Dynamic optimal power flow using interior point method and benders decomposition considering active and reactive constraints

This article describes an approach for the dynamic optimal power flow problem using interior point method (IPM) and Benders decomposition considering both active and reactive constraints. An efficient predictor-corrector primal-dual interior-point algorithm is used to solve the linearized dynamic OPF problem. The inclusion of active and reactive security constraints will assure a subsequent feasible solution for the dynamic OPF problem. The dynamic OPF problem is decomposed into a master problem and subproblems for checking the feasibility of the active and reactive constraints. The master problem is formulated and solved without active and reactive constraints to avoid complexity. The obtained dynamic OPF schedule from the master problem is applied to the active and reactive subproblems to minimize the violations. In case the current mix of scheduled units cannot remove the violations, additional constraints will be introduced in the master problem for rescheduling dynamic OPF. The proposed approach has been evaluated on an IEEE 118-bus test system. The results obtained with the proposed approach are presented and compared favorably with results of other stochastic techniques.