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• An advanced MPC strategy using MILP solver is developed for cooling system with cold storage device in data center. • The improved performance of MPC is evaluated through field test and simulation. • The annual PUE of MPC strategy decreased by 0.018 compared to Baseline strategy. • The influence of model mismatch on control performance is quantified. Data centers facing huge energy consumption challenges, the chiller is one of the main energy expenditure equipment. This study proposed a novel efficient operation strategy for chillers integrated with cold water storage technology. An advanced model predictive control (MPC) was developed to regulate the running parameters of the chillers and cold water storage device, targeting the maximum energy efficiency of cooling system. Specifically, the mixed integer linear programming (MILP) algorithm was constructed in MPC with low computer calculation cost to solve the optimization problem. The performance of the MPC strategy was validated through an actual data center test located at Guangzhou city and further comprehensively assessed through annual simulations. The relative error in terms of refrigeration capacity and cooling capacity of cold water storage device between simulation and field test was less than 5 %. During the on-site testing, compared with a Baseline strategy, the coefficient of performance (COP) of the MPC strategy increased by 1.96 on average with the cooling system energy consumption reduced by 5.8 %, and the power usage effectiveness (PUE) was reduced by 0.013. The annual PUE decreased by 0.018 and the annual electricity cost decreased by 21 % when the IT power was 4570 kW based on the simulation. In addition, the effect of model mismatch was quantified by setting the deviation degree of the chiller partial load rate (PLR). [ABSTRACT FROM AUTHOR]

This paper explored the application of model predictive control (MPC) technology to the TBSs hybrid free cooling system with latent heat thermal energy storage (LHTES) unit for minimizing the building operational cost without sacrificing temperature requirements. First, the system was briefly introduced and the dynamic thermal process models of building structure and LHTES unit were developed. Then, a hierarchical control structure with dynamic multi-swarm particle swarm optimization was presented to address the dimensional challenge and discontinuities in control variables. Due to the considerable decrease of optimization variable space, the method presented in this paper enables long-term simulation and application in a real controller. Simulations were carried out based on a typical TBS building located in Beijing, China. The total energy consumption of the cooling system and the control quality of indoor air temperature were used as the criteria to evaluate the performance. Compared to a defined baseline case, the optimal control method can achieve significant energy saving, i.e. up to 18%. The impacts of the size of LHTES unit and the type of building structure were discussed, as well. The active and passive heat capacity both played a catalytic role in performance of MPC. Additionally, an uncertainty analysis demonstrated that the proposed approach has strong robustness and can handle quite high errors in forecasting building disturbances from energy consumption level. In summary, the knowledge and use of the plant system and future disturbances make MPC a powerful control tool for TBS buildings for maximizing the use of renewable energy sources. [ABSTRACT FROM AUTHOR]

A refrigeration system using phase change material (PCM) with six operating modes is proposed to reduce the cooling energy use of energy-demanding spaces such as data centers and telecommunication base stations. PCM is used to store the cold of outdoor air (OA) and/or that produced by vapor compression refrigeration (VCR) at night, and to release the stored energy for indoor cooling during the daytime. Real-time space cooling and cold charging by VCR can be accomplished simultaneously. Free cooling from OA can provide significant energy saving for space conditioning. A prototype system using a commercially available PCM was developed and tested to investigate the system performance and operation characteristics. The temperatures of air, water and refrigerant were measured along with the refrigerant pressure. The study calculates and analyzes the refrigerating capacity, cooling capacity, cold storage rate, supplied cold, stored cold, and the coefficient of performance (COP) upon the measurements. Experimental results indicate that the proposed refrigeration system can perform the requested tasks in a stable manner. The paper further compares the operating performances with the cold from OA and from VCR. It is found that under the outdoor temperature of 15 °C, OA appears to be more energy-efficient than VCR when the stored cold is less than 5.8 MJ, but it takes more time to charge the cold. [ABSTRACT FROM AUTHOR]

