A project by SUSU scientists to develop the mechanical elements of blades for uninterrupted operation of wind turbines and quadcopters was supported by a grant from the Russian Science Foundation. This will increase the efficiency of quadcopter battery utilization and reduce the cost of wind turbines for emergency shutdown and restart. The neural network being developed on the basis of a control system is designed to fine-tune the operation of the upgraded equipment.
Researchers from the SUSU Department of Industrial Thermal Power Engineering have come up with an idea to equip the blades of horizontal wind generators with mechanical elements similar to those found in aircrafts, which will increase the efficiency of wind power plants. With these elements, the blade will be less susceptible to deformation, and the wind turbine will be less likely to stop in high wind speeds. The cost of "strong" wind turbines (more than 2 kW) is over 100 thousand roubles.
These mechanical elements will help avoid complete shutdown of the wind farm. Instead, the blades will slow down to safe speeds. Continuous operation of the wind turbine will prevent power supply failure and will eliminate the need for a backup power source. In addition, the developed mechanical element can be used to, among other things, improve the operational capabilities of civilian quadcopters, which are used for maintenance of power and heating networks, and agricultural needs, such as cadastral works.
The ability to adjust the angle of the quadcopter's blades during takeoff and landing will reduce the amount of power consumed by the battery. Battery power will also be saved because the operator can turn parts of the blade up and down, left and right. Another advantage in this area of research is that the trajectory of the quadcopter will become more stable, and the probability of the device toppling over will be minimized.
Within this grant, scientists are also developing a neural network that will support higher quality operation of wind turbines and quadcopters. Neural networks are needed in industrial applications to collect data on operator errors and control systems that need to be avoided in the future.