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This study was supported by a research project (POIR.04.01.02-00-0012/18), financed from European Funds (under the Intelligent Development Program) by the Polish National Centre for Research and Development.
Throughout the world there is an ongoing emphasis on the implementation of modern technologies and services to reduce the carbon footprint and increase the energy efficiency of existing and new buildings. Of particular interest are energy-efficient measures that can be easily implemented in existing building stock and at a low cost, such as a forecast controller for heating systems. However, there is a lack of detailed measured data for assessing the influence of varying outdoor conditions on energy savings from a heating system controlled by a forecast controller. The work aimed to assess the influence of variations in solar insolation and outdoor air temperature on the supply temperature, power demand, and heat consumption within thirteen buildings equipped with a forecast control system. The application employs simple correlations, utilizing an equivalent outdoor temperature derived from an online weather prediction application (API) leveraging the data from nearby meteorological stations. The algorithm utilises the weather predictions for changes in outdoor conditions, such as wind speed, temperature, and solar insolation, to optimise the conditions of the heat supplied to buildings.
The field research was conducted for one year. It was found that the use of the forecast controller in four public buildings and nine residential buildings reduced heat consumption by an average of 9.0% and 11.8%, respectively, for the case when the variations of the outdoor temperature or the solar insolation were taken into account independently. Higher energy savings (16.5%) were achieved for the case when the outdoor temperature increase as well as solar insolation were taken into account at the same time in the process of forecast control of the heating system.