Wind farm power maximization based on analytical sensitivity model considering wake effect

•An analytical sensitivity model of the wind farm power that quantitatively portrays the wake effect.•The wind farm power enhancement mechanism which contributes to accelerating the optimization process.•A wind farm power maximization method with higher optimization speed and better scenario applicability. To reduce the wake effect on wind energy capture, it is necessary to optimize the operating parameters of each wind turbine (WT) in the wind farm (WF) to improve the overall wind power. Considering the complex coupling characteristics of wind energy captured by upstream and downstream WTs caused by the wake effect, existing optimization methods for the WF usually adopt intelligent algorithms or numerical sensitivity-based search algorithms. However, most of the existing studies overlook the exploration of the physical mechanism underlying the wake influence on WF power, and the optimization speed still needs to be improved. To this end, in this paper, the analytical sensitivity model of WF power is formulated with the adjustable parameter - the pitch angle which is a key factor for the wake effect. On this basis, the improvement mechanism of how the WF power can be improved by changing the wake effect through the pitch angle is analyzed using the Blade Element Momentum theory, which can be used to guide and accelerate the optimization process. Furthermore, the WF power maximization method based on the analytical sensitivity model is proposed, and its effectiveness and advancement are verified based on SimWindFarm simulation under different operation scenarios.