Topical article: A heat pump system control based on solar gain prediction


How is the operation of a heat pump controlled? In Central and Northern Europe, the answer to that question is often “through the measured outdoors temperature”. Basically, this means that the system supply temperature is defined so that it covers the supposed heating demand caused by a specific ambient temperature.

Since also other factors such as heating distribution and the building envelope are considered when the system is installed, this control strategy gives roughly the correct supply temperature, on average. But other factors are not included – leading to periodic overheating. Such factors are e.g. solar radiation and heat generated by the inhabitants’ activities. The Swedish project “Smart Control Strategies for Heat Pump systems” developed a control algorithm that takes some of these factors into account.

The project focused on the improvement of heat pump heating systems with the traditional type of control in single-family houses. Several possible adjustments to the control system were evaluated, and their impact was analyzed. Examples of such adjustments are prediction of user internal gains, ambient temperature, wind and solar radiation. All these aspects might be implemented in both new and existing controllers of heat pump systems. Of course, additional sets of data are necessary. A model was developed within the project for prediction of the daily solar radiation in Stockholm, Sweden. This is a combination of the theoretical sun radiation and the average cloudiness value provided by the weather forecast. For each day, in particular, the predicted energy gain due to these two factors is calculated.

The aim of the project was to find out if it is possible to decrease the amount of electric energy used by the heat pump while maintaining the overall thermal comfort. To this end, simulations of heat pump installations in single-family buildings were performed. And the results imply that it is indeed possible to obtain energy savings with such a control algorithm. The results are actually quite promising: the annual energy saving could be as high as 9%. And for some months it could even be 25%.

 

Davide Rolando and Hatef Madani, Sweden

The text has been shortened by the HPC team
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