Site Wind Energy Appraisal Function for Future Egyptian Homes
Proceedings of the Grid of the Future Symposium
Wind energy systems are ideally suited for distributed generation systems especially in Egypt to solve the energy problem in future homes. This paper proposes identification and estimation of wind energy in Egypt to present a simple method for the calculation and appraisal of the wind energy potential available in Egypt. This is done based on real data from many stations in Egypt with the aid of Artificial Neural Network (ANN). The Neural Network is created and trained by the data of many wind energy stations in Egypt like: Sallum, Sidi Barrani, El Dabaa, Dekheila, Alexandria, Balteam, Damietta, Port Said, and El Arish stations; then checked and tested for Marsa Matroh and Hergada stations to show its validity. The neural network' inputs are: Latitude, Longitude, Elevation and Month; the output is the monthly wind speed. This Simulink Model (GUI) or the algebraic equations could be used directly without the need of Network training every time. ANN model is created with suitable numbers of layers and neurons, which trained, simulated, and checked with excellent regression constant. This neural model has the ability to predict values in – between learning values, also make interpolation between learning curves data. The validity of the model is achieved from comparison between target and output and model excellent regression factor. This work aims to identify good sites in Egypt for new wind turbine installations and predict for other sites too to help in designing wind family homes. All results and simulations data are well depicted in the form of 3D figures.
"Site Wind Energy Appraisal Function for Future Egyptian Homes."
Proceedings of the Grid of the Future Symposium: 1-13 Paris, France: CIGRE U.S. National Committee.