INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM

Flexible AC Transmission system (FACTS) controllers are widely accepted worldwide to provide benefits in increasing power transfer capability and maximizeing the use of the existing transmission networks. A new generation of FACTS controllers, particularly the Interline Power Flow Controller (IPFC) based on voltage source converter (VSC) provides fast power flow control flexibility. The IPFC with its unique capability of power flow management is significantly extended to control power flows of multi-lines or a sub network. Generally IPFC employs two or more VSCs connected together with DC links and each converter provides series compensation for the selected line of the transmission system. Optimal power flow is an important factor in power system operation, planning and control. In this thesis, the mathematical model of IPFC together with the modified Newton-Raphson method for power flow is used to derive the optimal parameters (the magnitude and voltage angles) of VSCs of IPFC. The optimal parameters are derived to minimize the transmission line losses using three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA). The proposed methods are applied using MATLAB 7.6 and tested on IEEE 14-bus and 30-bus bench mark power systems. The optimal parameters of IPFC, the voltage profile and the transmission line losses of the bench mark power systems are derived from the simulations. The simulation results obtained with PSO technique are compared with those obtained by other two optimization techniques. The thesis also covers the basic principles and operation of IPFC, the modified Newton-Raphson power flow method and an overview of the three intelligent optimization techniques used in this thesis. The results prove the efficacy of the three intelligent methods for the optimization of IPFC parameters and minimization of transmission line losses.