Artificial Intelligence in the Reliability Modeling and Maintenance of Renewable Energy Systems
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".
Deadline for manuscript submissions: 24 April 2026 | Viewed by 16
Special Issue Editor
Interests: servicing process; reliability engineering and system safety; system modelling; mathematical modelling; application of mathematics; wind power plant; artificial neural networks; diagnostics information; expert system; intelligent system; knowledge base; power in energy
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleague,
I hereby invite you to contribute to a Special Issue of Energies titled “Artificial Intelligence in the Reliability Modeling and Maintenance of Renewable Energy Systems”.
Today, it is becoming increasingly common to use solar and wind energy, both onshore and offshore. Equipment for generating renewable energy is continuously used, hence it needs to undergo regular, efficient reliability testing. In line with this, the daily costs and technological complexity of operating and maintaining energy equipment are rising. Therefore, publications in this field have been focusing on seeking several types of solutions and a more economical model to replace and repair power equipment.
Continuous repair cost reduction is necessary to effectively maintain renewable energy equipment in continuous serviceability (energy production) or operational readiness. The costs of repairs are strongly correlated with how quickly these facilities are being renewed. Only the employment of intelligent systems that support human (facility user) behavior makes it feasible for technical facilities to be renewed optimally and efficiently. A system where the technical object is refreshed exactly when this is needed is the best way to manage technical objects, and only artificial neural network-based intelligent object detection systems are capable of offering such a method.
Studying and evaluating the resilience of renewable energy systems allows for efficient control of the best plan for producing electricity. The generated model of the operation process and the adopted reliability quantities that analytically describe this model serve as the foundation for the analytical evaluation of the reliability of technical facilities. Measures that increase the reliability, energy, financial efficiency, etc., of the power system in operation can be chosen, relying on the knowledge of its existing reliability.
Currently, cognitive aspects in the use of intelligent systems supporting the use and operation of technical objects are particularly important, especially in the field of modeling the operation processes of the technical objects tested, and the research, evaluation and analysis of the reliability of the operation processes of objects using intelligent systems.
Prof. Dr. Stanisław Duer
Guest Editor
Manuscript Submission Information
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Keywords
- artificial intelligence in energy systems
- modeling of technical objects
- expert systems
- reliability and operation process
- security and safety systems
- diagnostics of technical objects
- renewable energy sources
- three-phase power grid
- transport systems
- wind farm devices
- power in energy
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