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1
Hussin, Masnida, Raja Azlina Raja Mahmood, and Mas Rina Mustaffa. "Sensor Communication Model Using Cyber-Physical System Approach for Green Data Center." International Journal of Interactive Mobile Technologies (iJIM) 13, no. 10 (September 25, 2019): 188. http://dx.doi.org/10.3991/ijim.v13i10.11310.
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Energy consumption in distributed computing system gains a lot of attention recently after its processing capacity becomes significant for better business and economic operations. Comprehensive analysis of energy efficiency in high-performance data center for distributed processing requires ability to monitor a proportion of resource utilization versus energy consumption. In order to gain green data center while sustaining computational performance, a model of energy efficient cyber-physical communication is proposed. A real-time sensor communication is used to monitor heat emitted by processors and room temperature. Specifically, our cyber-physical communication model dynamically identifies processing states in data center while implying a suitable air-conditioning temperature level. The information is then used by administration to fine-tune the room temperature according to the current processing activities. Our automated triggering approach aims to improve edge computing performance with cost-effective energy consumption. Simulation experiments show that our cyber-physical communication achieves better energy consumption and resource utilization compared with other cooling model.
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Lachhab, Fadwa, Mohamed Bakhouya, Radouane Ouladsine, and Mohammed Essaaidi. "A context-driven platform using Internet of things and data stream processing for heating, ventilation and air conditioning systems control." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 233, no. 7 (April 9, 2019): 877–88. http://dx.doi.org/10.1177/0959651819841534.
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Control approaches of heating, ventilation and air conditioning systems in buildings have been proposed in the past years for minimizing energy consumption and maintaining occupants’ comfort. However, recent studies have shown that context-driven control approaches using Internet of things and data stream processing technologies could further improve energy saving in heating, ventilation and air conditioning systems. In this article, an intelligent control approach using a state feedback technique is introduced to regulate the heating, ventilation and air conditioning system according to the actual context. The proposed thermal state feedback control was then implemented and deployed in our EEBLab to study its effectiveness in a real-setting scenario. The performance of the proposed control was evaluated in a real test-site by deploying a control card that links the controller with the heating, ventilation and air conditioning system. A smart mobile application for real feedback control was also developed and deployed to dynamically adapt the controller to context’s changes. The mobile application and the heating, ventilation and air conditioning system communicate and exchange data under a data acquisition and visualization platform. In this article, a holistic platform that combines Internet of things and data stream processing technologies was developed and deployed in a real-setting scenario. Experiments have been performed, and results are reported to demonstrate the effectiveness and usefulness of the proposed approach in terms of energy saving while maintaining a comfortable room temperature. The proposed state feedback control outperforms the proportional–integral–derivative and ON/OFF approaches in terms of energy consumption while providing acceptable thermal comfort by allowing a neutral thermal sensation with ± 0.30 of predictive mean vote and less than 7% of predicted percentage of dissatisfaction.
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Feng, Yayuan, Youxian Huang, Haifeng Shang, Junwei Lou, Ala deen Knefaty, Jian Yao, and Rongyue Zheng. "Prediction of Hourly Air-Conditioning Energy Consumption in Office Buildings Based on Gaussian Process Regression." Energies 15, no. 13 (June 24, 2022): 4626. http://dx.doi.org/10.3390/en15134626.
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Accurate prediction of air-conditioning energy consumption in buildings is of great help in reducing building energy consumption. Nowadays, most research efforts on predictive models are based on large samples, while short-term prediction with one-month or less-than-one-month training sets receives less attention due to data uncertainty and unavailability for application in practice. This paper takes a government office building in Ningbo as a case study. The hourly HVAC system energy consumption is obtained through the Ningbo Building Energy Consumption Monitoring Platform, and the meteorological data are obtained from the meteorological station of Ningbo city. This study utilizes a Gaussian process regression with the help of a 12 × 12 grid search and prediction processing to predict short-term hourly building HVAC system energy consumption by using meteorological variables and short-term building HVAC energy consumption data. The accuracy R2 of the optimal Gaussian process regression model obtained is 0.9917 and 0.9863, and the CV-RMSE is 0.1035 and 0.1278, respectively, for model testing and short-term HVAC system energy consumption prediction. For short-term HVAC system energy consumption, the NMBE is 0.0575, which is more accurate than the standard of ASHRAE, indicating that it can be applied in practical energy predictions.
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Arvidsson, Simon, Marcus Gullstrand, Beril Sirmacek, and Maria Riveiro. "Sensor Fusion and Convolutional Neural Networks for Indoor Occupancy Prediction Using Multiple Low-Cost Low-Resolution Heat Sensor Data." Sensors 21, no. 4 (February 3, 2021): 1036. http://dx.doi.org/10.3390/s21041036.
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Indoor occupancy prediction is a prerequisite for the management of energy consumption, security, health, and other systems in smart buildings. Previous studies have shown that buildings that automatize their heating, lighting, air conditioning, and ventilation systems through considering the occupancy and activity information might reduce energy consumption by more than 50%. However, it is difficult to use high-resolution sensors and cameras for occupancy prediction due to privacy concerns. In this paper, we propose a novel solution for predicting occupancy using multiple low-cost and low-resolution heat sensors. We suggest two different methods for fusing and processing the data captured from multiple heat sensors and we use a Convolutional Neural Network for predicting occupancy. We conduct experiments to assess both the performance of the proposed solutions and analyze the impact of sensor field view overlaps on the prediction results. In summary, our experimental results show that the implemented solutions show high occupancy prediction accuracy and real-time processing capabilities.
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Espejel-Blanco, Daniel Fernando, José Antonio Hoyo-Montaño, Jaime Arau, Guillermo Valencia-Palomo, Abel García-Barrientos, Héctor Ricardo Hernández-De-León, and Jorge Luis Camas-Anzueto. "HVAC Control System Using Predicted Mean Vote Index for Energy Savings in Buildings." Buildings 12, no. 1 (January 3, 2022): 38. http://dx.doi.org/10.3390/buildings12010038.
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Nowadays, reducing energy consumption is the fastest way to reduce the use of fossil fuels and, therefore, greenhouse gas emissions. Heating, Ventilation, and Air Conditioning (HVAC) systems are used to maintain an indoor environment in comfortable conditions for its occupants. The combination of these two factors, energy efficiency and comfort, is a considerable challenge for building operations. This paper introduces a design approach to control an HVAC, focused on an energy consumption reduction in the operation of the HVAC system of a building. The architecture was developed using a Raspberry Pi as a coordinator node and wireless connection with sensor nodes for environmental variables and electrical measurement nodes. The data received by the coordinator node is sent to the cloud for storage and further processing. The control system manages the setpoint of the HVAC equipment, as well as the turning on and off the HVAC compressor using an XBee-based solid state relay. The HVAC temperature control system is based on the Predicted Mean Vote (PMV) index calculation, which is used by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) to find the appropriate setpoint to meet the thermal comfort of 80% of users. This method combines the values of humidity and temperature to define comfort zones. The coordinator node makes the compressor control decisions depending on the value obtained in the PMV index. The proposed PMV-based temperature control system for the HVAC equipment achieves energy savings ranging from 33% to 44% against the built-in control of the HVAC equipment, when operating with the same setpoint of 26.5 grades centigrade.
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Magtibay, Oscar Bryan M., Rodelio H. Cabrera, Joselito P. Roxas, and Mark Anthony De Vera. "Green switch: an IoT based energy monitoring system for mabini building in De La Salle Lipa." Indonesian Journal of Electrical Engineering and Computer Science 24, no. 2 (November 1, 2021): 754. http://dx.doi.org/10.11591/ijeecs.v24.i2.pp754-761.
