Maintenance Management Applied to Renewable Energies
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".
Deadline for manuscript submissions: 31 July 2025 | Viewed by 450
Special Issue Editor
Special Issue Information
Dear Colleagues,
The decarbonization policies and the implementation of the sustainable development goals (SDGs) created by the United Nations General Assembly UNGA in 2015 led to an increase in the use of renewable energies, not only increasing the installed capacity, but also improving their efficiency and power generated and making them more competitive with respect to other non-renewable energy sources.
Operation and maintenance costs are usually high for renewable energies such as wind energy. Adequate maintenance management is essential to improve the efficiency and reliability of renewable energy-generating systems. The condition monitoring of these systems together with advanced mathematical and statistical tools allow us to study the state of the elements, predict future failures, identify failures and establish the best maintenance approaches that make renewable energies more efficient and competitive.
This Special Issue aims to present and disseminate the most recent advances related to maintenance management for renewable energies in order to increase their efficiency and competitiveness. This Special Issue will collect advances in smart maintenance such as approaches for smart maintenance decision support, data-driven decision making or new methods of machine learning, neural networks or deep learning for pattern recognition. In addition, reliability analysis, fault detection and diagnosis, deteriorating systems modelling and optimization methods for maintenance task scheduling will be welcome.
Manuscripts must be related to any type of renewable energy, such as wind energy (onshore, fixed offshore and floating offshore), solar energy (PV, CSP…), ocean energy, etc.
Topics of interest for publication include, but are not limited to:
- Maintenance management;
- Smart maintenance;
- Reliability analysis;
- Failure modes and effect analysis;
- Analysis and modelling of deterioration processes;
- In-depth analysis and comparation of case studies;
- Optimization methods for maintenance;
- Maintenance logistics;
- Maintenance task scheduling;
- Maintenance policies;
- Techno-economic analysis for maintenance approaches;
- Maintenance management of renewable energy storage systems;
- Control and maintenance of hybrid generating systems.
Dr. Jesús María Pinar Pérez
Guest Editor
Manuscript Submission Information
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Keywords
- maintenance management
- smart maintenance
- renewable energy
- reliability
- decision support
- machine learning
- neural networks
- optimization
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