Explainable artificial intelligence for energy systems maintenance: A review on concepts, current techniques, challenges, and prospects
University of Southern Denmark · Maersk (Denmark)
Abstract
The rising demand for energy requires high investments in network extensions and renewable sources, alongside replacing inefficient systems. Smart maintenance is important in minimizing unscheduled outages, reducing costs, improving network security, and increasing equipment’s life expectancy. The vast amount of data collected by sensors and measurements in energy networks makes it hard for humans to detect failures continuously. Thanks to recent breakthroughs in AI, the energy sector has boosted the use of intelligent algorithms in this field. Despite the widespread popularity and great results of machine learning (ML) models in many applications, they are mostly nevertheless considered ”black boxes” as…
Citation impact
- FWCI
- 33.10
- Percentile
- 100%
- References
- 263
Authors
3Topics & keywords
- Current (fluid)
- Systems engineering
- Energy (signal processing)
- Computer science
- Risk analysis (engineering)
- Management science
- Engineering
- Electrical engineering
- Affordable and clean energy