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<p>Building energy management systems (BEMS) are critical tools for managing and controlling a facility's technical systems and services, such as lighting, ventilation, heating, and air conditioning, to ensure that the building operates at peak efficiency while decreasing energy waste. The Mabini Building at De La Salle Lipa has nearly a hundred rooms, 70 of which are used by college students for lecture and laboratory classes. From 7:30 a.m. to 9:00 p.m., these rooms are available. In a daily class schedule, air conditioning units and lights are used an average of 10 hours per day, while fans and power outlets are used an average of 5 hours. Even when no classes are being held, the aforementioned equipment is frequently left open in these rooms. The researchers created and constructed an IoT-based energy monitoring system to monitor and control the lights and outlets in a room. The system will also record the number of kilowatt-hours (kWh) consumed. The system employs NodeMCU, current, and voltage sensors, a Raspberry Pi 3, and the school's existing network to send and receive data from the server. The building administrator will use the collected data to give consumption statistics and reduce the carbon footprint.</p>
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Essa, Mohamed El-Sayed M., Ahmed M. El-shafeey, Amna Hassan Omar, Adel Essa Fathi, Ahmed Sabry Abo El Maref, Joseph Victor W. Lotfy, and Mohamed Saleh El-Sayed. "Reliable Integration of Neural Network and Internet of Things for Forecasting, Controlling, and Monitoring of Experimental Building Management System." Sustainability 15, no. 3 (January 24, 2023): 2168. http://dx.doi.org/10.3390/su15032168.
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In this paper, Internet of Things (IoT) and artificial intelligence (AI) are employed to solve the issue of energy consumption in a case study of an education laboratory. IoT enables deployment of AI approaches to establish smart systems and manage the sensor signals between different equipment based on smart decisions. As a result, this paper introduces the design and investigation of an experimental building management system (BMS)-based IoT approach to monitor status of sensors and control operation of loads to reduce energy consumption. The proposed BMS is built on integration between a programmable logic controller (PLC), a Node MCU ESP8266, and an Arduino Mega 2560 to perform the roles of transferring and processing data as well as decision-making. The system employs a variety of sensors, including a DHT11 sensor, an IR sensor, a smoke sensor, and an ultrasonic sensor. The collected IoT data from temperature sensors are used to build an artificial neural network (ANN) model to forecast the temperature inside the laboratory. The proposed IoT platform is created by the ThingSpeak platform, the Bylink dashboard, and a mobile application. The experimental results show that the experimental BMS can monitor the sensor data and publish the data on different IoT platforms. In addition, the results demonstrate that operation of the air-conditioning, lighting, firefighting, and ventilation systems could be optimally monitored and managed for a smart system with an architectural design. Furthermore, the results prove that the ANN model can perform a distinct temperature forecasting process based on IoT data.
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Sermsuk, Maytungkorn, Yanin Sukjai, Montri Wiboonrat, and Kunlanan Kiatkittipong. "Utilising Cold Energy from Liquefied Natural Gas (LNG) to Reduce the Electricity Cost of Data Centres." Energies 14, no. 19 (October 1, 2021): 6269. http://dx.doi.org/10.3390/en14196269.
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The Office of the National Broadcasting and Telecommunications Commission has reported that, from 2014 to 2018, Thailand’s internet usage has grown six-fold to 3.3 million terabytes per annum. This market trend highlights one of the policies of Thailand 4.0, with the aim of making Thailand a hub for information transfer in ASEAN. As a result, there will be a massive demand growth for data storage facilities in the near future. Data centres are regarded as the brain and heart of the digital industry and are essential for facilitating businesses in organising, processing, storing and disseminating large amounts of data. As the energy demand for equipment cooling contributes to over 37% of the total energy consumption, the data centres of the world’s leading companies, such as Amazon, Google, Microsoft and Facebook, are generally located in cold climate zones, such as Iceland, in order to reduce operating costs for cooling. Due to this reason, the possibility of data centres in Thailand is limited. Beneficially, PTTLNG, as the first liquified natural gas (LNG) terminal in Thailand, has processed the import, receiving, storage and regasification of LNG. The high abundance of cold energy inherently presented in LNG is normally lost to the surroundings during regasification. Presently, PTTLNG’s LNG receiving terminal utilises a heat exchanger with propane as an intermediate fluid to transfer cold energy from LNG to water. This cold energy, in the form of cold water, is then used in several projects within the LNG receiving terminal: (1) production of electricity via an organic Rankine cycle capacity of 5 MWh; (2) cooling the air inlet of gas turbine generators to increase the generator efficiency; (3) replacing refrigerant heating, ventilation and air conditioning systems within buildings; (4) development of winter plantations with precision agriculture to replace imported products. Therefore, this study focuses on the potential and future use for LNG cold energy by performing a thermodynamic and economic analysis of the use of LNG cold energy as a source to produce cold water at 7 °C, with the total cold energy of 27.77 to 34.15 MW or 7934 t to 9757 t of refrigeration depending on the target pressure of the natural gas to replace the conventional cooling system of data centres. This research has the potential to reduce the cooling operation costs of data centres by more than USD 9.87 million per annum as well as CO2 emissions by 34,772 t per annum. In an economic study, this research could lead to a payback period of 7 years with IRR 13% for the LNG receiving terminal and a payback period of 2.21 years with IRR 45% for digital companies.
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Ghali, Abdulrahman Aminu, Rohiza Ahmad, and Hitham Alhussian. "A Framework for Mitigating DDoS and DOS Attacks in IoT Environment Using Hybrid Approach." Electronics 10, no. 11 (May 27, 2021): 1282. http://dx.doi.org/10.3390/electronics10111282.
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The Internet of Things (IoT) has gained remarkable acceptance from millions of individuals. This is evident in the extensive use of intelligent devices such as smartphones, smart television, speakers, air conditioning, lighting, and high-speed networks. The general application area of IoT includes industries, hospitals, schools, homes, sports, oil and gas, automobile, and entertainment, to mention a few. However, because of the unbounded connection of IoT devices and the lack of a specific method for overseeing communication, security concerns such as distributed denial of service (DDoS), denial of service (DoS), replay, botnet, social engineering, man-in-the-middle, and brute force attacks have posed enormous challenges in the IoT environment. Regarding these enormous challenges, this study focuses on DDoS and DoS attacks. These two attacks have the most severe consequences in the IoT environment. The solution proposed in this study can also help future researchers tackle the expansion of IoT security threats. Moreover, the study conducts rigorous experiments to assess the efficiency of the proposed approach. In summary, the experimental results show that the proposed hybrid approach mitigates data exfiltration caused by DDoS and DoS attacks by 95.4%, with average network lifetime, energy consumption, and throughput improvements of 15%, 25%, and 60%, respectively.
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Song, Li Fei, Tao Li, Qi Fen Li, Lin Hui Zhao, Xin Zhao, Lei Zhang, Jia Lin Zhao, and Jing Jing Xu. "Data Center Room Air Conditioning Energy Consumption Analysis." Applied Mechanics and Materials 672-674 (October 2014): 518–21. http://dx.doi.org/10.4028/www.scientific.net/amm.672-674.518.
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In this paper, the Unicom's medium-sized IDC room in a city of northern China is the research object for the study. Based on field research of the room refrigeration conditions, data center room air conditioning system is carried out to optimize and for energy conservation research. Through the analytic methods of energy saving-technology, the best energy saving solutions is explored.
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Stankov, Stanko. "Modern control of mineral wool production process." Chemical Industry 67, no. 2 (2013): 375–84. http://dx.doi.org/10.2298/hemind120428069s.
