Discrete reactive power optimization based on interior point filter algorithm and complementarity theory

This paper solves the problem of power system reactive power optimization with discrete variables based on interior point filter algorithm and complementarity theory which aims to deal with discrete variables. Create nonlinear programming model for reactive power optimization of power system with complementarity constraints by means of complementarity theory and use smooth processing, realize the unified solution of continuous variables and discrete variables; adopt the interior point filter algorithm to solve the model. The interior point filter algorithm is based on the primal-dual interior-point algorithm and introduces the updatable filter set, so it can avoid the non convergence problem due to the oscillation caused by the contradiction between the decrease of objective function and the restriction of constraints, and it has the global convergence. Take IEEE30 bus and IEEE118 bus test system as simulation example, the calculation results show that the model based on complementarity theory together with the solution based on interior point filter algorithm can effectively deal with the discrete variables of reactive power optimization of power system, realize to solve the discrete variables exactly; the method has the property of high calculation efficiency, coordinate the computing time and calculation precision, and has a great prospect of engineering application.