Inefficient cooling systems and rudimentary control methods are accountable for the significant cooling energy consumption in telecommunication base stations (TBSs). To address this issue, our study explores the performance of model predictive control (MPC) technology over a hybrid cooling system with ventilation and air-conditioning cooling. Specifically, a discrete particle swarm optimization (DPSO) algorithm is adopted in the MPC to handle the discontinuity and nonlinearity involved in the model built upon a state-space structure. Simulations are performed for a typical week during a cooling season. Moreover, we observe that a model mismatch could hinder the actual performance of MPC; thus, this study initiatively quantifies the impact of model mismatch by setting different coefficients of performance (COP) on the air-conditioner. The results show that the structured MPC has a better performance over conventional control methods, with an average reduction of 34% daily cooling energy consumption, while increasing the control accuracy in terms of maximum deviation from the desired temperature range. It is also found that a higher degree of model mismatch can lead to a higher performance degradation, either on the total energy consumption or on the room temperature deviation. [ABSTRACT FROM AUTHOR]

Ventilation system with a latent heat thermal energy storage (LHTES) unit can be used to reduce building energy consumption, which stores the coldness of nighttime outdoor air in the LHTES unit and releases it to cool the fresh air during the daytime. The potential energy saving through the use of the system over a conventional ventilation system, however, has seldom been quantitatively evaluated. This study develops and validates a computational heat transfer model of the system, which takes into account two-dimensional heat transfer in phase change material (PCM). The effect of PCM melting temperature on the melted fraction of LHTES unit is investigated to determine the optimum melting temperature. This study then calculates and evaluates the energy saving potential of the LHTES system in summer for eight cities located in four different climate zones of China. The energy saving potential is assessed in terms of cooling energy supply, cooling energy supply ratio, net electricity saving and electricity saving ratio. The results show that the seasonal average cooling energy supply ratio varies from 39% to 194%, with a mean value of 85%, and the seasonal average electricity saving ratio ranges from 26% to 165%, with a mean value of 68%. [ABSTRACT FROM AUTHOR]

Loop thermosyphon system is an efficient cooling system for energy saving in data center. It is necessary to investigate the performance of the loop thermosyphon system filled with alternative refrigerants to prompt its application. In this paper, a R32 loop thermosyphon system is experimentally investigated in an enthalpy difference laboratory for its performance. R22 and R134a are also used for comparison. The results show that the optimal filling ratio of R22, R134a and R32 is the same (37.3%). At the optimal filling ratio, the flow stability of R32 is obviously better than those of R22 and R134a. When cold water temperatures are 10–22 °C, the cooling capacity of R32 is 5.4–15.6% higher than those of R22 and R134a. After controlling extractor fans, the energy efficiency ratio of R32 is 4.9–206.6% higher than those of R22 and R134a. Moreover, the free cooling potentials of the three refrigerants in five typical climate cities across China are analyzed and compared. Compared with R22 and R134a, R32 has 3.6–11.0% and 18.5–26.7% higher free cooling percentages and annual energy efficiency ratio, respectively; and its annual average partial power usage effectiveness is 0.0012–0.0017 lower than that of other two refrigerants. [ABSTRACT FROM AUTHOR]