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In this paper, the control of the plant for mineral wool production consisting of a number of the technological units of different sizes and complexity is considered. The application of modern equipment based on PLC (Programmable Logic Controller) and SCADA (Supervisory Control And Data Acquisition) configuration provides optimal control of technological process. Described supervisory and control system is consisting of a number of units doing decentralized distributed control of technological entities where all possible situation are considered during work of machines and devices, which are installed in electric drive and are protected from technological and electrical accident. Transformer station and diesel engine, raw materials transport and dosage, processes in dome oven, centrifuges, polycondensation (PC) chamber, burners, compressor station, binder preparation and dosage, wool cutting, completed panel packing and their transport to storehouse are controlled. Process variables and parameters like as level, flow, velocity, temperature, pressure, etc. are controlled. Control system is doing identification of process states changes, diagnostic and prediction of errors and provides prediction of behavior of control objects when input flows of materials and generates optimal values of control variables due to decreasing downtime and technic - economical requires connected to wool quality to be achieved. Supervisory and control system either eliminates unwanted changes in the production line or restricts them within the allowable limits according to the technology. In this way, the optimization of energy and raw materials consumption and appropriate products quality is achieved, where requirements are satisfied in accordance with process safety and environmental standards. SCADA provides a visual representation of controlled and uncontrolled parts of the technological process, processing alarms and events, monitoring of the changes of relevant variables, data archiving, choice of either automatic or manual control. Supervison of the production process by intuitive screens on monitors, and display terminal is allowed to the operator. Certain objects of plant are represented by the appropriate symbols whose color is changed depending on status (working, inactive status, stand by, failure, etc.). Symbols are associated with characteristic parameters and the variables whose current values are monitored by graphics and/or tables. Special attention is paid to alarm conditions occurring in the case of failure or exceeding the set limits of certain values. Alarm signal is manifested by sound and signal light, with a corresponding text message on the screen, with the date and time of occurrence and the request to the operator to confirm the alarm in some way. Alarms and other important data are stored in the database, including information about the time of removing the causes of the alarm emergence. Beside data acqusition and processing data of process variables and installed equipment state, the system also provides data archiving and generating and printing of daily, weekly and monthly reports. Based on these reports, analysis and appropriate corrections are being done to increase productivity. Specific data of drive functionality, raw materials and amounts of final products are available to management at any moment via Internet. Information about status of embedded equipment, devices and protective elements provide planning periodical reviews and remont some lines or whole plant. Then replacement of certain parts significantly contributes to efficienty of current, preventive and investment maintenance. In this way, reliability and safety of production plant are increased. With complete automatization of production process that is complex and multidisciplinary, demages and energy consumption are considerably decreasing, workforce is optimized, good quality of final product is achieved and plant work with full capacity is provided. Some technical solutions (diesel engine and transformer station supervisory, compressor station supervisory, electric drive regulation, dedusting system control, HVAC (heating, ventilation, and air conditioning) system control, transport and dosage system control) applied at realization of supervisory and control system for mineral wool production process, can be also applied to regulation large number of industrial processes.
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Ni, Jia Jia, Li Tao, Yi Jun Wang, and Jin Lei Wu. "The Energy Consumption Investigation of the Hotel Central Air-Conditioning System and the Research of Energy Saving Measures." Advanced Materials Research 712-715 (June 2013): 1614–18. http://dx.doi.org/10.4028/www.scientific.net/amr.712-715.1614.
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Through to investigation on present situation of the Changzhou Changrui Hotel air conditioning system energy consumption, by analysis the energy consumption, the power consumption of hotel central air-conditioning system charge 58% of the total electric, accounted for a large proportion. So we should take the necessary measures to reduce the expenses of air conditioning system energy consumption. According to the analysis of data on the survey, we put forward some particular energy-saving measures of central air-conditioning system of the hotel, including strengthening the building envelope insulation, energy saving technology of doors and windows, measures of roof energy saving, setting reasonable indoor temperature, adopting frequency control air-conditioning, reuse waste heat of the central air-conditioning, using the condensation water of central air conditioning to make-up water and reducing temperature of cooling tower , and drying the fresh air independently.
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Jing, You Yin, Qian Qian Liu, and Jiang Jiang Wang. "System Optimization and Exergy Analysis of Air Conditioning System for Data Center." Applied Mechanics and Materials 291-294 (February 2013): 1857–62. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.1857.
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As the air conditioning energy consumption of the date center has increasingly become the focus of attention, reformation for the energy consumption and exploration for the suitable combination model of the air conditioning system have significance in energy saving. This paper makes a program design for the air-conditioning system of a data center in Beijing, makes an analysis of the system operation mode and uses the concept of exergy efficiency to optimize the air conditioning system in order to achieve maximum efficiency.
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Pan, Wen Yan, Liu Yang, and Zhu Hui Zhang. "Energy Consumption and Analysis of Air-Conditioning System of Large-Scale Public Buildings in Xi'an." Applied Mechanics and Materials 99-100 (September 2011): 388–92. http://dx.doi.org/10.4028/www.scientific.net/amm.99-100.388.
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As the main consumption equipment, the air-conditioning system of large-sized public buildings in Xi'an consumes 30%~¬60% of the total energy. Combining with the survey data and related norms, the paper analyses the energy consumption from the following aspects: basic situation of building, index of building energy consumption, ratio of energy consumption of air-conditioning system, load of air-conditioning and indoor environment. Thus, it will give a rational and scientific understanding to energy-efficiency of air-conditioning system of large-scale public buildings in Xi'an for the purpose of providing an efficient assistance to improving the energy consumption of air-conditioning system.
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Ma, Rongjiang, Xianlin Wang, Ming Shan, Nanyang Yu, and Shen Yang. "Recognition of Variable-Speed Equipment in an Air-Conditioning System Using Numerical Analysis of Energy-Consumption Data." Energies 13, no. 18 (September 22, 2020): 4975. http://dx.doi.org/10.3390/en13184975.
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Motor-driven equipment (ME) is one of the key components in an air-conditioning system, which contributes to the vast majority of the total energy consumption by air-conditioning systems. Distinguishing variable- and constant-speed equipment is important since the energy simulation models of the two types differ. Traditionally, types of ME are known in advance, and energy consumption data are consequently analyzed. However, in the application scenarios of energy consumption data mining, precedent information on the ME type could be missing. Thus, this study applies this process in reverse, providing new insight into energy consumption data of ME to recognize variable-speed ME in an air-conditioning system. The energy consumption data of ME in an air-conditioning system implemented in a commercial building were collected and numerically analyzed. A proposed simple parameter, coefficient of the median, and several numerical parameters were calculated and used to distinguish variable- from constant-speed ME. Results showed that the energy consumption data distributions of the two types of ME differed. The proposed coefficient of the median could successfully distinguish variable- from constant-speed ME, and it could be applied as an important step in energy consumption data mining of air-conditioning systems.
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Zhang, Guang Ming, Xue Shen, and Gui Zhong Tang. "Energy Consumption Simulation of the Air Conditioning System in Large-Scale Buildings." Advanced Materials Research 724-725 (August 2013): 1506–9. http://dx.doi.org/10.4028/www.scientific.net/amr.724-725.1506.
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The working environment of air conditioning system in large-scale building is very complex, and there is no significant linear relationship between factors affecting energy consumption and energy demand of air conditioning system. This study adopts a nonlinear regression model: ANN (artificial neural network) model as energy model of air conditioning system. Take outdoor temperature, categorical day-of-week variable, equipment efficiency and terminal load as input, energy demand as output. Use energy consumption data in 2011 for network training, and energy consumption data in 2012 to verify the reliability of model. Based on energy analysis, the operation condition and the characteristics of energy consumption of air conditioning system for large-scale buildings in Nanjing could be precisely represented.
