimization problem that can be solved by efficient available solvers. The proposed framework is applied to IEEE 24-bus reliability test system (RTS). Results obtained from case study are reported and discussed. These results show the effectiveness of the presented model in order to improve the ATC.