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Maintenance Management in Solar Energy Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A2: Solar Energy and Photovoltaic Systems".

Deadline for manuscript submissions: closed (1 August 2021) | Viewed by 12662

Special Issue Editor

Special Issue Information

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

Manuscript Submission Information

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Keywords

  • maintenance
  • energy
  • diagnosis
  • prognosis
  • predictive maintenance
  • preventive maintenance
  • corrective maintenance
  • downtime
  • strategy on maintenance
  • maintenance planning
  • resource management
  • organization management
  • financial
  • cost
  • profit
  • efficiency
  • reliability
  • availability
  • safety
  • maintainability
  • durability
  • alarms
  • scada
  • condition monitoring
  • maintenance software

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Published Papers (4 papers)

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Editorial

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3 pages, 195 KiB  
Editorial
Maintenance Management in Solar Energy Systems
by Fausto Pedro García Márquez
Energies 2022, 15(10), 3727; https://doi.org/10.3390/en15103727 - 19 May 2022
Cited by 2 | Viewed by 1233
Abstract
The energy industry is employing new reliable and efficient renewable energy sources because of government and environment restrictions [...] Full article
(This article belongs to the Special Issue Maintenance Management in Solar Energy Systems)

Research

Jump to: Editorial

27 pages, 2395 KiB  
Article
Criticality Analysis and Maintenance of Solar Tower Power Plants by Integrating the Artificial Intelligence Approach
by Samir Benammar and Kong Fah Tee
Energies 2021, 14(18), 5861; https://doi.org/10.3390/en14185861 - 16 Sep 2021
Cited by 8 | Viewed by 2585
Abstract
Maintenance of solar tower power plants (STPP) is very important to ensure production continuity. However, random and non-optimal maintenance can increase the intervention cost. In this paper, a new procedure, based on the criticality analysis, was proposed to improve the maintenance of the [...] Read more.
Maintenance of solar tower power plants (STPP) is very important to ensure production continuity. However, random and non-optimal maintenance can increase the intervention cost. In this paper, a new procedure, based on the criticality analysis, was proposed to improve the maintenance of the STPP. This procedure is the combination of three methods, which are failure mode effects and criticality analysis (FMECA), Bayesian network and artificial intelligence. The FMECA is used to estimate the criticality index of the different elements of STPP. Moreover, corrections and improvements were introduced on the criticality index values based on the expert advice method. The modeling and the simulation of the FMECA estimations incorporating the expert advice method corrections were performed using the Bayesian network. The artificial neural network is used to predicate the criticality index of the STPP exploiting the database obtained from the Bayesian network simulations. The results showed a good agreement comparing predicted and actual criticality index values. In order to reduce the criticality index value of the critical elements of STPP, some maintenance recommendations were suggested. Full article
(This article belongs to the Special Issue Maintenance Management in Solar Energy Systems)
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23 pages, 6707 KiB  
Article
A Combined Approach for Model-Based PV Power Plant Failure Detection and Diagnostic
by Christopher Gradwohl, Vesna Dimitrievska, Federico Pittino, Wolfgang Muehleisen, András Montvay, Franz Langmayr and Thomas Kienberger
Energies 2021, 14(5), 1261; https://doi.org/10.3390/en14051261 - 25 Feb 2021
Cited by 9 | Viewed by 2197
Abstract
Photovoltaic (PV) technology allows large-scale investments in a renewable power-generating system at a competitive levelized cost of electricity (LCOE) and with a low environmental impact. Large-scale PV installations operate in a highly competitive market environment where even small performance losses have a high [...] Read more.
Photovoltaic (PV) technology allows large-scale investments in a renewable power-generating system at a competitive levelized cost of electricity (LCOE) and with a low environmental impact. Large-scale PV installations operate in a highly competitive market environment where even small performance losses have a high impact on profit margins. Therefore, operation at maximum performance is the key for long-term profitability. This can be achieved by advanced performance monitoring and instant or gradual failure detection methodologies. We present in this paper a combined approach on model-based fault detection by means of physical and statistical models and failure diagnosis based on physics of failure. Both approaches contribute to optimized PV plant operation and maintenance based on typically available supervisory control and data acquisition (SCADA) data. The failure detection and diagnosis capabilities were demonstrated in a case study based on six years of SCADA data from a PV plant in Slovenia. In this case study, underperforming values of the inverters of the PV plant were reliably detected and possible root causes were identified. Our work has led us to conclude that the combined approach can contribute to an efficient and long-term operation of photovoltaic power plants with a maximum energy yield and can be applied to the monitoring of photovoltaic plants. Full article
(This article belongs to the Special Issue Maintenance Management in Solar Energy Systems)
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13 pages, 4175 KiB  
Article
Comparative Study of Tubular Solar Stills with Phase Change Material and Nano-Enhanced Phase Change Material
by M. Mohamed Thalib, Athikesavan Muthu Manokar, Fadl A. Essa, N. Vasimalai, Ravishankar Sathyamurthy and Fausto Pedro Garcia Marquez
Energies 2020, 13(15), 3989; https://doi.org/10.3390/en13153989 - 2 Aug 2020
Cited by 79 | Viewed by 4902
Abstract
This study is intended to investigate and analyze the operational performances of the Conventional Tubular Solar Still (CTSS), Tubular Solar Still with Phase Change Material (TSS-PCM) and Tubular Solar Still with Nano Phase Change Material (TSS-NPCM). Paraffin wax and graphene plusparaffin wax were [...] Read more.
This study is intended to investigate and analyze the operational performances of the Conventional Tubular Solar Still (CTSS), Tubular Solar Still with Phase Change Material (TSS-PCM) and Tubular Solar Still with Nano Phase Change Material (TSS-NPCM). Paraffin wax and graphene plusparaffin wax were used in the CTSS to obtain the modified solar still models. The experimental study was carried out in the three stills to observe the operational parameters at a water depth of 1 cm. The experiment revealed that TSS-NPCM showed the best performance and the highest yield in comparison to other stills. The distillate yield from the CTSS, TSS-PCM and TSS-NPCM was noted to be 4.3, 6.0 and 7.9 kg, respectively, the daily energy efficiency of the stills was observed to be 31%, 46% and 59%, respectively, and the daily exergy efficiency of the stills was recorded to be 1.67%, 2.20% and 3.75%, respectively. As the performance of the TSS-NPCM was enhanced, the cost of freshwater yield obtained was also low in contrast to the other two types of stills. Full article
(This article belongs to the Special Issue Maintenance Management in Solar Energy Systems)
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