The presented paper dealt with the concept of an innovative manifold header for evacuated tube solar collectors. The proposed concept eliminates the drawbacks of conventional manifold headers, especially the serial connection of heat pipes that operate under uneven conditions. The advantage of the proposed design of the manifold header is also an increase in the heat exchange surface and the possibility of conducting the heat transfer media flow in a parallel flow arrangement, which increases the overall efficiency. The concept of the manifold header was evaluated on five variations of design with the use of the computational fluid dynamics (CFD) analysis. The results of the CFD analysis confirmed the functionality of the concept and also enabled the selection of the most suitable design elements, which were incorporated into the final design of a manifold header in the pre-prototype phase of manufacturing.

The energy storage field is nowadays a highly ranking topic. This research deals with the installation and analysis of the ice storage system which combines heat pump, solar absorber, and ice storage tank (phase change material—PCM). This system uses a special kind of solar absorber – header pipes (HDP), which have no thermal isolation compared to the common solar absorber. Thanks to that the HDP, pipes can absorb thermal energy not only from the sun but also from the environment. The rain or snow also affects heat exchange. All that is provided by one technical device. The system can store thermal energy gained from the solar absorber into the ice storage tank for future usage. Research works with data from the real operation, for a period of the year covering all working phases/modes of the system. The analysis of the data led to the identification of several specific modes of the system, especially from the processes taking place in the PCM storage tank during its charging and discharging at various time stages of operation of the whole system. The installation and analysis of the ice storage system probably took place for the first time in Slovakia and Slovak Republic’s conditions. Besides, this system was not installed on a new low-energy house, but on an older family house with thermal insulation. The aim of this installation was also to demonstrate the usability of the ice storage system in an older house and potentially reduce the homeowner’s fees thanks to new technology with higher efficiency. We managed to comprehensively analyze and describe the operation of this system, which also appears to be highly efficient even in a family house with a lower energy certificate, than today’s new low-energy buildings. The results showed a significant efficiency difference in favor of the ice storage system compared to conventional heating systems. The total analysis time was 1616 h and the total efficiency of this heating system—the seasonal coefficient of performance (SCOP) was 4.4. Compared to the average SCOP 3.0 of conventional heating systems for new low-energy houses, the total efficiency increased by 46.6%. These results could therefore be considered as beneficial, especially if we take into account that this system was installed on an approximately 40-year-old family house. The analyzed ice storage system is still working today. The main goals of this paper were to describe the heat pump’s duty cycle with ice storage (PCM) based on real-life data and bring a detailed description of the heat transfer medium behavior at various phases of storing/utilizing heat in the vertical ice storage’s profile for increasing efficiency.

Sales of electric cars and vehicles (EVs) have recently been showing a rapidly growing trend. In connection with rising electricity prices as well as social pressure on the environmental impacts of electromobility, there is also increasing interest of EV owners in the ecological source of electricity. The largest group of owners of EVs are residents of family houses, so, logically, they focus their attention on the possibility of using photovoltaic (PV) charging systems for EV charging. The design of the PV system for supporting EV charging is problematic due to several input parameters in the calculation of energy needs and due to the inconsistencies of electricity generation with normal electric vehicle (EV) charging time. While the PV system produces electricity during the day, family homeowners require charging EVs mainly at night. This requires batteries as part of a PV system. The optimal design of the PV of the battery system must take into account the real consumption of EV, the average daily distance traveled, the location, the weather bridging time, and, last but not least, the investor’s financial situation. The timing mismatch of electricity needs and generation may result in the oversizing or sub-scaling of the PV system depending on the time period for which the investor claims full coverage. With an average daily EV consumption of 10 kWh/day, the overproduction of electricity may be at 8620 kWh per year if it is required to fully cover PV systems in January. Conversely, for the installation of PVs for full coverage in August, the year-round electricity deficit will be 1500 kWh per year. For the analyzed geographical conditions, i.e., Latitude 48.8, the optimum performance of PV system for one-day electricity storage is 3.585 kW. This corresponds to the full coverage of EV consumption in March, the price of the whole system varies from EUR 9000 to EUR 20,000 depending on the type of battery. In addition to the battery price, the required accumulation time for electricity to overcome adverse weather increases the required performance of a photovoltaic system (PVS), which again results in system overshooting and financial loss by not using the generated electricity. This cycle of interdependencies is usually very difficult to adjust optimally. In the contribution, we analyzed the mutual relationships of calculating the performance of a PVS according to the daily consumption of EV and required time of overcoming adverse weather. The input data for the analyses were normal average EV consumption and the number of daily km traveled from 10 to 100 km/day scaled to 10. The optimization process consisted of determining the necessary performance of the PVS and its production in the event of a requirement to ensure full energy demand in each month. In addition, different types of batteries that influence the investment price enter into optimization analyses. This depends on the energy density of a given battery, the depth of discharge, capacity, and type. The result of this research is a computational model for determining a new indicator—we called it the monthly deviation factor. This indicates the degree of oversizing or undersizing of the PV system in relation to the stated factors.