MPPT Control of Wind Generation Systems Based on Estimated Wind Speed Using SVR

In this paper, a novel algorithm for wind-speed estimation in wind-power generation systems is proposed, which is based on the theory of support-vector regression (SVR). The inputs of the SVR wind-speed estimator are chosen as the wind-turbine power and rotational speed. During the offline training, a specified model, which relates the inputs to the output, is obtained. Then, the wind speed is determined online from the instantaneous inputs. The experimental results have verified the validity of the proposed estimation algorithm.

I. Introduction

In most of wind-energy generation systems, anemometers are used to measure the wind speed for the maximum-power-point-tracking (MPPT) control [1]. The anemometer installed on the top of nacelle may be a source of inaccurate measurement of the wind speed. In wind farms, several anemometers are often placed at some locations to measure the average wind speed [2]. The use of anemometers raises a problem of calibration and measurement accuracy, as well as increasing the initial cost of the wind generation systems. For these reasons, it is desirable to replace the mechanical anemometers by the digital wind-speed estimator based on the turbine characteristics.