A Large-scale Reactive Power Optimization Method Based on Gaussian Penalty Function With Discrete Control Variables

Reactive power optimization with discrete control variables can be formulated as a mixed-integer nonlinear programming problem,which is a typical NP–hard problem in mathematics.This paper proposed a Gaussian penalty function based approach to handle discrete variables,in which the discrete variables were relaxed to continuous variables.The properties of the optimization model with Gaussian penalty function,as well as how it could be affected by parameters,were discussed.Then a practical algorithm combining nonlinear interior point method and a heuristic parameters tuning strategy was developed to solve the optimization problem.Finally,numerical experiments were taken on different systems,including IEEE standard systems and several real power systems with varying scales,to verify the robustness and practicability of the proposed method.