This paper presents a distributed mathematical model for a carbon dioxide direct expansion solar-assisted heat pump used to heat bath water. The main components are a gas cooler, a needle valve, an evaporator/collector, and a compressor. To develop the heat exchange models, mass, energy, and momentum balances were used. The model was validated for transient as well as steady state conditions using experimental data. A reasonably good agreement was observed between the predicted temperatures and experimental data. The simulations showed that the time step required to demonstrate the behavior of the heat pump in the transient regime is greater than the time step required for the steady state. The results obtained with the mathematical model revealed that a reduction in the water mass flow rate results in an increase in the water outlet temperature. In addition, when the carbon dioxide mass flow rate is reduced, the compressor inlet and outlet temperatures increase as well as the water outlet temperature.

Technical literature shows that there is a performance gap between a simulated design and the actual building performance, especially given the differences between the post-occupation routines and those provided in the design phase. This paper aims to analyze the differences between the electric energy consumption prediction of a call center building located in Belo Horizonte, Brazil, using (a) a schedule based on routines provided by the air conditioning designer made in order to establish the system loads and to define the system equipment and (b) a schedule based in the employee's routines provided by the owners of the building. First, the simulation results were compared to the mean measured building energy consumption and, differently from the first schedule, when the second schedule was used, a Normalized Mean Bias Error (NMBE) of 5% was met which is considered a prediction acceptable by the ASHRAE Guideline 14-2002 [Measurement of Energy and Demand Savings (American Society of Heating, Refrigerating and Air-conditioning Engineers, 2002)]. Afterwards, it was verified how the two occupation schedules influenced the building classification according to the Brazilian Governmental Building Energy Efficiency Labeling. In this case, the two different schedules resulted in a difference in electric energy consumption of 10.9%, leading to a difference of one level in the classification. This fact clearly demonstrates the importance of a correct definition of occupation and equipment usage in the energy performance prediction of a building.