Simplifications in the Optimization of Heat Pumps and Their Comparison for Effects on the Accuracy of the Results †.
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| Title: | Simplifications in the Optimization of Heat Pumps and Their Comparison for Effects on the Accuracy of the Results †. |
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| Authors: | Görgen, Maurice1 (AUTHOR) maurice.goergen@hs-niederrhein.de, Zaubitzer, Louisa (AUTHOR), Alsmeyer, Frank (AUTHOR) |
| Source: | Energies (19961073). Feb2026, Vol. 19 Issue 3, p635. 17p. |
| Subject Terms: | *Heat pump efficiency, *Compressor performance, *Standard deviations, *Approximation theory, *Reduced-order models, *Comparative studies |
| Abstract: | This work presents a model that calculates temperature-dependent heat pump performances as a circular heat pump process as a reference model. The model is then systematically simplified by making assumptions or applying functional approximations to key variables. These simplifications include linearization of the substance database calculations and modeling of the compressor efficiency as a function or constant. The effects of these simplifications on the accuracy of results are quantified and compared with other modeling approaches from the literature suitable for linear and bilinear optimization issues. Initial comparisons show that the root mean square error of the model achieves better results than comparable methods. While the root mean square error of the COP in linearized models in the compared literature ranges from 0.433 to 1.233, it can be improved to a maximum of 0.335 using the approach presented. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| Abstract: | This work presents a model that calculates temperature-dependent heat pump performances as a circular heat pump process as a reference model. The model is then systematically simplified by making assumptions or applying functional approximations to key variables. These simplifications include linearization of the substance database calculations and modeling of the compressor efficiency as a function or constant. The effects of these simplifications on the accuracy of results are quantified and compared with other modeling approaches from the literature suitable for linear and bilinear optimization issues. Initial comparisons show that the root mean square error of the model achieves better results than comparable methods. While the root mean square error of the COP in linearized models in the compared literature ranges from 0.433 to 1.233, it can be improved to a maximum of 0.335 using the approach presented. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 19961073 |
| DOI: | 10.3390/en19030635 |