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Ma, Rongjiang, Shen Yang, Xianlin Wang, Xi-Cheng Wang, Ming Shan, Nanyang Yu, and Xudong Yang. "Systematic Method for the Energy-Saving Potential Calculation of Air-Conditioning Systems via Data Mining. Part I: Methodology." Energies 14, no. 1 (December 25, 2020): 81. http://dx.doi.org/10.3390/en14010081.
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Air-conditioning systems contribute the most to energy consumption among building equipment. Hence, energy saving for air-conditioning systems would be the essence of reducing building energy consumption. The conventional energy-saving diagnosis method through observation, test, and identification (OTI) has several drawbacks such as time consumption and narrow focus. To overcome these problems, this study proposed a systematic method for energy-saving diagnosis in air-conditioning systems based on data mining. The method mainly includes seven steps: (1) data collection, (2) data preprocessing, (3) recognition of variable-speed equipment, (4) recognition of system operation mode, (5) regression analysis of energy consumption data, (6) constraints analysis of system running, and (7) energy-saving potential analysis. A case study with a complicated air-conditioning system coupled with an ice storage system demonstrated the effectiveness of the proposed method. Compared with the traditional OTI method, the data-mining-based method can provide a more comprehensive analysis of energy-saving potential with less time cost, although it strongly relies on data quality in all steps and lacks flexibility for diagnosing specific equipment for energy-saving potential analysis. The results can deepen the understanding of the operating data characteristics of air-conditioning systems.
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Ashraf, A., M. Faisal, K. Parvin, Pin Jern Ker, and M. A. Hannan. "Air Conditioning for Smart Home Energy Management System." International Journal of Engineering & Technology 7, no. 4.35 (November 30, 2018): 487. http://dx.doi.org/10.14419/ijet.v7i4.35.22896.
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Smart load management system with an advanced metering infrastructure operates to monitor the electricity consumption by the load and transferring data to the utility grid. It has direct benefit to the end-users by managing the load. This system has incorporated with home appliance for achieving the goal of home energy management system (HEMS) such as efficient energy utilization of house by avoiding the wastage. Efficient loading system can strengthen the efficient power utilization and thus can save the economy greatly. Air conditioner (AC), thermostat associated with a room were selected for this purpose as they have the high demand of electricity consumption. This study mainly focuses on developing the mathematical model and simulate it for the considered home appliances to assess the trend of electricity consumption. Research proved that, considering the ambient temperature developed model can provide the specific instructions for automatic controlling of the appliances which will save the electricity consumption and utility bill of end-users compare to the manual operation of the system. Matlab /Simulink software was used to implement and justify the model.
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Chen, Yong-Liang, Zi-Qiang Qin, Yao Li, Hai-Bo Wang, Sheryar Muhammad, and Hai-Qing Si. "Optimization of modular data center air conditioning system." International Journal of Modern Physics B 34, no. 14n16 (June 3, 2020): 2040123. http://dx.doi.org/10.1142/s0217979220401232.
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In high-density data center, energy consumption is increasing dramatically. For reducing the energy consumption, CFD software, Fluent 15.0, is used to simulate the flow and temperature field distribution with [Formula: see text] turbulence model and fluid–solid coupling method. Fans on the back of racks are simplified as walls with a certain pressure jump. Severs are treated as solid heat sources and porous media. Simulation results reveal that the temperature distribution on the back of racks is not uniform when air conditioners are arranged face-to-face, and local high temperature points emerge near the side wall of air conditioners. Factors affecting cooling efficiency, such as location of air conditioners, speed of inlets, distance of racks, etc., need to be improved. Geometric model is optimized by using a diagonal rack arrangement and drilling holes on the side wall. Based on this, four different cases with various hot aisle distance are proposed. Single and double modular data center are both simulated. Results of new model are better than those of baseline model.
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Tong, Li, CAI Liang, and zhang xiao. "Simulation and Analyses of a Novel Air-conditioning Solution for Improving Energy Saving in a Data Room." E3S Web of Conferences 233 (2021): 01081. http://dx.doi.org/10.1051/e3sconf/202123301081.
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In view of the feature of long airflow path, high wind resistance, and large area of refrigeration equipment in traditional data room, a new type of under-floor modular air conditioner and its corresponding new air conditioning solution for data room is proposed in this paper. The mathematical and physical model of the new solution for data room is established through a computational fluid simulation software and compared with two mainstream air conditioning solutions. Meanwhile, the impact of these three different air conditioning solutions on the temperature field, airflow field and energy consumption are analysed. The results show that the new type air conditioning solution for data room not only can be used to improve the distribution of temperature and airflow in the data room, but also can greatly reduce the energy consumption of the system.
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Feng, Zheng Qian, and Chong Chao Pan. "The Central Air-Conditioning Energy Saving System." Advanced Materials Research 986-987 (July 2014): 656–59. http://dx.doi.org/10.4028/www.scientific.net/amr.986-987.656.
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At present most of the research is aimed at the end of the central air conditioning equipment, not considering the inner link between each component of the central air conditioning. In order to achieve economic operation of equipment and systems, to maximize energy saving of central air conditioning, we designed and implemented a monitoring system analysis which considered in the system more equipments linkage, multi parameter coupling, and a variety of factor. It collected energy consumption data of each device, to get the system running in typical operating conditions of the system by simulating the optimal process parameters and guide debugging critical control equipment.
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P. Hengjinda and Dr Joy Iong Zong Chen. "An Intelligent Feedback Controller Design for Energy Efficient Air Conditioning System." September 2020 2, no. 3 (July 17, 2020): 168–74. http://dx.doi.org/10.36548/jei.2020.3.003.
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Air conditioning systems were invented to improve human comfort in a room or hall. An efficient air conditioner systems are always needed to minimize the power consumption. There are several settings with lot of control devices were introduced in the past years to achieve minimal energy consumption rate. Those control systems were minimized the energy consumption to certain limit without considering human comfort. The proposed model is designed to minimize the energy consumption with maximum human comfort. Several sensor modules were introduced in the model to predict human comfort level in a room or hall. The sensor data are taken as feedback to the air conditioning system for attaining maximum human comfort level. The proposed design is verified with energy consumption calculation and change in room temperature measurements.
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Zhang, Wei Ya, and Jun Wei. "The Experimental Research on Beijing Subway Air-Conditioning System Energy-Saving." Applied Mechanics and Materials 170-173 (May 2012): 2494–98. http://dx.doi.org/10.4028/www.scientific.net/amm.170-173.2494.
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The subway is the major means of transportation in Beijing, and it also takes huge energy consumption. Now the consumption of a subway station is 9500 kWh every day, and the proportion of the air-conditioning system energy dissipation is about 64%, in which, a big part of that can be saved down to save and make full use of the energy. The key to the air-conditioning system energy saving is to put forward reasonable energy-saving schemes and feasible method. In this paper, with a subway station in Beijing as a test location，the measurement and data analysis are carried out, and the schemes put forward for energy conservation and emission reduction in subway air- conditioning system.
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Huang, Zhijia, Xiaofeng Chen, Kaiwen Wang, and Binbin Zhou. "Air Conditioning Load Forecasting and Optimal Operation of Water Systems." Sustainability 14, no. 9 (April 19, 2022): 4867. http://dx.doi.org/10.3390/su14094867.
