POWER QUALITY IMPROVEMENT IN STANDALONE SEIG SYSTEM INCORPORATING MODERN CONTROL ALGORITHMS

Abstract

This thesis presents an intelligent control strategy for an isolated hybrid PV–Wind Self-Excited Induction Generator (SEIG) microgrid aimed at enhancing power quality, frequency stability, and dynamic performance under nonlinear loading conditions. The proposed system integrates a Solar Photovoltaic (PV) array, Wind Energy Conversion System (WECS), Battery Energy Storage System (BESS), and DSTATCOM to ensure reliable and continuous power supply in remote standalone applications. Due to the intermittent nature of renewable energy sources and the nonlinear characteristics of SEIG, isolated microgrids experience severe voltage fluctuations, frequency deviations, reactive power imbalance, and harmonic distortion. To overcome these challenges, a Dual Third-Order Generalized Integrator Phase-Locked Loop (DTOGI PLL) based synchronisation technique is employed for accurate extraction of the fundamental positive-sequence component under distorted operating conditions. In addition, an Adaptive Neuro-Fuzzy Inference System (ANFIS) based intelligent controller is implemented for adaptive frequency regulation and improved transient response. The coordinated control of DSTATCOM and BESS provides effective reactive power compensation, harmonic mitigation, DC-link voltage regulation, and power balancing. The complete system is modelled and simulated in MATLAB/Simulink under steady-state and dynamic operating conditions. Simulation results demonstrate improved voltage stability, enhanced frequency regulation, reduced total harmonic distortion within IEEE-1547 limits, and superior overall power quality performance of the proposed hybrid microgrid system.