A hybrid model for optimal power flow incorporating FACTS devices

Abstract

Optimal power flow (OPF) is one among the most important algorithms available to an electric utility for generating least cost generation patterns in a power system satisfying transmission and operational constraints. In day to day life, the forecasted loads used in classical OPF algorithms are increasing with time and are also not completely free from errors. Increase in load demands leads to overloading of the transmission lines and forecasted errors cause loss of optimality. So classical optimal power flow algorithms may not be able to provide optimal solutions and they are limited to fixed type of cost characteristic curves and cannot handle frequent increase and variation in load demands. In this paper, a new hybrid model for OPF incorporating FACTS devices has been proposed to overcome the above said difficulties. In the proposed model, load demands, generation outputs and cost of generation are treated as fuzzy variables. In the first stage fuzzy dynamic programming has been used to determine a set of feasible generation patterns. In the second stage a DC power flow algorithm has been used to determine a set of valid sub-optimal generation patterns satisfying transmission and operational constraints. Finally in the third stage over loading of transmission lines can be eliminated by installing FACTS devices in the system. To verify the validity of the proposed model a 5 generator and 10-bus test system with and without modification has been used. It was found that the solutions obtained are quite encouraging and suitable for the modern deregulated environment.