Designing, Monitoring, Diagnosis and Reliability of the Renewable Energy Systems
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".
Deadline for manuscript submissions: closed (31 March 2019) | Viewed by 13223
Special Issue Editors
Interests: photovoltaic systems; renewable energy technologies; smart cities technologies; infrared analysis; cloud-based applications for the energy; diagnostics and prognostics
Special Issues, Collections and Topics in MDPI journals
Interests: MATLAB simulation; renewable energy technologies; electrical power engineering; power electronics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The Special Issue is focused on the issues related to the designing of Renewable Energy Sources (RES), the monitoring of the performance, the diagnosis of failures, the reliability, and the resilience. The RES have been rapidly growing in the past years in all over the world with beneficial effects on the price reduction. Researchers are making a valuable contribution to the development of increasingly efficient renewable energy sources, by improving the designing of the constituting components and increasing the performance of RES. Diagnostics and prognostics are reducing the time related to a fault (MTTF, MTTR, MDT, etc.) and increasing the availability of the power source at full power. Topics of interest for this issue include, but are not limited to the areas:
- Photovoltaic systems
- Concentrating solar systems
- Concentrating photovoltaics and thermal (CPT) systems
- Wind systems
- Tidal systems
- Storage systems for RES applications
- Electrical machines for RES
- Converters for RES
- Maximum power point tracking techniques
- Modelling of renewable energy devices and systems
- Modeling of smart and/or insulated grids with distributed RES
Application of the following techniques and methods within the aims of this special issue:
- Innovative sensors and data acquisition systems
- Not-Destructive Techniques (NDT - infrared, luminescence, etc.)
- Diagnostics and prognostics
- Statistic methodologies
- Artificial intelligence techniques and machine learning for diagnostics
- Forecasting techniques
- Optimization techniques
- Decision support and IT solutions for diagnostics
- IoT
Dr. Silvano Vergura
Prof. Giuseppe Marco TINA
Guest Editors
Manuscript Submission Information
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