Hybrid energy systems combine multiple energy sources and storage technologies to enhance performance and meet diverse energy needs. Hybrid heat pump systems are particularly suitable for heating and cooling buildings in rural areas. Air-source heat pumps have two well-known disadvantages during the coldest period of the year, when the building’s heating load is at its peak: the heat pump’s capacity is reduced and it needs to perform defrost cycles. A potential solution is to size the heat pump to cover only a portion of the peak load and to use a second heat generator in a hybrid heat pump system. There is a gap in the literature regarding the configurational analysis of hybrid heat pump (HHP) systems, particularly in terms of combining heat pumps and biomass boilers, and evaluating their efficiency, economic aspects, and environmental impact. Thus, in this research, a dynamic model of a HHP system, consisting of an air-to-water heat pump paired with a biomass boiler as a backup, is presented. Various configurations of the HHP system have been developed to evaluate key performance indicators, such as efficiency, emissions, operational costs, and other relevant factors. The findings of this paper indicate that the energy performance of HHP systems is significantly affected by the system layout, heat pump size, cut-off temperature, and the control algorithm used to activate the heat generators. Moreover, series operation of HHP systems is not only more efficient than parallel operation but also results in lower emissions and reduced operation costs. As expected, the energy loss associated with defrost cycles significantly impacts the overall performance of a hybrid system based on an air-source heat pump. Finally, the impact of the cut-off temperature on the key parameters in the configuration analysis was examined, and the optimal performance of the HHP system, in terms of minimizing operational costs and emissions, was depicted using a heat map diagram.

The impact of the mushy zone parameter ($A_{mushy}$) and the chosen numerical model during the solidification of a commercial paraffin-type phase change material (PCM) in a vertical cylinder under T-history conditions was examined through numerical simulations. The cooling process was modeled using three methods implemented in the CFD software ANSYS Fluent 2020 R2: the enthalpy–porosity method, the apparent heat capacity (AHC) method, and a new model proposed by the authors which incorporates heat capacity directly into ANSYS Fluent. To accurately define the boundary conditions, radiative heat transfer between surfaces was taken into account. Furthermore, the influence of the mushy zone parameter on the simulation accuracy and solidification rate was investigated, with the parameter being treated as a function of the liquid fraction. The results indicate that the proposed model aligns closely with experimental data regarding cooling temperature, offering better predictions compared to the other models. It was observed that temperature varies with time but not with position, suggesting that this model more effectively satisfies the lumped system condition—an essential characteristic of the T-history experiment—compared to the other methods. Additionally, the analysis showed that a higher mushy zone parameter enhances the accuracy of simulations and predicts a shorter solidification time; approximately 11% for the E-p and 7% for the AHC model. Using a variable mushy zone parameter based on the liquid fraction also produced similar results, resulting in an increased solidification rate.

Phase change materials (PCMs) are widely used in various critical applications because of their capacity to store thermal energy and regulate temperature effectively. A review of the literature on PCM solidification and melting simulations reveals that the accuracy of these simulations is highly dependent on the input parameters and underlying assumptions used in the software. Among the key factors influencing precise simulation results are the parameter of mushy zone () and the thermal properties of the material. This study numerically investigated the impact of the and thermal properties on the solidification behavior of a paraffin in the test tube under T‐history conditions. The analysis was conducted using the commercial CFD software ANSYS Fluent and the enthalpy‐porosity method is applied to simulation the solidification process. To accurately reflect the conditions of the T‐history experiment, radiative heat transfer between surfaces was employed for the boundary conditions, ensuring a realistic representation of the experimental setup. An evaluation of four thermal properties—thermal conductivity, density, latent heat, and specific heat—indicates that while an increase in latent heat, density, and specific heat slows down the rate of solidification, an increase in thermal conductivity has the opposite effect, accelerating the solidification process. The results further emphasize that selecting an appropriate value for is crucial for achieving accurate solidification simulations. Increasing from to enhanced the prediction accuracy of the solidification time by 10%. Additionally, the mushy zone parameter significantly affects the shape and progression of solidification. As increases, solidification in the lower layers decreases, concentrating the process more in the layers adjacent to the cold wall.