• An air-cooled heat pump unit comprising of two constant rotation speed compressors integrated with PCMs is studied. • Electrical energy and electricity charge consumptions are discussed. • A lower indoor temperature results in a higher electricity charge saving ratio. • A higher cold charging temperature has a positive impact on the energy-efficiency. This paper studies the performance of a cold storage heat pump system integrated with phase change materials (PCMs) for space cooling. An air-cooled heat pump unit comprising of two constant rotation speed compressors is selected. The PCM is an organic material that is commercially available, and has a phase change temperature of 10–12 °C. A coupled computational heat transfer model of the heat pump unit, fan coil units, and a cold storage tank filled with PCM slabs is developed. The simulations are performed under the climatic condition of Fuzhou, China. The operational behaviors of the cold charging and discharging processes of the system are analyzed. Furthermore, the overall electrical energy and electricity charge consumptions at various indoor temperature set points are compared. The results indicate that, the electrical energy consumption of the cold storage heat pump system increases as the indoor temperature increases. However, there is very little difference in the electrical energy consumption of the conventional heat pump system and the cold storage system. While under the demand tariff, the electricity charge saving ratio of the cold storage system over the conventional system is 9.07%-11.28%. In general, as the indoor temperature set point reduces, the electricity charge saving ratio increases. Moreover, the effect of cold charging temperature is also discussed. It is found that higher cold charging temperature consumes less electrical energy, however, takes longer to store the same amount of cold, and the differences relies on the required amount of cold. [ABSTRACT FROM AUTHOR]

• The necessity and uniqueness of TES for data centers are discussed. • TES units and TES integrated cooling systems in data center are summarized and classified. • The designs and performance characteristics of TES units and TES integrated cooling systems in data center are analyzed. • Main trends in TES developments and applications are summarized when utilized in data center. Data center consumes a great amount of energy and accounts for an increasing proportion of global energy demand. Low efficiency of cooling systems leads to a cooling cost at about 40% of the total energy consumption of a data center. Due to specific operation conditions, high security and high cooling load is required in data center. To achieve energy saving, cost saving and high security, novel cooling systems integrated with thermal energy storage (TES) technologies have been proposed. This paper presents an extensive overview of the research advances and the applications of TES technologies in data centers. Operating conditions, energy mismatch and requirement of high security in data center were overviewed. Principles and characteristics of TES technologies were discussed. Applications of passive TES coupled air flow and applications of active TES integrated cooling system are summarizes, and the design and performance of these TES integrated thermal systems are analyzed, with a focus on energy saving, cost savings and high security. [ABSTRACT FROM AUTHOR]

Abstract: This study deals with predicting the performance characteristics of a reversibly used cooling tower (RUCT) under cross flow conditions for heat pump heating system in winter using artificial neural network (ANN) technique. For this aim, extensive field experimental work has been carried out in order to gather enough data for training and prediction. After back-propagation (BP) training combined with principal component analysis, the three-layer ANN model with a tangent sigmoid transfer function at hidden layer with 11 neurons and a linear transfer function at output layer was obtained. The predictions agreed well with the experimental values with a satisfactory correlation coefficient in the range of 0.9249–0.9988, the absolute fraction of variance in the range of 0.8753–0.9976, and the mean relative error in the range of 0.0008–0.54%, moreover, the root mean square error values for the ANN training and predictions were very low relative to the range of the experiments. The results reveal that ANN model can be used effectively for predicting the performance characteristics of RUCT under cross flow conditions, then providing the theoretical basis on the research of heat and mass transfer inside RUCT, which is important for design and running control of the RUCT system. [Copyright &y& Elsevier]

Abstract: The paper presents a field study of occupants’ thermal comfort and residential thermal environment conducted in an urban and a rural area in Hunan province, which is located in central southern China. The study was performed during the cold winter 2006. Twenty-eight naturally ventilated urban residences and 30 also naturally ventilated rural residences were investigated. A comparative analysis was performed on results from urban and rural residences. The mean thermal sensation vote of rural residences is approximately 0.4 higher than that of urban residences at the same operative temperature. Thermal sensation votes calculated by Fanger’s PMV model did not agree with these obtained directly from the questionnaire data. The neutral operative temperature of urban and rural residences is 14.0 and 11.5°C, respectively. Percentage of acceptable votes of rural occupants is higher than that of urban occupants at the same operative temperature. It suggests that rural occupants may have higher cold tolerance than urban occupants for their physiological acclimatization, or have relative lower thermal expectation than urban occupants because of few air-conditioners used in the rural area. The research will be instrumental to researchers to formulate thermal standards for naturally ventilated buildings in rural areas. [Copyright &y& Elsevier]