Condition Monitoring, Fault Diagnosis, Sustainable Control and Grid Integration of Wind Turbines

Short description of the research team

Thematic fields of interest/research areas: Condition Monitoring, Fault Diagnosis, Sustainable Control and Grid Integration of Wind Turbines

Manager/head of the team: Dr. Silvio Simani

Team members: Dr. Marcello Bonfè, Dr. Elena Mainardi, Mauro Mazza


Research infrastructures: Laboratory of Intelligent Robotics and Automation. The laboratory houses several state of the art tests and measurement set-ups, including power supplies, multimeters, signal generators, mixed signal oscilloscopes and personal computers. The laboratory is also equipped with the necessary hardware and software for experimenting on field PLCs (Rockwell Automation – CompactLogix, Schneider Electric - ELAU PacDrive, Siemens - S7-300). The laboratory provides facilities also both for training and research in robotics and related fields, such as artificial intelligence, pattern recognition and computer graphics. Software development for robotic applications, development of interface circuits and sensory circuits pertaining to position feedback form the majority of the research studies conducted in this laboratory. Home made and industrial robots are available.


Prerequisites of the trainee researcher:

Level of education: “Marie Curie Individual Fellowship” Action requirements.
Research experience: Engineering & information science: Automation & Robotics
Required working language: English
Further required requisites: Computer Hardware, Information Systems, Software Development, Artificial Intelligence, Signal Processing, Systems, Control, Modelling & Neural Networks


Further useful information:

The increasing demand in energy, the consequent depletion reserves of fossil fuels and the commitment of governments to reduce greenhouse gases effect required by peoples, encouraged the renewable energy development. Among the renewable energies, wind energy presents the highest growth in installed capacity and penetration in modern power systems. This is why reliability of wind turbines becomes an important topic in research and industry.
Wind turbines have highly non-linear dynamics with stochastic and uncontrollable variables, presenting an interesting challenge for modern control methods. In addition, the increasing degree of complexity of such systems needs a rigorous monitoring. Also if a fault happens in a critical part of the wind turbine, it can cause damages to the entire system. Thus, this surveillance must be able to detect an abnormal system operation, to localize it and to identify it in order to decide an action to undertake: making corrective maintenance, or changing the control strategy by Fault Tolerant Control.
Regarding this issue, the key point is represented by the development of suitable control methods, which can provide sustainable maximisation of energy conversion efficiency over wider than normally expected wind speeds, whilst also giving a degree of tolerance to certain faults, providing an important impact on maintenance scheduling, e.g. by capturing the effects of some turbine system faults before they become serious.
In the same context, the integration of wind power units in distribution grid, mainly those above the megawatt, is a question that interest most network operators. The main impacts on electrical systems, for these transmission operators, are variations of the voltage and changes of the power flows due to, both stochastic nature of the wind turbine variables, and also to the grid components.


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