AI Based Real-Time Signal Reconstruction for Wind Farm with SCADA Sensor Failure - Artificial Intelligence Applications and Innovations Access content directly
Conference Papers Year : 2020

AI Based Real-Time Signal Reconstruction for Wind Farm with SCADA Sensor Failure

Nadia Masood Khan
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Peter Matthews
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Abstract

Supervisory Control and Data Acquisition (SCADA) systems used in wind turbines for monitoring the health and performance of a wind farm can suffer from data loss due to sensor failure, transmission link breakdown or network congestion. Sensory data is used for important control decisions and such data loss can make the failures harder to detect. This work proposes various solutions to reconstruct the lost information of important SCADA parameters using Linear and non-linear Artificial Intelligence (AI) algorithms. It comprises of three major contributions; (1) signal reconstruction from other available SCADA parameters, (2) comparison of linear and non-linear AI models, and (3) generalization of the AI algorithms between turbines. Experimental results demonstrate the effectiveness of the developed methodologies for reconstruction of the lost information for valuable planning decisions.
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hal-04060654 , version 1 (06-04-2023)

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Nadia Masood Khan, Gul Muhammad Khan, Peter Matthews. AI Based Real-Time Signal Reconstruction for Wind Farm with SCADA Sensor Failure. 16th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Jun 2020, Neos Marmaras, Greece. pp.207-218, ⟨10.1007/978-3-030-49186-4_18⟩. ⟨hal-04060654⟩
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