Maximum Power Point Tracking of a Wind Power Plant With Predictive Gradient Ascent Method

Abstract

In this paper, we present maximum power point tracking for a wind power plant (WPP) using the gradient ascent (GA) in a data-driven manner. The conventional GA method achieves fast convergent performance by considering only direct wake terms when calculating the axial induction factors. However, the conventional method might not be close to optimal even when the wind conditions are steady state. In this paper, we propose a new method using the relationships between the direct and indirect wake terms. Using the relationship between the wake terms can prevent sudden deviations after convergence to a single operating point, even when significant indirect wake terms exist in the presence of multiple wakes. Therefore, the proposed method provides not only fast convergence to an operating point, but also closer-to- optimal power production without sudden deviations compared to the conventional method. We validated the effectiveness of the proposed method using modeled WPP layouts with various wind conditions.