An intelligent parallel scheduling method for optimal transmission switching in power systems with batteries

Daily load variation and intermittence of renewable generation may sometime cause transmission congestion in modern power system. As a result, cheap generation cannot be fully dispatched and in extreme condition involuntary load shedding will be enforced. In this paper, an intelligent parallel scheduling method using optimal transmission switching (OTS) and batteries is proposed to mitigate transmission congestion and therefore reduce operational cost. OTS and batteries are embedded in AC optimal power flow (ACOPF) with binary variables used, which is formulated as a mixed integer nonlinear programming (MINLP) problem. To solve the MINLP problem efficiently for multi-hour case, a two-stage optimization scheme is proposed based on developed knowledge. A multi-hour case first is calculated in stage one with OTS disabled to obtain the knowledge of estimated the optimal charging/discharging strategy for batteries. Then, the multi-hour case is decoupled into several subproblems and solved simultaneously in parallel computing. Numerical results on modified IEEE-118 bus system shows the usefulness of the proposed intelligent parallel scheduling method.