A primal–dual penalty-interior-point method for solving the reactive optimal power flow problem with discrete control variables

The Optimal Reactive Power Flow (ORPF) problem has been used as an important computational tool for power system planning and operation. Its mixed-discrete version (DORPF) is formulated as a non-convex, non-linear optimization problem with discrete and continuous variables, which is aimed at minimizing the transmission losses while meeting the power demand and enforcing operational and physical limits of the system. Although the DORPF problem has been solved by a myriad of methods, some of them present regularization problems associated with poor matrix-conditioning in the optimal solution, some do not provide for rapid infeasibility detection and some do not provide effective ways for handling the discrete nature of the control variables. Although some of these complicating issues have been tackled separately in the literature by various studies, a method that addresses all these issues has not yet been proposed for solving the DORPF problem. In this paper, an integration of optimization approaches is proposed for handling all such complicating issues. The basis of this approach is a primal–dual penalty-interior-point method, which integrates the good properties of penalty methods (e.g. regularization effects on the constraints and rapid infeasibility detection) and interior-point methods (e.g. scalability and good convergence behavior), without suffering from their disadvantages. In the proposed approach, this method is integrated with a sinusoidal penalty function method for handling the discrete nature of the control variables of the DORPF problem, together with a specific inertia correction strategy designed to avoid local maximizers associated with such a penalty function. Numerical tests carried out with the IEEE 30-, 57-, 118- and 300-bus systems focus on showing that all the complicating issues have been addressed by the proposed method. Comparisons with the results obtained by interior-point methods are also provided. • An integration of approaches is proposed for handling mixed-discrete optimization problems. • A Primal–dual penalty-interior-point method is integrated with a sinusoidal penalty method and an inertia correction strategy. • The approach handles discrete variables, poor matrix-conditioning and has rapid infeasibility detection. • The approach is applied to solving a mixed-Discrete version of the Optimal Reactive Power Flow problem. • Systems up to 300 buses are solved and comparisons with interior-point methods are provided.