Politecnico di Torino - Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY

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Micro wind energy conversion system (micro-wecs)

artificial neural networkenergy conversionESTECHMax power point trackingsensorless systemwind turbine


Micro-WECSs allow energy coming from a synchronous generator, supplied by a vertical-axis wind turbine, to be injected into the national single-phase low-voltage grid. As the wind speed varies and transfers power to the turbine, the system  is  able  to compute and reach the angular speed that allows extracting the maximum available power. Our micro-WECS tracks the maximum power almost instantaneously and does not use mechanical sensors for measuring wind speed and angular speed. This implies increased yield and reliability, and a lower cost.

Technical features

The system we have conceived and set-up belongs to the class of Micro Wind Energy Conversion Systems (micro-WECSs), to be connected to the national single-phase low-voltage grid. It could cover a power range from 1 kW to 10 kW. Differently from other approaches, our micro-WECS tracks the maximum power exploiting an artificial neural network, which operates as a virtual anemometer, and using an electronic circuit that acts as a virtual encoder. The tracking is almost instantaneous, so the yield is increased; also, mechanical sensors are not needed, enabling to achieve a higher reliability and a lower cost. The control logic has been implemented on a field programmable gate array (FPGA) platform. This choice allows a higher working frequency and the true parallel execution of several tasks, so that good performance can be obtained despite the use of a simple hardware topology.

Possible Applications

  • Microgeneration in residential and service sectors
  • Possible integration with other generators and storage devices
  • Rural electrification
  • Retrofitting of existing micro-wind energy conversion systems


  • Higher energy yield (especially at low wind speed)
  • Higher reliability
  • Higher robustness
  • Low production cost