Intelligent Condition Monitoring of Wind Power Systems

Dear Colleagues,

We are inviting submissions to a Special Issue of Energies on the subject area of “Intelligent Condition Monitoring of Wind Power Systems”. Wind turbines, both onshore and offshore, represent a major and rapidly growing form of renewable and sustainable energy generation. Modern wind turbines operate in continuously transient conditions, with varying speed, torque, and power based on the stochastic nature of the wind resource. These uncertainties can affect not only the operational performance but also the integrity of the wind power generation system under service conditions. Condition monitoring (CM) continues to play an important role in achieving reliable and economic operation of wind turbines. Recent developments in artificial intelligence (AI) and computational intelligence (CI) techniques have received considerable attention in the CM area, indicating promising application potential. It is essential that intelligent CM techniques utilizing AI and CI are developed to improve detection robustness and increase confidence of diagnosis and prognosis. This could enable CM to become more capable at the detection and diagnosis of faults and become better at autonomous prediction of operational state and failures of key components and the system as a whole, with as little human intervention as possible.

The aim of this Special Issue is to collect and disseminate novel, intelligent, and autonomous condition monitoring techniques and their potential applications for wind power systems. Topics of interest for this Special Issue include but are not limited to:

• Development of condition monitoring systems including sensor systems
• Modeling and condition monitoring of electric machines and drives/wind power generation systems
• Power conversion system reliability
• Power electronic condition monitoring
• Condition monitoring of the interconnection/HVDC electronics
• Performance analysis of wind turbines and their connections
• Condition-based operation and maintenance strategies
• Physics-based modeling and data-driven modeling
• Signal processing and data mining
• AI- and CI-enabled techniques and applications

Dr. Xiandong Ma
Dr. Sinisa Durovic
Prof. Dr. Mohamed Benbouzid
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.