New undergraduate research project in Electrical and Systems Engineering! Learn More.
Solar power has become a popular source of renewable energy for both commercial and presidential use. Unlike weather, solar power generation varies significantly across different regions, due to shade, surroundings, etc. Therefore, it is important to help solar power users accurately predict local generation amount. In this project, students will build real weather stations in multiple locations to measure local weather conditions (e.g., temperature, humidity, wind speed) and solar power generation, and predict local solar power generation based on weather forecasts. Machine learning techniques will be utilized to implement the prediction model, and measured data will be used to validate the designed prediction method. Contact Professor Arye Nehorai for more information.