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On the Influence of Solar Radiation on Heat Delivered to Buildings for Heating

doi: 10.3390/en14040851
Nowadays, the attention of designers and service providers is especially focused on energy efficiency and integration of renewable energy sources (RES). However, the knowledge on smart devices and automated, easily applicable algorithms for optimizing heating consumption by effectively taking advantage of solar heat gains, while avoiding overheating, is limited. This paper presents a simple method for taking into account the influence of solar heat gains in the form of solar radiation for the purposes of forecasting or controlling thermal power for heating of buildings. On the basis of field research carried out for seven buildings (five residential buildings and two public buildings) during one heating season, it was noticed that it was justified to properly narrow down the input data range included in the building energy model calculations in order to obtain a higher accuracy of calculations. In order to minimize the impact of other external factors (in particular wind speed) affecting the heat consumption for heating purposes, it was recommended to consider the data range only at wind speeds below 3 m/s. On the other hand, in order to minimize the impact of internal factors (in particular the impact of users), it was suggested to further narrow down the scope of the input data to an hour (e.g., 10–14 in multi-family residential buildings). During these hours, the impact on users was minimized as most of them were outside the building.
Technology, integration of RES, solar radiation, T, building energy model, prediction methods, solar heat gains
Technology, integration of RES, solar radiation, T, building energy model, prediction methods, solar heat gains
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).4 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
