Studies on Cup Anemometer Performances Carried out at IDR/UPM Institute. Past and Present Research

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...

mentioning

confidence: 99%

Three-Dimensional Wind Measurement Based on Ultrasonic Sensor Array and Multiple Signal Classification

Teng

Zhu

et al. 2020

“…The S4 wind tunnel is an open-circuit wind tunnel with a closed test section measuring 0.9 by 0.9 m. It is served by four 7.5 kW fans with a flow uniformity under 0.2% in the testing area. More information on the S4 wind tunnel and the anemometer calibration process followed at IDR/UPM Institute can be found in [ 11 , 12 , 13 , 22 ].…”

Section: Experimental Set-upmentioning

confidence: 99%

“…The common work at the IDR/UPM Institute, related to experimental aerodynamics [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ], cup anemometer calibration and behavior characterization [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ], space components analysis (batteries, solar panels, control systems) [ 23 , 24 , 25 , 26 , 27 , 28 ], and space thermal analysis [ 29 , 30 , 31 , 32 ], has driven the development of the 5-channel Arduino-Based Data Acquisition System (ABDAS) described in the present paper. The purpose of this development is to have a simple but accurate multi-purpose 10–500 Hz sampling rate voltage-data acquisition system capable of being used in different measurement problems from measuring temperatures with thermocouples to wind-tunnel pitot-tube pressure signals.…”

Section: Introductionmentioning

confidence: 99%

Design and Development of a 5-Channel Arduino-Based Data Acquisition System (ABDAS) for Experimental Aerodynamics Research

Vidal-Pardo

Pindado

2018

Self Cite

In this work, a new and low-cost Arduino-Based Data Acquisition System (ABDAS) for use in an aerodynamics lab is developed. Its design is simple and reliable. The accuracy of the system has been checked by being directly compared with a commercial and high accuracy level hardware from National Instruments. Furthermore, ABDAS has been compared to the accredited calibration system in the IDR/UPM Institute, its measurements during this testing campaign being used to analyzed two different cup anemometer frequency determination procedures: counting pulses and the Fourier transform. The results indicate a more accurate transfer function of the cup anemometers when counting pulses procedure is used.

“…The use of cup anemometers is widely extended in fields such as meteorology and wind energy production. In the wind energy field, their use is increasing as the installed wind power capacity does [5]. In fact, wind speed metrology is key to assess the energy potential of wind turbines [6,7].…”

Section: Introductionmentioning

confidence: 99%

Alternative Calibration of Cup Anemometers: A Way to Reduce the Uncertainty of Wind Power Density Estimation

Guerrero-Villar¹,

Dorado-Vicente²,

Medina-Sánchez³

et al. 2019

This study presents a procedure to reduce the uncertainty of wind power density estimations, which is useful to improve the energy production predictions of wind farms. Power density is usually determined from the wind speed measured by a cup anemometer and the air density value (conventional procedure). An alternative procedure based on wind speed and dynamic pressure estimations provided by a cup anemometer is proposed. The dynamic pressure is obtained by means of a calibration curve that relates the anemometer rotation frequency and the dynamic pressure measured by a Pitot tube. The quadratic regression, used to define the calibration curve, and its uncertainty are both detailed. A comparison between the alternative procedure and the conventional one points out the advantage of the proposed alternative since results show a high reduction of the indirect measurement uncertainty of wind power density.