Accurate Monitoring and Fault Detection in Wind Measuring Devices through Wireless Sensor Networks
Many wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulat...
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doaj-ff9bcbf5329348469d674e9de2df06022020-11-25T00:29:12ZengMDPI AGSensors1424-82202014-11-011411221402215810.3390/s141122140s141122140Accurate Monitoring and Fault Detection in Wind Measuring Devices through Wireless Sensor NetworksKomal Saifullah Khan0Muhammad Tariq1Department of Electrical Engineering, National University of Computer & Emerging Sciences (NUCES), Peshawar Campus, Peshawar 25000, PakistanDepartment of Electrical Engineering, National University of Computer & Emerging Sciences (NUCES), Peshawar Campus, Peshawar 25000, PakistanMany wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulated models) may vary from the actual potential of the area. Hence, introducing accurate site assessment techniques will lead to accurate predictions of energy production from a particular area. We solve this problem by installing a Wireless Sensor Network (WSN) to periodically analyze the data from anemometers installed in that area. After comparative analysis of the acquired data, the anemometers transmit their readings through a WSN to the sink node for analysis. The sink node uses an iterative algorithm which sequentially detects any faulty anemometer and passes the details of the fault to the central system or main station. We apply the proposed technique in simulation as well as in practical implementation and study its accuracy by comparing the simulation results with experimental results to analyze the variation in the results obtained from both simulation model and implemented model. Simulation results show that the algorithm indicates faulty anemometers with high accuracy and low false alarm rate when as many as 25% of the anemometers become faulty. Experimental analysis shows that anemometers incorporating this solution are better assessed and performance level of implemented projects is increased above 86% of the simulated models.http://www.mdpi.com/1424-8220/14/11/22140wind speed monitoringerror detectionwireless sensor networkssite assessmentcup anemometers |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Komal Saifullah Khan Muhammad Tariq |
spellingShingle |
Komal Saifullah Khan Muhammad Tariq Accurate Monitoring and Fault Detection in Wind Measuring Devices through Wireless Sensor Networks Sensors wind speed monitoring error detection wireless sensor networks site assessment cup anemometers |
author_facet |
Komal Saifullah Khan Muhammad Tariq |
author_sort |
Komal Saifullah Khan |
title |
Accurate Monitoring and Fault Detection in Wind Measuring Devices through Wireless Sensor Networks |
title_short |
Accurate Monitoring and Fault Detection in Wind Measuring Devices through Wireless Sensor Networks |
title_full |
Accurate Monitoring and Fault Detection in Wind Measuring Devices through Wireless Sensor Networks |
title_fullStr |
Accurate Monitoring and Fault Detection in Wind Measuring Devices through Wireless Sensor Networks |
title_full_unstemmed |
Accurate Monitoring and Fault Detection in Wind Measuring Devices through Wireless Sensor Networks |
title_sort |
accurate monitoring and fault detection in wind measuring devices through wireless sensor networks |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2014-11-01 |
description |
Many wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulated models) may vary from the actual potential of the area. Hence, introducing accurate site assessment techniques will lead to accurate predictions of energy production from a particular area. We solve this problem by installing a Wireless Sensor Network (WSN) to periodically analyze the data from anemometers installed in that area. After comparative analysis of the acquired data, the anemometers transmit their readings through a WSN to the sink node for analysis. The sink node uses an iterative algorithm which sequentially detects any faulty anemometer and passes the details of the fault to the central system or main station. We apply the proposed technique in simulation as well as in practical implementation and study its accuracy by comparing the simulation results with experimental results to analyze the variation in the results obtained from both simulation model and implemented model. Simulation results show that the algorithm indicates faulty anemometers with high accuracy and low false alarm rate when as many as 25% of the anemometers become faulty. Experimental analysis shows that anemometers incorporating this solution are better assessed and performance level of implemented projects is increased above 86% of the simulated models. |
topic |
wind speed monitoring error detection wireless sensor networks site assessment cup anemometers |
url |
http://www.mdpi.com/1424-8220/14/11/22140 |
work_keys_str_mv |
AT komalsaifullahkhan accuratemonitoringandfaultdetectioninwindmeasuringdevicesthroughwirelesssensornetworks AT muhammadtariq accuratemonitoringandfaultdetectioninwindmeasuringdevicesthroughwirelesssensornetworks |
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