The wind power industry continues to experience rapid growth worldwide. However, the fluctuations in wind speed and direction complicate the wind turbine control process and hinder the integration of wind power into the electrical grid. To maximize wind utilization, we propose to precisely measure the wind in a three-dimensional (3D) space, thus facilitating the process of wind turbine control. Natural wind is regarded as a 3D vector, whose direction and magnitude correspond to the wind's direction and speed. A semi-conical ultrasonic sensor array is proposed to simultaneously measure the wind speed and direction in a 3D space. As the ultrasonic signal transmitted between the sensors is influenced by the wind and environment noise, a Multiple Signal Classification algorithm is adopted to estimate the wind information from the received signal. The estimate's accuracy is evaluated in terms of root mean square error and mean absolute error. The robustness of the proposed method is evaluated by the type A evaluation of standard uncertainty under a varying signal-to-noise ratio. Simulation results validate the accuracy and anti-noise performance of the proposed method, whose estimated wind speed and direction errors converge to zero when the SNR is over 15 dB.Sensors 2020, 20, 523 2 of 16 turbines, which further maximizes wind utilization efficiency [10]. In addition, wind measurement can be used to estimate the corresponding power generation, thus contributing to the system scheduling and energy dispatching, and, ultimately, the integration of wind power in the grid [11]. In summation, precise wind speed and direction measurements in a 3D space are of vital importance to wind energy utilization and the wind power industry.Light detection and ranging (LIDAR) technology is one of the most popular wind measurements [12]. However, LIDAR can only measure the wind speed component along the line of sight, a disadvantage known as "the Cyclops dilemma" [13,14]. Therefore, the wind distribution measurement in a 3D space would require the very costly installment and deployment of several LIDARs in the wind farm. In contrast, wind measurement sensors are much cheaper and could be deployed around the wind field in distances of miles to provide information for previewing wind measurement. Several types of wind measurement sensors have been employed by researchers, including cup anemometers [15][16][17], thermal anemometers [18][19][20], and ultrasonic anemometers [21][22][23]. However, measurements from cup anemometers often suffer from errors caused by wear and tear on the internal rotating bearings, and frequent inspection or calibration is required to ensure measurement accuracy [24,25]. The performance of cup anemometers can also be affected by the measuring environment. For example, cup anemometers are prone to jamming in humid environments, since water vapor can penetrate their bearings [26]. Thermal anemometers also have difficulties coping with harsh environments. In addition, their sensitivity to changes in the velocity f...
