Adaptive Methods for Energy Forecasting of Production and Demand of Solar-Assisted Heating Systems

Solar-assisted heating systems use the energy of the sun to supply consumers with renewable heat and can be found all over the world where heating of buildings is necessary. For these systems, both heat production and heat demand are directly related to the weather conditions. In order to optimally plan production, storage, and consumption, forecasts for both the future heat production of the thermal solar collectors as well as the future heat demand of the connected consumers are essential. For this reason, this contribution presents adaptive forecast methods for the solar heat production and the heat demand of consumers using weather forecasts. The developed methods are easy to implement and therefore practically applicable. The final verification of the methods shows good agreement between the predicted values and measurement data from a representative solar-assisted heating system.