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Quantification of predictive capabilities of a new empirical model for a variable speed heat pump system trained with sparse data.

Number: 2285

Author(s) : YOUSAF S., BRADSHAW C., KAMALAPURKAR R., SAN O.

Summary

The importance of energy conservation has greatly increased to promote the decarbonization of buildings. This has resulted in significant interest in variable-speed heat pumping systems with improved efficiency. This paper formulates and evaluates a variable heat pump system model compatible with Building Energy Modeling (BEM) software like EnergyPlus. The model uses as inputs the indoor and outdoor temperatures along with indoor supply air and compressor speed of the heat pump system to predict the heating capacity and coefficient of performance (COP) with 10 trained coefficients each for capacity and COP prediction. The model predictions are compared against experimental data from two, state-of-the-art, variable-speed heat pumps. The model can predict the capacity and COP of the variable heat pump system under 3.5% Mean Absolute Percentage Error (MAPE).

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  • Original title: Quantification of predictive capabilities of a new empirical model for a variable speed heat pump system trained with sparse data.
  • Record ID : 30033190
  • Languages: English
  • Subject: Technology
  • Source: 2024 Purdue Conferences. 19th International Refrigeration and Air-Conditioning Conference at Purdue.
  • Publication date: 2024/07/17

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