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The energy consumption of buildings accounts for about 30% of the total energy consumption in China, and the energy consumption of central air conditioning systems accounts for more than half of the total energy consumption. In order to improve energy efficiency, this study used a hotel’s central air conditioning system as the research object. Based on the data of the hotel energy management system, the load-forecasting model of the central air conditioning system based on support vector regression (SVR) was established by MATLAB. Based on the working principle of a chiller, chilled water pump, cooling water pump, and cooling tower, the energy consumption models were established, respectively. Finally, based on the load-forecasting results and the equipment energy consumption model, the energy consumption optimization objective function of the hotel water system was established, the objective function was solved to optimize the operating parameters of the water system at different load rates, the operation control strategy for each piece of equipment was obtained, and the energy-saving analysis was carried out. The results show that in the range of a load rate of 25~90%, the optimization strategy has an energy-saving effect, and the system’s energy-saving rate is the highest when the load rate is 25.4%. The average energy-saving rate of the system is 12.4%.
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Yao, Leehter, and Jin-Hao Huang. "Multi-Objective Optimization of Energy Saving Control for Air Conditioning System in Data Center." Energies 12, no. 8 (April 18, 2019): 1474. http://dx.doi.org/10.3390/en12081474.
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A multi-objective optimization scheme is proposed to save energy for a data center air conditioning system (ACS). Since the air handling units (AHU) and chillers are the most energy consuming facilities, the proposed energy saving control scheme aims to maximize the saved energy for these two facilities. However, the rack intake air temperature tends to increase if the energy saving control scheme applied to AHU and chillers is conducted inappropriately. Both ACS energy consumption and rack intake air temperature stabilization are set as two objectives for multi-objective optimization. The non-dominated sorting genetic algorithm II (NSGA-II) is utilized to solve the multi-objective optimization problem. In order for the NSGA-II to evaluate fitness functions that are both the ACS total power consumption and AHU outlet cold air temperature deviations from a specified range, neural network models are utilized. Feedforward neural networks are utilized to learn the power consumption models for both chillers and AHUs as well as the AHU outlet cold air temperature based on the recorded data collected in the field. The effectiveness and efficiency of the proposed energy saving control scheme is verified through practical experiments conducted on a campus data center ACS.
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Zhu, Qixin, Mengyuan Liu, Hongli Liu, and Yonghong Zhu. "Application of machine learning and its improvement technology in modeling of total energy consumption of air conditioning water system." Mathematical Biosciences and Engineering 19, no. 5 (2022): 4841–55. http://dx.doi.org/10.3934/mbe.2022226.
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<abstract> <p>Accurate energy consumption model is the basis of energy saving optimal control of air conditioning system. The existing energy consumption model of air conditioning water system mainly focuses on a certain equipment or a part of the cycle. However, the coupling between water system equipment will affect the setting of optimal energy consumption of equipment. It is necessary to establish the energy consumption model of water system as a whole. However, air conditioning water system is a highly nonlinear complex system, and its precise physical model is difficult to establish. The main goal of this paper is to develop an accurate machine learning modeling and optimization technique to predict the total energy consumption of air conditioning water system by using the actual operation data collected. The main contributions of this work are as follows: (1) Three commonly used machine learning techniques, artificial neural network (ANN), support vector machine (SVM) and classification regression tree (CART), are used to build prediction models of air conditioning water system energy consumption. The results show that all the three models have fast training speed, but the ANN model has better performance in cross-validation. (2) The improved differential evolution algorithm was used to optimize the parameters (initial weights and thresholds) of the ANN, which solved the problem that the ANN is easy to fall into the local optimal solution. The simulation results show that the root mean square error (RMSE) of the improved model decreases by 20.5%, the mean absolute error (MAE) decreases by 30.2%, and the coefficient of determination (R<sup>2</sup>) increases from 0.9227 to 0.9512. (3) Sensitivity analysis of the established optimization model shows that chilled water flow, chilled water outlet temperature and air conditioning load are the main factors affecting the total energy consumption.</p> </abstract>
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Lin, Xiaoyu, Hang Yu, Meng Wang, Chaoen Li, Zi Wang, and Yin Tang. "Electricity Consumption Forecast of High-Rise Office Buildings Based on the Long Short-Term Memory Method." Energies 14, no. 16 (August 6, 2021): 4785. http://dx.doi.org/10.3390/en14164785.
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Various algorithms predominantly use data-driven methods for forecasting building electricity consumption. Among them, algorithms that use deep learning methods and, long and short-term memory (LSTM) have shown strong prediction accuracy in numerous fields. However, the LSTM algorithm still has certain limitations, e.g., the accuracy of forecasting the building air conditioning power consumption was not very high. To explore ways of improving the prediction accuracy, this study selects a high-rise office building in Shanghai to predict the air conditioning power consumption and lighting power consumption, respectively and discusses the influence of weather parameters and schedule parameters on the prediction accuracy. The results demonstrate that using the LSTM algorithm to accurately predict the electricity consumption of air conditioners is more challenging than predicting lighting electricity consumption. To improve the prediction accuracy of air conditioning power consumption, two parameters, relative humidity, and scheduling, must be added to the prediction model.
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Aver’yanova, Olesya, Viktoria Voronkova, Viktoria Demchenko, Nailya Kudaibergenova, and Anna Solobay. "Comparison of Air Conditioning Systems for Advanced Data Centers." Applied Mechanics and Materials 725-726 (January 2015): 1279–84. http://dx.doi.org/10.4028/www.scientific.net/amm.725-726.1279.
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Considering nowadays growth of electronic data, the necessity of major data centers establishment is also increasing. Such centers may contain data distribution, storing and processing systems, like servers. The equipment generates huge heat energy, so an appropriate microclimate is required in such premises. High capacity air conditioners are used for maintaining of appropriate parameters and assuring normal functioning of these systems. Herein you can find comparison analysis of central and precision air conditioning systems considering two parameters: cost and energy efficiency for the central regions of the Russian Federation. During such comparison analysis the most cost-efficient and ergonomic air conditioning system was revealed for the Data Center Berzarina, Moscow.
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Fan, Yi Peng, Yu Yun Li, Jun Zhou Yang, and Rui Huang. "The Comparative Analysis of an Official and Experimental Building." Advanced Materials Research 986-987 (July 2014): 2184–88. http://dx.doi.org/10.4028/www.scientific.net/amr.986-987.2184.
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The simulation software DeST developed by Air Conditioning Research Group Of Tsinghua University has been used in my thesis. We use this software to simulate an official and experimental building’s energy of air conditioning and heating, then compared to the measured efficiency. We analyzed what has caused the simulated and measured energy consumption data difference, providing a reference for rationality of consumption simulation and optimization of building’s operation management.
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Hamdallah, Mustafa W., Omar M. Jumaah, Zaid A. Shaalan, and Adnan M. Hussein. "Performance Enhancement of Air Conditioning (Split Unit) Using CuO/Oil Nano-Lubricant." Materials Science Forum 1021 (February 2021): 97–106. http://dx.doi.org/10.4028/www.scientific.net/msf.1021.97.
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The aims of this study are to improve thermal characteristics and decrease electrical consumption of air-conditioning as well as, to increase the performance (COP) of cooling cycle. CuO nanoparticles (0.003 mass fraction) have been added to compressor oil of air conditioning (1 ton capacity, split-unit) used Freon gas (R22), and then compared with pure oil compressor of air conditioning under same environmental conditions. The results showed that the increasing of density ratio, COP and viscosity ratio are 3%, 50% and 1.8% respectively while the decreasing of electrical consumption is 51.2%. The experimental data are compared with previous data in the literature to be validated. It can be recommended that the nano-oil is significant utilizing in air conditioner compressors for energy consumption applications.
