Wide Area Voltage Stability Assessment of DFIG Based Wind Farm Integrated Large Power System

Abstract

With rising global energy demand, transmission lines are operated at their limits, causing electrical grids to operate under extreme voltage instability conditions. To meet the increased load-demand and the forced tendency across the globe to tilt towards even more renewable generation, solar and wind farms are integrated with increased size and capacity. This uncontrolled natural power injection may again affect the system s voltage stability. To avoid blackouts and to achieve the maximum voltage stability of power systems, operators need to do effective real-time grid monitoring and control at load terminals. Load models are important in the analysis of voltage stability, and accurate load models are useful in analysing the voltage stability conditions. As more fluctuating and unpredictable wind energy enters the power grid, the complexity of real-time voltage stability assessment and control increases. It should be noted that doubly-fed induction generator (DFIG) is a type of wind-energy machinery that can operate in both sub-synchronous and super-synchronous speed regions and extract the maximum available wind power. Real-time analysis is a challenging task when a DFIG-based wind farm is integrated into a WAMS-based large power system with GPS-aided phasor-measurement-unit (PMU) technology. This real-time wide-area monitoring and smart-automation is an innovative technology for measuring load voltage magnitude, phase angle, and frequency variations in a large wind power system. This thesis presents the real-time voltage stability monitoring and estimation through the use of linear, nonlinear, and dynamic load models in the presence of a DFIG-based wind-farm in a power network using PMU recorded data. The Local Thevenin Index (LTI) is a novel technique in scientific research to assess the voltage stability of power systems integrated with renewable energy. From the standpoint of grid voltage stability, this index aids in determining the best location for integrating the wind farm into the existing power system