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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Main Authors: Komal Saifullah Khan, Muhammad Tariq
Format: Article
Language:English
Published: MDPI AG 2014-11-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/14/11/22140
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spelling 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
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