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Alsharif, Khaled Iyad, Aspen Glaspell, and Kyosung Choo. "Energy Conservation Measures for a Research Data Center in an Academic Campus." Energies 14, no. 10 (May 14, 2021): 2820. http://dx.doi.org/10.3390/en14102820.
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Simulation and experimental studies were conducted to investigate energy consumption, develop ECMs (Energy Conservation Measures), and analyze temperature increase under a power failure scenario for a research data center at Youngstown State University. Two ECMs were developed to improve energy consumption by analyzing the thermal performance of the data center: (1) increase the return temperature in air conditioning vents; (2) provide cold aisle containment with the set point temperature increase. A transient analysis was conducted under a cooling system failure scenario to predict the temperature variation over time. The results suggest that it takes 600 s to increase the server inlet temperature by 16.1 °C for the baseline model. In addition, in the ECM #2, the maximum temperature at the server inlet did not reach 40 °C under the air conditioning system failure scenario, which is the maximum operating temperature of the ASHRAE A3 envelop.
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Ariwibowo, Didik. "AUDIT ENERGI PADA SEBUAH HOTEL." Gema Teknologi 16, no. 3 (February 6, 2012): 131. http://dx.doi.org/10.14710/gt.v16i3.4710.
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Didik Ariwibowo, in this paper explain that energy audit activities conducted through several phases, namely: the initial audit, detailed audit, analysis of energy savings opportunities, and the proposed energy savings. Total energy consumed consists of electrical energy, fuel, and materials in this case is water. Electrical energy consumption data obtained from payment of electricity accounts for a year while consumption of fuel and water obtained from the payment of material procurement. From the calculation data, IKE hotels accounted for 420.867 kWh/m2.tahun, while the IKE standards for the hotel is 300 kWh/m2.tahun. Thus, IKE hotel included categorized wasteful in energy usage. The largest energy consumption on electric energy consumption. Largest electric energy consumption is on the air conditioning (AC-air conditioning) that is equal to 71.3%, and lighting and electrical equipment at 27.28%, and hot water supply system by 4.44%. Electrical energy consumption in AC looks very big. Ministry of Energy and Mineral Resources of the statutes, the profile of energy use by air conditioning at the hotel by 48.5%. With these considerations in the AC target for audit detail as the next phase of activity. The results of a detailed audit analysis to find an air conditioning system energy savings opportunities in pumping systems. Recommendations on these savings is the integration of automation on the pumping system and fan coil units (FCU). The principle of energy conservation in the pumping system is by installing variable speed drives (VSD) pump drive motor to adjust speed according to load on the FCU. Load variations FCU provide input on the VSD pumps to match. Adaptation is predicted pump can save electricity consumption up to 65.7%. Keywords: energy audit, IKE, AC
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Zailan, Roziah, and Mohd Tarmizy Che Kar. "Energy Audit: A Case Study in FTK Building Universiti Malaysia Pahang." International Journal of Engineering Technology and Sciences 5, no. 2 (August 1, 2018): 91–101. http://dx.doi.org/10.15282/ijets.v5i2.1400.
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The energy audit program was carried out for Faculty of Engineering Technology (FTK), University Malaysia Pahang by internal energy audit team. This paper presented annual energy consumption trend for FTK building, measurement finding for room data survey (air conditioning temperature and humidity comfort performance & CO2 level for air quality) and lighting, Building Energy Index (BEI) value and appropriate recommendation in regards of energy saving practice and technological solution. According to those analysis, value for Building Energy Index (BEI) in FTK building is 98.035 kWh/m2/year, Air Conditioning Energy Index (ACEI) is 73.254 kWh/m2/year while for Lighting Energy Index (LEI) is 11.402 kWh/m2/year. Total energy consumption estimated for 2017 is 31, 7951.375 kWh per year. The implementation of the proposed energy conservation measures were expected to give positive results where the total cost saving per year is estimated about RM 48,551.20. Finally, it was recommended to implement three major energy conservation measures (ECMs) in specific: implementation of Sustainable energy management system (SEMS), maintenance of air conditioning system and retrofitting of LED lighting. As a result, FTK is targeted to achieve 30% annual energy saving about from the total energy consumption.
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Liang, Wang, Yang Lu-lu, and Tian Ya-bin. "Study on Energy Efficient Operation of Air-Conditioning Cooling Water System." Open Electrical & Electronic Engineering Journal 9, no. 1 (February 26, 2015): 53–60. http://dx.doi.org/10.2174/1874129001509010053.
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The control logic of frequency adjustment for pump and cooling tower fan has been presented in this paper, based on the operation mode of a chiller with one pump and one cooling tower. Optimum outlet water temperature control of cooing tower has been put forward through analysis and comparison among factors influencing it, based on measured data. A mathematical model of energy consumption has been established under different outdoor wet-bulb temperature and load rate conditions. The optimized controlling strategy has been obtained after the analysis on energy consumption under two different operational strategies with different number of cooling towers in service. In partial load condition, the best operation mode of cooling water system is the optimal water outlet temperature control system, which aims at the lowest comprehensive system energy consumption. Cooling water system can match the best temperature difference and determine the fan frequency according to optimum outlet temperature automatically. Variable frequency control should be applied to fans; meanwhile, routing maintenance and cleaning is also needed for an even distribution of water and effective use of heat exchange area.
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Alshahrani, Jubran, and Peter Boait. "Reducing High Energy Demand Associated with Air-Conditioning Needs in Saudi Arabia." Energies 12, no. 1 (December 28, 2018): 87. http://dx.doi.org/10.3390/en12010087.
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Electricity consumption in the Kingdom of Saudi Arabia (KSA) has grown at an annual rate of about 7% as a result of population and economic growth. The consumption of the residential sector accounts for over 50% of the total energy generation. Moreover, the energy consumption of air-conditioning (AC) systems has become 70% of residential buildings’ total electricity consumption in the summer months, leading to a high peak electricity demand. This study investigates solutions that will tackle the problem of high energy demand associated with KSA’s air-conditioning needs in residential buildings. To reduce the AC energy consumption in the residential sector, we propose the use of smart control in the thermostat settings. Smart control can be utilized by (i) scheduling and advance control of the operation of AC systems and (ii) remotely setting the thermostats appropriately by the utilities. In this study, we model typical residential buildings and, crucially, occupancy behavior based on behavioral data obtained through a survey. The potential impacts in terms of achievable electricity savings of different AC operation modes for residential houses of Riyadh city are presented. The results from our computer simulations show that the solutions intended to reduce energy consumption effectively, particularly in the advance mode of operation, resulted in a 30% to 40% increase in total annual energy savings.
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Park, Jaeryang, Hojin Jang, Sinhyeok Choi, Ryeong Jung, and Sokhee P. Jung. "Current and Prospects of Waste Heat Utilization and Cooling Technology in Data Centers." Journal of Korean Society of Environmental Engineers 44, no. 11 (November 30, 2022): 493–503. http://dx.doi.org/10.4491/ksee.2022.44.11.493.
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As the COVID-19 pandemic and interest in the virtual world rapidly increase, the data usage in the current society is rapidly increasing to an unprecedented level, and the need for expansion of data centers to handle it is also rapidly increasing. Data centers operate continuously and consume a lot of power in operation. As electricity consumption increases, the increase in greenhouse gas emissions adversely affects the environment, so the increase in data centers inevitably affects the climate environment. Typical technologies that can reduce power consumption in data centers are waste heat energy utilization and outdoor air conditioning. By analyzing the cases of major countries for the two technologies, the technological direction beneficial to Korea was reviewed. As Korea's outdoor air conditioning standards are relaxed, the number of outdoor air conditioning facilities in Korea is increasing. However, the Korean government's practical support for waste heat energy utilization is extremely limited. By analyzing policy cases for waste heat energy utilization in data centers in other countries, policies for revitalizing waste heat energy utilization in Korean data centers were proposed. Furthermore, several ways to reduce the amount of power in the data center were explored and proposed.
