Solution of interval reactive power optimization using genetic algorithm

Abstract

Reactive power optimization is generally used to design an optimal profile of voltage and reactive power of power systems in steady state for deterministic sets of demand load and generation values, and it is a significant procedure in voltage control. However, the input data of power system is actually uncertain in practice, which makes reactive power optimization an uncertain nonlinear programming, and it is not solved properly at present. To address this problem, the input data is considered as interval and reactive power optimization incorporating interval uncertainties is proposed to model this problem. In order to solve this model, genetic algorithm is employed as the solution algorithm, where reliable power flow calculation is used to judge the constraints of the model. The IEEE14 system is tested and analyzed to demonstrate the effectiveness of the proposed method, especially in comparison to previously proposed chance constrained programming.