Emerging nano-engineered materials for protection of wind energy applications photovoltaic based nanomaterials

The globe is looking at sustainable energy alternatives to protect the earth for future generations as worry about global warming and the depletion of fossil fuel supplies grows. The largest promise exists for renewable energy sources in hydropower to meet our energy needs and preserve the environment. The effectiveness of the solar panels is enhanced using nanotechnology and nanomaterials to produce more electricity and extend their usable lives. This research proposes novel technique in nanomaterial based wind energy by photovoltaic cell for wind turbines to detect the fault in wind farm in wind energy application using attention mechanism based convolutional neural network. The wind energy forecasting is carried out using spatio temporal stacked reinforcement neural networks. The simulation results demonstrate that suggested method can identify imbalance fault with an accuracy of over 98%, demonstrating its efficacy in identifying wind turbine blade imbalance faults. The proposed technique attained accuracy of 95%, precision of 95%, recall of 82%, specificity of 96%, negative detection of 71%.