Maintenance Management in Solar Energy Systems

Dear Colleagues,

The energy industry is employing new reliable and efficient renewable energy sources because of government and environment restrictions. The amount of renewable energies available around the world is growing so fast, it is anticipated that their contribution to global energy will be more than 20% in the next few years.

Solar energy is one of the most renewable energies used today but, despite the technical and economic advantages of concentrated solar energy, this industry needs development and improvement of the technologies employed, better maintenance policies, to increase efficiency and sustainability, create a better energy distribution, etc., to reach competitive levels.

Maintenance is a critical variable in the industry when it comes to reaching competitiveness—in fact, together with operations, it is the most important factor in the energy industry. Therefore, a correct management of the corrective, predictive, and preventive politics in any energy industry is required. Maintenance management considers the main concepts, state-of-the-art, advances, and case studies in this topic.

This issue will consider original research works that share content complementary to other subdisciplines, such as economics, finance, marketing, decision and risk analysis, engineering, etc., in maintenance management.

The issue will show also real case studies, with the main topics being failures detection and diagnosis, fault trees, and subdisciplines (e.g., FMECA, FMEA). It is essential to link these topics with finance, scheduling, resources, downtimes, etc. in order to increase productivity, profitability, maintainability, reliability, safety, availability, and reduce costs, downtimes, etc. in the energy industry.

Advances in mathematics, models, computational techniques, dynamic analysis, etc. are employed in maintenance management and are particularly important for this issue.

Finally, we will also consider computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques that are expertly blended to support analysis of multicriteria decision-making problems with defined constraints and requirements.

Prof. Dr. Fausto Pedro García Márquez
Guest Editor

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