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Original Authors: Acoidan Betancort Montesdeoca, Aresse Engineering S.L.
Edited by Cyth Systems
The Challenge
Creating a stand-alone, unified platform to acquire and analyze data that certifies small-scale wind turbine efficiency, operation, and structural integrity.
The Solution
Using NI CompactRIO hardware to build a system that combines multiple distributed sensors to gather data in four main groups: reference condition, operational, loading, and electrical parameters.
Small-scale wind turbine installations are growing with the demand for affordable clean energy for isolated consumption as well as the environmental concern of users who try to sustainably use energy resources. These small-scale wind turbines need efficiency, operation, and structural integrity evaluations to verify that they are safe and appropriate for the users and their communities.
In cooperation with Kliux Energies, we developed a stand-alone, unified platform to acquire and analyze the data required by international standards (IEC 61400/2, IEC 61400/11 and IEC 61400/12) to certify the operation of small-scale wind turbines and give the manufacturer a required database to optimize their design.
Left: Measurement Points Diagram, Right: Torque Campbell Diagram
Left: Power Versus Rotor Speed Results, Right: Data Acquisition System Diagram
Hardware Setup
Based on the standard requirements and the data required to validate the analytical design, we chose the CompactRIO platform for our system. We combined multiple sensors distributed on the turbine and its adjacent devices to capture the data provided by the Kliux GEO4K vertical axis small-scale wind turbine. The data is classified into four main groups: reference condition data, operational data, loading data, and electrical parameters. All the data, up to 34 channels, is acquired, analyzed, stored, and classified based on the reference condition by the CompactRIO installed in a cabinet at the small-scale wind turbine (SSWT) ground. A router connected to the Internet via 3G permits access to instantaneously check the installation status and download the stored data.
The system is defined according to the following four subsystems:
Reference Condition Data: We compare the production data to the environmental conditions to calculate the energy the turbine can use. The NI cRIO-9014 embedded controller receives wind speed data from a GILL WindMaster sonic anemometer and temperature, pressure, and humidity data from a Vaisala sensor through RS485.
Operational Data: We analyze the gearbox and gearbox high-frequency accelerations, acoustic noise, and internal gearbox temperature to perform predictive machine condition monitoring. We do this with a single NI 9234 C Series DAQ module that conditions and inputs data from a PCB tri-axial accelerometer and a G.R.A.S. microphone. An NI 9219 C Series module acquires temperature from a PT-100.
Loading Data: To verify the aerodynamic loads of the wind turbine meet the analytical design, we measure the rotor torque and revolutions, the loads at the tower base, the accelerations at the rotor, and the lateral accelerations at different heights of the tower. We can do all this with a single NI 9205 C Series module that reads data from different sensors distributed along the rotor and the tower. An NI 9219 module conditions three strain gages that detect axial load and bending moments on the tower.
Electrical Parameters: To determine the performance of the turbine, we calculate the electrical energy production using an NI 9205 module to digitize three-phase voltage and current data from Phoenix Contact and CR Magnetics sensors at both the generator and the inverter.
Original Authors:
Acoidan Betancort Montesdeoca, Aresse Engineering S.L.
Edited by Cyth Systems
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