Modelling and Simulation of Wind Power System Considering Wake Effect Using DigSILENT

The increasing demand for electricity, coupled with the depletion of fossil fuel sources, has accelerated the integration of renewable energies into conventional power generation. Wind energy, recognized for its environmental benefits, faces challenges related to the wake effect resulting in decreased wind velocity downstream of wind turbines (WITs). This turbulence adversely affects power generation efficiency, necessitating the optimization of wind farm layouts (WFALO) to mitigate operational and maintenance costs. This article employs DigSILENT for modeling and simulation, considering wake effects to enhance wind power system efficiency. The wake effect involves a reduction in wind speed and turbulence downstream of WITs, impacting neighboring turbines. Optimizing WFALO requires meticulous consideration of factors such as elevation, wind speed, and hub height. Current techniques often fall short due to computational complexities. The article introduces wake effect models, categorizing them into hydrodynamic and domain models. The Jensin model is highlighted for its simplicity and accuracy in predicting wake effects. Mathematical formulations for non-wake, full wake, partial wake, and multiple wake effects are presented. The impact of wake effects on wind farm output power is analyzed, demonstrating potential power losses of 10-15%. Wind farm designs with uniform or multiple WIT specifications pose challenges in optimization algorithms due to computational complexities. The study emphasizes the importance of incorporating wake effects into wind farm design, considering turbine spacing, control algorithms, and rotor designs. A 15 MW wind power system is simulated in DigSILENT, revealing a significant reduction in wind speed and power output due to wake effects. The outcomes underscore the need for ongoing research in wake modeling and prediction methods to optimize wind farm layouts and operational strategies, promoting cleaner and sustainable power sources.