The development of models for renewable energy prediction is one of the main targets of the HY4RES research project. In fact, intermittent renewable energy sources rely heavily on weather conditions and on the availability of natural resources such as solar radiation and wind to produce electricity.
Therefore, the first step to develop novel renewable energy prediction models is to obtain accurate forecasts of future weather conditions.
The HY4RES Weather Forecast App for Renewable Energy Prediction developed by Easy Hydro provides a comprehensive set of over 30 weather variables (e.g. temperature, humidity, precipitation, wind speed, air pressure, UV index) with forecasts up to 15 days ahead. The app will be useful to develop appropriate energy management strategies based on such weather forecasts.
This desktop app integrates an API continuously gathering weather forecast data on an hourly basis. A graphical example of the app is shown in the graphic below, with some of the variables plotted.
The Weather Forecast App for Renewable Energy Prediction will help its users, in particular owners of renewable energy assets, to optimize the energy generation based on different parameters:
● For Solar Energy: predicted solar radiation, cloud cover, UV index, and expected sunlight hours.
● For Wind Energy: wind speed, direction, wind gust forecasts, as well as optimal wind conditions for turbines.
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