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Girard, A., Gago, E. J., Muneer, T., & Caceres, G. (2015). Higher ground source heat pump COP in a residential building through the use of solar thermal collectors. Renew. Energy, 80, 26–39.
Abstract: This article investigates the feasibility of achieving higher performance from ground-source heat-pumps (GSHP) in space heating mode through the use of solar thermal collectors. A novel simulation tool for solar-assisted ground-source heat-pumps (SGSHP) is presented with an analysis of the influence of solar collectors on the improvement of heat pump performance. Solar radiation and climate temperature data of 19 European cities were used to perform simulations of SGSHP and GSHP systems considering a typical residential house. Overall performance coefficients (COPsys) varied from northern to southern locations between 4.4 and 5.8 for SGSHP and between 4.3 and 5.1 for GSHP. Results show that solar collectors coupling has more impact on performance improvement in regions that benefit from higher irradiance. However, greater running cost savings are achieved in milder climate conditions. Both heat-pump systems are able to effectively contribute to carbon footprint reductions for residential buildings, especially in countries where fossil fuels are the primary source of electricity generation. SGSHP payback periods are found between 8.5 and 23 years from northern to southern localities, making such heating system an economic heating option. SGSHPs are best suited for high irradiance and cool climate locations such as the mountainous regions in southern Europe. (C) 2015 Elsevier Ltd. All rights reserved.
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Simon, F., Ordonez, J., Reddy, T. A., Girard, A., & Muneer, T. (2016). Developing multiple regression models from the manufacturer's ground-source heat pump catalogue data. Renew. Energy, 95, 413–421.
Abstract: The performance of ground-source heat pumps (GSHP), often expressed as Power drawn and/or the COP, depends on several operating parameters. Manufacturers usually publish such data in tables for certain discrete values of the operating fluid temperatures and flow rates conditions. In actual applications, such as in dynamic simulations of heat pump system integrated to buildings, there is a need to determine equipment performance under operating conditions other than those listed. This paper describes a simplified methodology for predicting the performance of GSHPs using multiple regression (MR) models as applicable to manufacturer data. We find that fitting second-order MR models with eight statistically significant x-variables from 36 observations appropriately selected in the manufacturer catalogue can predict the system global behavior with good accuracy. For the three studied GSHPs, the external prediction error of the MR models identified following the methodology are 0.2%, 0.9% and 1% for heating capacity (HC) predictions and 2.6%, 4.9% and 3.2% for COP predictions. No correlation is found between residuals and the response, thus validating the models. The operational approach appears to be a reliable tool to be integrated in dynamic simulation codes, as the method is applicable to any GSHP catalogue data. (C) 2016 Elsevier Ltd. All rights reserved.
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