Optimal Reactive Power Control using Artificial Intelligence Methods

Abstract

This thesis focuses in studying the dynamic response of reactive power in the Voltage Source Converters High-Voltage Direct Current (VSC- HVDC) system. In order to get better and faster response, reactive power values should be controlled. Optimizing the parameters of PI (proportional & integration) controller is necessary to control these values. Four meta-heuristic optimization methods which are Gravitational Search Algorithm (GSA), Sine Cosine algorithm (SCA), Particle Swarm Optimization (PSO) and Modified PSO are used to get optimal parameters of PI controller. These algorithms have an efficient global Search capability. Using MATLAB™ Simulink, model of VSC- HVDC system is presented. This system is exposed to different disturbances for checking its dynamic response of reactive power. Simulation results show that the dynamic response is improved with the optimal gains than the default ones. At the end of this thesis, it is noted that the response of reactive power is improved with using optimized parameters. The Modified PSO presented the best response among the other proposed methods as it is based on mathematical modification to update the value of parameters in each iteration. The mathematical modification is based on calculating the error in the objective value between two successive iterations in order to obtain better values of parameters.