Wind Farm Modeling and Simulation with Doubly-Fed Induction Generator Implementation

This project involves comprehensive wind farm modeling and simulation. For modeling aspects, we employ advanced computational techniques to construct key modules including wind speed profiles and turbine systems, enhancing model accuracy through parametric configuration and real-time data integration. The turbine modeling specifically focuses on doubly-fed induction generators (DFIG), requiring complex mathematical representations of electromechanical dynamics that involve extensive experimental data validation and professional expertise for debugging. The implementation includes adjustable control parameters for power conversion systems and fault diagnostic algorithms to ensure operational reliability and debugging efficiency. Furthermore, we conduct in-depth research addressing prevalent industry challenges such as low power generation efficiency and excessive noise pollution. Our modeling framework incorporates optimization algorithms for maximum power point tracking (MPPT) and acoustic emission reduction strategies, ensuring these critical factors are integral to the design and implementation process. The simulation environment enables performance validation through scenario testing and sensitivity analysis, ultimately improving overall wind farm performance metrics and system reliability through data-driven refinements.