ResFaultyMan: An intelligent fault detection predictive model in power electronics systems using unsupervised learning isolation forest

Safari, Ashkan; Sabahi, Mehran; Oshnoei, Arman

doi:10.1016/j.heliyon.2024.e35243

Heliyon

2024

DOI: 10.1016/j.heliyon.2024.e35243

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ResFaultyMan: An intelligent fault detection predictive model in power electronics systems using unsupervised learning isolation forest

Ashkan Safari,

Mehran Sabahi,

Arman Oshnoei

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2024

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Cited by 1 publication

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Energy Intelligence: A Systematic Review of Artificial Intelligence for Energy Management

Safari,

Daneshvar,

Anvari-Moghaddam

2024

Applied Sciences

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Artificial intelligence (AI) and machine learning (ML) can assist in the effective development of the power system by improving reliability and resilience. The rapid advancement of AI and ML is fundamentally transforming energy management systems (EMSs) across diverse industries, including areas such as prediction, fault detection, electricity markets, buildings, and electric vehicles (EVs). Consequently, to form a complete resource for cognitive energy management techniques, this review paper integrates findings from more than 200 scientific papers (45 reviews and more than 155 research studies) addressing the utilization of AI and ML in EMSs and its influence on the energy sector. The paper additionally investigates the essential features of smart grids, big data, and their integration with EMS, emphasizing their capacity to improve efficiency and reliability. Despite these advances, there are still additional challenges that remain, such as concerns regarding the privacy of data, challenges with integrating different systems, and issues related to scalability. The paper finishes by analyzing the problems and providing future perspectives on the ongoing development and use of AI in EMS.

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Energy Intelligence: A Systematic Review of Artificial Intelligence for Energy Management

Safari,

Daneshvar,

Anvari-Moghaddam

2024

Applied Sciences

View full text Add to dashboard Cite

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scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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ResFaultyMan: An intelligent fault detection predictive model in power electronics systems using unsupervised learning isolation forest

Cited by 1 publication

References 28 publications

Energy Intelligence: A Systematic Review of Artificial Intelligence for Energy Management

Energy Intelligence: A Systematic Review of Artificial Intelligence for Energy Management

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