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Papakostas, Konstantinos T., Dimitrios Kyrou, Kyrillos Kourous, Dimitra Founda, and Georgios Martinopoulos. "Bin Weather Data for HVAC Systems Energy Calculations." Energies 14, no. 12 (June 12, 2021): 3501. http://dx.doi.org/10.3390/en14123501.
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The increase in global air temperature is well documented, as during the last several years each decade has been consecutively warmer than the preceding. As climatic conditions affect the energy performance of buildings, the changes in outdoor air temperature and humidity will inevitably lead to significant alterations in energy consumption and costs for the heating, ventilating and air conditioning (HVAC) of buildings. The availability and quality of climatic data play an important role in the accuracy of energy analysis results. In this study, the hourly temperature and relative humidity of outdoor air measurements, for a period of three decades (1983–2012), recorded at the climatic station of the National Observatory of Athens were processed, and an up-to-date set of specific data for the application of bin methods was produced and presented. The data were then used to calculate changes in the energy demands in a typical office building throughout the specified period. Results showed a progressive reduction in the low and increase in the high temperature intervals, leading to an increase in the building’s annual energy requirements for air conditioning of up to 14.5% from the first to the third decade, with decrease in the energy demands for heating and increase in the energy demands for cooling.
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Zhao, Jinhui, Panle Wang, Jingshun Li, Tianwei Gu, and Jiaxu Lu. "Energy-saving and emission reduction system of data center heat pipe based on latent heat of water evaporation." Thermal Science 26, no. 5 Part B (2022): 4475–87. http://dx.doi.org/10.2298/tsci2205475z.
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To address the current problem of high energy consumption in data centers, this paper proposes a data center heat pipe air-conditioning system based on the latent heat of water evaporation, which uses the latent heat of water evaporation for cooling by creating a low pressure environment to evaporate large amounts of water. In order to verify the effect of the system, a heat pipe test bench based on the latent heat of water evaporation was designed and built. Compared with the traditional heat pipe in the data center for heat dissipation, the performance and economy of the water evaporation latent heat pipe system designed in this paper are analyzed experimentally. A multi-physics coupled model of water evaporation latent heat pipe air-conditioning based on COMSOL Multiphysics was established to simulate and study the temperature field and velocity field distribution of water evaporation latent heat pipe air-conditioning system in data centers. The research shows that: - Under the designed test conditions, compared with the traditional heat pipe system, the water evaporation latent heat pipe air conditioner can conduct 2540 kJ more heat in one day in an outdoor environment of 24?C. - At an ambient temperature of 35?C and an indoor temperature of 25.8 ?C, the cooling capacity of the heat pipe in the data center water evaporation latent heat pipe air-conditioning system is twice the cooling capacity of the air conditioner, and the heat pipe can work efficiently regardless of the outdoor ambient temperature. - The energy-saving effect of the latent heat pipe of water evaporation in the data center has a significant effect on air conditioners with an energy efficiency rating (EER) lower than 2.5-4.4. It can improve the energy efficiency of level 5 with an EER of 2.5 to level 2 with an EER of 3.22, greatly reducing the power consumption of the data center air-conditioning system. When the EER of the air conditioner exceeds 4.4, the coefficient of performance of the data center water evaporation latent heat pipe air-conditioning system will be lower than that of the air conditioner itself.
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Mei, Guanghang, Bin Hu, Zhenjie Liu, Zhikun Zhu, and Wenjun Huang. "Energy-saving optimization of refrigeration system in a data centre based on Nelder-Mead method." ITM Web of Conferences 47 (2022): 03017. http://dx.doi.org/10.1051/itmconf/20224703017.
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In order to improve the cooling efficiency of the data centre HVAC (Heating Ventilation and Air Conditioning) system and save costs, this paper proposes a control strategy that combines traditional control method with Nelder and Mead method, in order to optimize equipment operating parameters. Firstly, this paper selected a data centre in Northeast China as the research object. Moreover, the central air-conditioning system, as the control object, was simulated on TRNSYS, whose result was compared with the actual operating parameters to verify the reliability of the simulation model. Finally, the optimal control strategy was applied to the simulation model to analyze the changes of energy consumption of the system before and after optimization. The results showed that in August, the optimal control strategy is able to meet the extremity of cooling load demand, and the total energy consumption of the system is 269,612kwh, which is 10% less than the energy consumption before optimization. The overall energy consumption of the system is significantly reduced, and the proportion of energy consumption of each part tends to be reasonable, which will effectively improve the cooling efficiency of HVAC.
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Xue, Guiyuan, Chen Wu, Wenjuan Niu, Xun Dou, Shizhen Wang, and Yadie Fu. "Flexible Control Strategy for Intelligent Building Air Conditioning System." E3S Web of Conferences 252 (2021): 01039. http://dx.doi.org/10.1051/e3sconf/202125201039.
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An improved optimization adjustment strategy for building heating ventilation and air conditioning (Heating Ventilation and Air Conditioning, HVAC) is proposed. The energy consumption model of building heating/refrigeration is established by using the instantaneous energy balance of heat, and then the optimal operation strategy of building HVAC energy based on weather forecast data is constructed in the range of user temperature comfort. Finally, the MATLAB and TRNSYS simulation techniques are used to verify the example. Simulation results show that the optimal operation strategy of building HVAC energy based on weather forecast data can not only significantly reduce the cost of energy use, but also effectively improve the absorption capacity of renewable energy on the building side.
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Chang, Yu Sheng, Yuan Liang Cheng, Wen Sheng Ou, and Chi Chang Liao. "Evaluation the Feasibility of Zero-Carbon Green Building in Taiwan." Applied Mechanics and Materials 145 (December 2011): 395–99. http://dx.doi.org/10.4028/www.scientific.net/amm.145.395.
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In order to accommodate the global climate change, the idea of constructing zero-carbon green buildings has become the main stream and highest standard in building design in many countries. Located in subtropical zone, Taiwan features hot and humid weather in summer. The high usage of air conditioning is the main challenge to design zero-carbon green buildings in Taiwan. However, the temperature in the middle and high mountain areas decreases as altitude increases and makes it possible to create a living environment without using air conditioning in the summer. This project analyzed weather data in the middle and high mountain areas of Taiwan. The degree hour method and weather research and forecast model were used to evaluate the demand of air conditioning in the summer based on outside air temperature. The results showed that the low air conditioning load areas are above 1000 m elevation. This project then simulated energy consumption of a two-floor building near the Sun Moon Lake, an area of low air conditioning load, to explore the feasibility of zero-carbon green buildings in Taiwan. Based on the life style of a four-member family, a simulation process was conducted to estimate energy consumption of various appliances and different life habits. This study showed that the energy consumption in the buildings can be reduced up to 70% by using three major design strategies. These strategies include selection of a low air conditioning load location, using high energy efficient appliances, and application of energy conserving habits. Followed by renewable energy evaluation, it is possible to put zero-carbon green building into practice in Taiwan.
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Futawatari, Naoki, Yosuke Udagawa, Taro Mori, and Hirofumi Hayama. "Impact of Fan Airflow of IT Equipment on Thermal Environment and Energy Consumption of a Data Center." Energies 13, no. 23 (November 24, 2020): 6166. http://dx.doi.org/10.3390/en13236166.
