Wind farm power maximization based on a cooperative static game approach

The objective of this study is to improve the cost-effectiveness and production efficiency of wind farms using cooperative control. The key factors in determining the power production and the loading for a wind turbine are the nacelle yaw and blade pitch angles. However, the nacelle and blade angles may adjust the wake direction and intensity in a way that may adversely affect the performance of other wind turbines in the wind farm. Conventional wind-turbine control methods maximize the power production of a single turbine, but can lower the overall wind-farm power efficiency due to wake interference. This paper introduces a cooperative game concept to derive the power production of individual wind turbine so that the total wind-farm power efficiency is optimized. Based on a wake interaction model relating the yaw offset angles and the induction factors of wind turbines to the wind speeds experienced by the wind turbines, an optimization problem is formulated with the objective of maximizing the sum of the power production of a wind farm. A steepest descent algorithm is applied to find the optimal combination of yaw offset angles and the induction factors that increases the total wind farm power production. Numerical simulations show that the cooperative control strategy can increase the power productions in a wind farm.