Particle Swarm Optimization Based Reactive Power Planning for Voltage Stability Improvement

With the increase in power demand and limited power sources has caused the system to operate at its maximum capacity and this can cause the deterioration of the quality of service, with cut-offs power supply like to the deterioration of the equipment. Therefore, the ability of determine voltage stability before voltage collapse has received a great attention due to the complexity of power system. This paper proposes a particle swarm optimization method for solving optimal reactive power planning (ORPP) problem using Thyristor Controlled Series Compensator (TCSC). The proposed PSO have been applied for the ORPP problem to improve the system voltage stability by minimizing the fast voltage stability index (FVSI) and to minimize the investment cost of TCSC devices and the system voltage deviations, satisfying various constraints of power flow equation, generator voltage limits, TCSC's reactance limits, transformer tap changer limits, and transmission line limits. The Fast Voltage Stability Index (FVSI) are used to identify the stressed lines which will receive the FACTS devices (TCSC). The proposed method has been examined and tested on the Algerian electric power system 114-bus and the obtained results are compared with two other methods, namely, Genetic Algorithm (GA), interior point method (IPM). The result comparisons demonstrate the potential of the proposed approach and show its effectiveness and robustness to solve the ORPP problem. Therefore, the proposed PSO can be a promising solution method for dealing the ORPP problem.