Control variable selection for the corrective control of voltages and reactive power flows

Abstract

A sequential search strategy for the control variable subset selection, used for optimal power system voltage control and reactive power management, is presented in this paper. The objective of the presented selection method is to eliminate the redundant control variables which have small impact on the reactive power optimization (RPO) objective function and/or constraints. Selected control variable set is used for correcting the power system state in which the operational limits are violated. The candidate control variables are evaluated based not just on their impact on the out-of-bound variables, but also on the overall power system state. Sensitivity analysis, based on power flow calculation, was conducted for each candidate control variable and the results were used as an input data for the sequential search method. Considering the RPO is inherently a mixed integer nonlinear programming (MINLP) problem, the genetic algorithm (GA) was used for solving the optimization problem. The efficiency of the presented method was tested on IEEE test systems. Simulation results are presented for IEEE 118-bus test system.