Applying instantaneous SCADA data to artificial intelligence based power curve monitoring and WTG fault forecasting

Bi, R.; Zhou, Chengke; Hepburn, Donald M.

doi:10.1109/icsgce.2016.7876048

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…Maintaining the SCADA systems' resiliency can be accomplished by applying AI techniques. For example, in wind turbine generators, faults could be predicted by employing Artificial Neural Networks (ANNs) that monitor ambient temperature, generator speed, and pitch angle of the generator power outputs [166]. In controlling water systems, AI techniques such as k-NN, Decision Trees, and SVMs were employed to classify different anomaly events, including cyberattacks and hardware failures [167].…”

Section: H Critical Infrastructurementioning

confidence: 99%

Harnessing Artificial Intelligence Capabilities to Improve Cybersecurity

et al. 2020

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Cybersecurity is a fast-evolving discipline that is always in the news over the last decade, as the number of threats rises and cybercriminals constantly endeavor to stay a step ahead of law enforcement. Over the years, although the original motives for carrying out cyberattacks largely remain unchanged, cybercriminals have become increasingly sophisticated with their techniques. Traditional cybersecurity solutions are becoming inadequate at detecting and mitigating emerging cyberattacks. Advances in cryptographic and Artificial Intelligence (AI) techniques (in particular, machine learning and deep learning) show promise in enabling cybersecurity experts to counter the ever-evolving threat posed by adversaries. Here, we explore AI's potential in improving cybersecurity solutions, by identifying both its strengths and weaknesses. We also discuss future research opportunities associated with the development of AI techniques in the cybersecurity field across a range of application domains.

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Section: H Critical Infrastructurementioning

confidence: 99%

Harnessing Artificial Intelligence Capabilities to Improve Cybersecurity

et al. 2020

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Wind Energy Forecasting with Artificial Intelligence Techniques: A Review

Maldonado

Valdiviezo

Solano

et al. 2020

Communications in Computer and Information Science

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Using SCADA Data for Wind Turbine Condition Monitoring: A Systematic Literature Review

et al. 2020

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Operation and maintenance (O&M) activities represent a significant share of the total expenditure of a wind farm. Of these expenses, costs associated with unexpected failures account for the highest percentage. Therefore, it is clear that early detection of wind turbine (WT) failures, which can be achieved through appropriate condition monitoring (CM), is critical to reduce O&M costs. The use of Supervisory Control and Data Acquisition (SCADA) data has recently been recognized as an effective solution for CM since most modern WTs record large amounts of parameters using their SCADA systems. Artificial intelligence (AI) techniques can convert SCADA data into information that can be used for early detection of WT failures. This work presents a systematic literature review (SLR) with the aim to assess the use of SCADA data and AI for CM of WTs. To this end, we formulated four research questions as follows: (i) What are the current challenges of WT CM? (ii) What are the WT components to which CM has been applied? (iii) What are the SCADA variables used? and (iv) What AI techniques are currently under research? Further to answering the research questions, we identify the lack of accessible WT SCADA data towards research and the need for its standardization. Our SLR was developed by reviewing more than 95 scientific articles published in the last three years.

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Applying instantaneous SCADA data to artificial intelligence based power curve monitoring and WTG fault forecasting

Cited by 3 publications

References 12 publications

Harnessing Artificial Intelligence Capabilities to Improve Cybersecurity

Harnessing Artificial Intelligence Capabilities to Improve Cybersecurity

Wind Energy Forecasting with Artificial Intelligence Techniques: A Review

Using SCADA Data for Wind Turbine Condition Monitoring: A Systematic Literature Review

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