Photovoltaic-thermal (PVT) technology refers to the integration of a photovoltaic (PV) and a conventional solar thermal collector, representing the deep exploitation and utilization of solar energy. In this paper, we evaluate the performance of a solar PVT cogeneration system based on specific building energy demand using theoretical modeling and experimental study. Through calculation and simulation, the dynamic heating load and electricity load is obtained as the basis of the system design. An analytical expression for the connection of PVT collector array is derived by using basic energy balance equations and thermal models. Based on analytical results, an optimized design method was carried out for the system. In addition, the fuzzy control method of frequency conversion circulating water pumps and pipeline switching by electromagnetic valves is introduced in this paper to maintain the system at an optimal working point. Meanwhile, an experimental setup is established, which includes 36 PVT collectors with every 6 PVT collectors connected in series. The thermal energy generation, thermal efficiency, power generation and photovoltaic efficiency have been given in this paper. The results demonstrate that the demonstration solar PVT cogeneration system can meet the building energy demand in the daytime in the heating season.

Statistical modeling and analysis of satellite failure is an effective way to master the satellite operating status, and the results can provide important theoretical basis for the performance improvement of satellite reliability. In view of the dual-period characteristics of satellite failure distribution, a 2-Weibull segmented model for statistical modeling of satellite failure has been proposed in this paper. In order to improve the robustness of the parameter estimation for 2-Weibull segmented model, a parameter estimation method for 2-Weibull segmented model based on least squares Hough transform algorithm is continued to be proposed in this paper. And the feasibility and effectiveness of the parameter estimation method are verified by simulation experiments. The 2-Weibull segmented model is used for statistical modeling of 1584 satellite failure samples. The results show that, compared with the traditional single Weibull distribution model, the 2-Weibull segmented model proposed in this paper improves the fitting accuracy of satellite failure distribution by 46.15%.

The efficient utilization of solar energy significantly contributes to energy efficiency in buildings. Solar photovoltaic thermal (PVT) heat pumps, a hybrid of photovoltaic and solar-assisted heat pumps, have demonstrated a significant development trend due to their multi-generational capacity for heating, power, and cooling with reliable operational performance. This research work presents and investigates a single-stage compression PVT heat pump system, along with the operation principle of the system’s heating and power co-generation throughout the winter and transitional season. The construction of the testing facility, data reduction, error analysis, and performance evaluation indices of the system are all explained theoretically. A continuous experiment research project focusing on system heating and power performance was carried out in Dalian during the transition season (November in this study) and winter season (December in this study) as part of our investigation into the potential uses for space heating, residential hot water, and power supply in northern China. The findings of the experimental research demonstrate that the proposed system can generate electricity and heat at high efficiency during the winter and transitional seasons, with long-term stable performance. The system’s average heating COP_t is 5 during the transitional season and 4.4 during the winter season. Meanwhile, the average photovoltaic power efficiency under both weather conditions is 11.9% and 10.2%, with a peak value of 15.7% and 12.0%, respectively. Additionally, the system compression ratio’s variation range is 2 to 3.88, which is lower than the standard heat pump system. As a result, the entire system heating operating process remains constant.

Adaptive transparent system (ATS) is an aspiring and effective building system that can adapt itself through environmental changes in spontaneous and reversible ways. It proposes an automatic and real-time response to indoor and outdoor conditions by increasing building energy efficiency and user comfort. This research presents a critical analysis to provide a preference order of the smart materials being used in the adaptive transparent systems. The approach of using smart material technologies in the building façades is discussed as the promising research direction for the future. A comprehensive literature review is conducted to identify the smart materials used in adaptive transparent systems along with their properties. Seven types of smart materials that are aerogel (AG), phase change material (PCM), photovoltaic (PV), electrochromic (EC), thermo-chromic (TC), thermo-tropic (TT), and liquid crystal polymers (LCP) are selected based on evaluation criteria determined by the literature. The identified criteria are bulk density (BD), thermal conductivity (TCd), sound insolation (SI), fire retardation (FR), heat transfer coefficient (HTC), solar transmittance (ST), air purification (AP), annual energy saving (AES), cost saving (CS), ultraviolet (UV)/near infrared (NIR) control (UNC), and embodied carbon (EC). The identified seven smart materials are investigated with the help of two multi-criteria decision-making (MCDM) techniques named analytical hierarchical process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) for analysis and ranking of materials. Results of the analysis demonstrate that PV is the most optimum material for adaptive transparent systems while others are ranked according to their performance.