This paper focuses on analyzing the thermal environment and optimizing energy consumption in data centers, which has largely omitted from previous studies. The thermal environmental of data centers is simulated and analyzed by utilizing the established "server-rack-room" multi-scale heat transfer numerical model. Based on this, the coupling simulation model of thermal environment and energy consumption in data centers is proposed to explore the relationship between them, and the corresponding optimization strategy is put forward. The energy consumption simulated by energy-environment coupled model and non-coupled model can reach a discrepancy of over 30 %, which indicates that the thermal environment impacts the power consumption of the data center significantly. Besides, the effect of several operational parameters of air conditioning system on the thermal environment and energy consumption of data center is analyzed. Through the particle swarm optimization algorithm, the optimal system parameters, which meet the requirements of thermal environment and lead to the lowest energy consumption, are found for typical cities in different climatic regions. The recommended settings include the supply air temperature of about 24 similar to 26 degree celsius, the air supply volume of 8 m(3)/s, and the temperature difference of about 3.5 degree celsius between the supply air temperature and the supply chilled water temperature. Under the optimized parameter setting, the highest temperature of server decreases to below 71 degree celsius, and the energy saving rate is more than 6 %.

Both the thermal environment of a data center room and the internal thermal environment of a server are of great concern, but it is extremely difficult to build and solve full-scale computational fluid dynamics (CFD) simulation models from room scale to chip scale. In this paper, a multi-scale simulation method for data centers is proposed to achieve this aim by coupling room-level, rack -level, and server-level models. Simulations of the designed working conditions were carried out. The results showed that aisle containment systems improve the server's thermal environment, resulting in a drop in the maximum temperature of the server from 87.5 degrees C to 73.1 degrees C. A multi -scale model of the data center can be used to optimize system operation parameters conveniently and accurately. In this simulation, air conditioning parameters that contribute to energy savings with higher supply air temperatures and lower supply air volumes while guaranteeing safe server operation were determined. Moreover, fast and accurate prediction of chip temperature by radial basis function (RBF) networks has been proven to be feasible.

Buildings consume large amount of energy for cooling in summer and heating in winter. A renewable energy-based district heating using seasonal thermal storage can better serve for a lower carbon space heating for buildings. The research objective is to propose a first semi-analytical model of large-scale water tank storage as an efficient and flexible tool for further development of TES. A new idea of "three-zone method" is proposed for detailed heat and mass flow inside water storage with least increase in computational burden and better capture of internal non-uniform thermal distribution. All three modes of charging, discharging and standby are modeled separately with high flexibility. A modified finite cylindrical source model for TES was proposed, for the first time, for transient heat transfer in the ground, which is inspired by analytical model of ground source heat pump. A complete comparison was made between the new semi-analytical model and validated reference data, which shows a good match in temperature profile in different locations. This study will pave a way for a further systematical study on seasonal thermal storage.(c) 2022 Elsevier B.V. All rights reserved.

The unequal heat gain in south and north orientation of a building causes higher energy consumption which should have been avoided. In this paper, an active pipe-embedded building envelope system is proposed to achieve heat redistribution between north and south rooms to reduce building heating load. The system is mainly composed of closed-loop pipes embedded in external walls which will absorb and transfer the solar heat gain from the south façade to the north. On cloudless days, the structure can effectively raise the surface temperature of the north wall, thus reducing the heat loss through the envelope. We present all the mathematical equations and a mathematical model validated against experimental data in the literature. To further check the feasibility of the system, the heat transfer of a pipe-embedded external wall and a conventional wall are compared, with the same configurations under typical weather conditions in five building climate zones of China. The results show that the heating load reduction during heating season for the room adopting this system relative to the one without it is 12.8% for hot summer and cold winter climate. For severe cold climate and cold climate, the heating loads in January are reduced by 4.6% and 8.7%, respectively. The system plays a minor role in reducing building energy consumption in the hot summer and warm winter zone. Besides, energy consumption of building in summer can also be reduced, although not as effectively as in winter. This study may guide a better design and control of low energy building in further research and practice.

Heat transmit between ambient and indoor space passively through building envelope. This heat flow intensity can be reduced by using insulations and eliminated by conventional air conditioner, which causes huge amount of energy. In this study, a new concept is proposed for a new active building envelope system that can realize heat gain/loss control and in some senses the conventional air conditioner system could be saved, because it is shown that the building envelope itself could be an air conditioner. It should be specially noted that, we can set parameter Qw in this system to determine how much extra thermal energy you want from the new building envelope. It is based on the combination of photovoltaic (PV), thermoelectric modules (TEM), energy storage and control algorithms. Five types of systems, namely PV + TE (S1), Grid + TE (S2), PV + Grid + TE (S3), PV + Battery + TE (S4) and PV + Grid + Battery + TE (S5) are studied. It is found that in all the five systems, there is a typical optimum setting of thermal load for each one of them with minimum annual power consumption.