Estimation On Natural Energy Resources

The use of meteorological models and machine learning/data mining methods to estimate (to forecast) the availability of renewable energy sources like wind, water flow and sunlight, and of the amount of energy to be generated from them, as well as the consumption of fossil fuel resources such as natural gas

Product Properties:

• Making weather forecasts by WRF which is an open-source digital weather forecast model
• Automatic data collection from national (such as Directorate General of Meteorology) and international organizations (such as ECMWF) providing meteorological data
• Use of machine learning algorithms such as artificial neural networks and support vector machines to estimate short-term (48 hours) wind power
• Use of hydrological models and machine learning algorithms for water flow estimation
• Applicability of the said models and algorithms for the solar power estimation and natural gas consumption/demand estimation