Double-Target Based Neural Networks in Predicting Energy Consumption in Residential Buildings

Interaction Effect of Room Size and Opening on Trombe Wall Performance in Sichuan–Tibet Alpine Valley Areas

The Trombe wall (T-wall) system is one of the most effective systems for passive solar energy utilization technology, which is of great significance for the alleviation of the energy crisis and the protection of the environment. Taking as an example Tibetan dwellings in the Sichuan–Tibet alpine valley which have installed T-walls for heating, the effects of the length of the room (Factor A), the width of the room (Factor B), the width of the opening on the north wall of the room (Factor C), and the distance from the lower edge of the opening to the floor (Factor D) on the indoor air temperature and room energy consumption are studied by orthogonal experiment and numerical simulation. Results show that the four factors all have a significant effect on the two analysis indicators. The rankings of the factors are consistent for their impact on the two analysis indicators, as, in both cases, Factor A > Factor B > Factor C > Factor D. Therefore, the influence of room configuration cannot be ignored in the optimization of T-wall design. Additionally, the optimal parameter combination for the highest indoor temperature and low energy consumption in winter is also proposed. This research can further improve the study of T-walls, and provide a reference for the thermal environment design of buildings.

Decreasing the Battery Recharge Time if Using a Fuzzy Based Power Management Loop for an Isolated Micro-Grid Farm

An isolated micro-grid has different requirements from the traditional power grids. Several energy sources may be linked for the purpose of sharing load demand without being linked to the grid. The isolated micro-grid is made up of at least one energy generator, an energy storage system, and a load portion. Because there are several energy sources and a range of models, the power flow must be managed to ensure the safety of all hardware. Monitoring the flow of power from multiple energy sources necessitates adherence to many parameters and other requirements. As a result, the goal of this work is to identify a worthwhile solution for providing the appropriate portions with the necessary power while also obtaining the necessary energy from other sources. The approach is based on the fuzzy logic controller, which is an intelligent technology. This regulator is used in an efficient process that tries to control all of the equipment in the isolated micro-grid under investigation. The MATLAB/Simulink platform is employed for simulating this proposed system, and then, the depicted results were discussed and compared. Showing the traditional relay control, the standard PI regulator, and a neural control combination process, the achieved results prove that it is possible to reduce the battery recharge time to half; if the proposed fuzzy controller is used. Then, the established controller specifications have been used for evaluating the energy performances of the hybrid energy system under a real case situation in a specific location in the world. Consequently, the obtained results prove that this proposal power management system will be largely beneficial for such energy storage applications and an energy yield can be assured during all climatic conditions and specifications.

Energy/Economic Analysis and Optimization of On-Grid Photovoltaic System Using CPSO Algorithm

Today, the use of renewable energy is increasing day by day, and this development requires the optimization of these technologies in various dimensions. Solar systems have a higher acceptance due to their high availability and accessibility; the most common solar technology is photovoltaic cell. In this research, modeling was done to achieve the most economically optimal arrangement of photovoltaic panels, inverters, and module placement to generate more electrical energy by considering economic parameters, for which the CPSO algorithm was used. Four different combinations of module and inverter were studied in this research, among which the second combination, which included PV module type one and inverter type two, was the best case. One of the significant results of the present study is 191,430 kWh of electrical energy during the studied year by the solar cell connected to the grid, which requires $42,792,727 to produce.

Energy Recovery in Air Conditioning Systems: Comprehensive Review, Classifications, Critical Analysis, and Potential Recommendations

Energy has become the backbone of humanities daily activities. Heating, ventilating, and air conditioning systems (HVAC), which consume around 39% of energy in the residential sector, have turned into an essential constituent for providing fresh air, especially after COVD-19, not only in hospitals but also in any simple construction. Thus, decreasing this percentage or recovering part of the energy lost is an essential issue in today’s energy management scenarios. In this context, the present manuscript suggests a comprehensive review, classifications, critical analysis, and potential recommendations for energy recovery in air conditioning systems. It classifies energy recovery into two main categories: using lost energy for external uses, such as heating domestic water, or with other devices; and using lost energy for internal uses, such as the hot airflow which can be reused again for increasing efficiency of HVAC. In addition, this paper presents a summary of previous research and undertakes a review of the devices used for recovering energy. Furthermore, this review identifies superior devices in terms of climate and weather conditions. These objectives are accomplished by investigating around 190 published papers to conclude that energy recovery devices show a considerable effect on energy consumption in HVAC, mainly the heat pipe, fixed plate, and rotary wheel devices.