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Energy-saving in regard to heating, ventilation, and air-conditioning (HVAC) in data centers is strongly required. Therefore, to improve the operating efficiency of the cooling equipment and extend the usage time of the economizer used for cooling information-technology equipment (ITE) in a data center, it is often the case that a high air-supply temperature within the range in which the ITE can be sufficiently cooled is selected. In the meantime, it is known that when the ambient temperature of the ITE rises, the speed of the built-in cooling fan increases. Acceleration of the built-in fan is thought to affect the cooling performance and energy consumption of the data center. Therefore, a method for predicting the temperature of a data center—which simply correlates supply-air temperature with ITE inlet temperature by utilizing existing indicators, such as air-segregation efficiency (ASE)—is proposed in this study. Moreover, a method for optimizing the total energy consumption of a data center is proposed. According to the prediction results obtained under the assumption of certain computer-room air-conditioning (CRAC) conditions, by lowering the ITE inlet temperature from 27 °C to 18 °C, the total energy consumption of the machine room is reduced by about 10%.
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Mohd Nasib, Affandi, Henry Nasution, Azhar Abdul Aziz, Muchamad Oktaviandri, Sumeru, and Sulaimon Shodiya. "Energy Analysis of Split Air Conditioning System Using Variable Speed Drive." Applied Mechanics and Materials 819 (January 2016): 212–15. http://dx.doi.org/10.4028/www.scientific.net/amm.819.212.
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An air conditioning (AC) system design requires two main aspects that should be taken into consideration, there are reducing energy consumption and ensuring thermal comfort. This paper present variable speed drive on compressor motor is being tested to reduce the energy consumption. Conventional AC system to use on/off controller where the compressor motor turns itself on and runs at maximum speed then turns back off to achieve the temperature setting. This controller consumes more energy, however, by using a variable speed drive, the compressor motor will constantly run at various speeds while achieving the temperature setting. A system that developed software to implement the controller algorithms was installed in a thermal environmental room with data acquisition to monitor the room temperature, energy consumption, energy saving and coefficient of performance. Measurements were taken during the one hour experimental period at a time interval of three minutes for temperature set-points of 22, 23 and 24°C with internal heat loads of 500, 700 and 1000 W. The proposed technique can save energy and thermal comfort in comparison with conventional on/off control. The experiment results indicate that the application of variable speed drive on compressor motor is better than conventional on/off.
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Istomin, Stanislav, and Aleksandr Shtraukhman. "Simulation model of the heating and air conditioning system of dc electric trains." E3S Web of Conferences 135 (2019): 02018. http://dx.doi.org/10.1051/e3sconf/201913502018.
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Most of the territory of the Russian Federation is located in the zone of long-term exposure to negative ambient temperatures. In this regard, in the suburban traffic on the railways of the Russian Federation, a significant proportion of the electric power falls on the operation of heating and air conditioning systems. Nowadays, Russia and the world are developing energy-saving methods and tools to reduce the energy consumption of auxiliary needs of electric trains. In this paper, the method of constructing simulation models in the MATLAB Simulink software was used to build an energy-saving heating and air conditioning system, since this method allows studying various options for building the studied systems with lower financial and labor costs in comparison with the experimental method. The correct selection and display of the parameters of the electric train interior will allow achieving the optimal values of energy consumption for heating and air conditioning of the electric trains. In order to verify its adequacy, the simulation model includes standard values of electric energy consumption for heating and conditioning electric trains for various sections and operating conditions, which were obtained earlier during the correlation and regression analysis of data from electric train parameter recorders. The results of the study showed the adequacy of the application of the developed simulation model for organizing the control of electric power consumption for heating and air conditioning of DC electric trains.
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Istomin, Stanislav Gennadyevich, and Oleg Dmitrievich Yurasov. "Simulation model of heating system of DC electric-multiple units." Transport of the Urals, no. 4 (2020): 75–79. http://dx.doi.org/10.20291/1815-9400-2020-4-75-79.
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Most of the Russian Federation territory is located in the zone of long-term exposure to negative ambient temperatures. In this regard, a significant proportion of power consumption in the suburban traffic on the railways of the Russian Federation accounts for the operation of heating and air conditioning systems. Currently, Russian and foreign scientists are developing energy-saving methods and tools to reduce the power consumption for auxiliary needs of electric-multiple units. In this paper, the authors used the method of constructing simulation models in the MATLAB Simulink program in order to create an energy-saving heating and air conditioning system since this method allows you to explore various options for constructing the studied systems with lower financial and labour costs in comparison with the experimental method. In order to verify its adequacy the simulation model includes standard values of electric energy consumption for heating and air conditioning for various sections and operating conditions obtained by the authors earlier during the correlation and regression analysis of data from parameter recorders installed in electric-multiple units. The results of the study showed the adequacy of application of the developed simulation model for organizing the control of power consumption for heating and air conditioning of direct current electric-multiple units.
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Yu, Jiawen, Yanqiu Yan, Yiqiang Jiang, and Jie Ge. "Renewable energy configuration scheme of data center in cold area. A case study." International Journal of Low-Carbon Technologies 17 (2022): 411–20. http://dx.doi.org/10.1093/ijlct/ctac014.
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ABSTRACT The core of building energy allocation is to reduce the power load and power consumption through the reasonable allocation of energy equipment, so as to reduce the capacity of the supply side and save investment. In this way, the configuration of energy schemes in data center is conducted in this paper. According to the results of load forecasting, the energy supply scheme of each building in the planning area is determined, including ground source heat pump (GSHP) system, solar water heating system and heat pipe air conditioning system. In addition, feasibility analysis and economic analysis of each configuration scheme are carried out, and the relatively reasonable scheme is selected. It is found that GSHP system can be used in canteen building, solar hot water system can be used as auxiliary for apartment buildings and joint operation of heat pipe air conditioning unit and traditional machine room air conditioning unit is the most economical for data room. Through the research of this paper, a feasible method for the reasonable allocation of energy is provided in the data center planning stage.
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Nasution, Henry, Abdul Latiff Zulkarnain, Azhar Abdul Aziz, and Mohd Rozi Mohd Perang. "Retrofitting R-22 Split Type Air Conditioning with Hydrocarbon (HCR-22) Refrigerant." Applied Mechanics and Materials 388 (August 2013): 91–95. http://dx.doi.org/10.4028/www.scientific.net/amm.388.91.
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An experimental study to evaluate the energy consumption of a split type air conditioning is presented. The compressor works with the fluids R-22 and HCR-22 and has been tested varying the internal heat load 0, 500, 700 and 1000 W. The measurements taken during the one hour experimental periods at 10-minutes interval times for temperature setpoint of 20oC. The performance data considered where the evaporator cooling load, the condenser heat rejection, the electrical energy consumption, the refrigeration system temperatures, and the room temperature. And hence the Coefficient of Performance (COP) could be determined. The final results of this study show an overall better energy consumption of the HFC-22 compared with the R-22.
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Zherlykina, M. N., T. V. Shchukina, and A. Gurbangulyev. "Optimization of Building Air Conditioning Processes Applying Free Cooling." Proceedings of the Southwest State University 24, no. 2 (October 4, 2020): 73–89. http://dx.doi.org/10.21869/2223-1560-2020-24-2-73-89.
Full textAbstract:
Purpose of research is to carry out an applied research of the thermal behaviour of the production premise of an industrial building and to develop air conditioning processes, including the search for an expedient circuit design for conditioning and increasing the effectiveness of the system by using the cold outdoor air.Methods. In the work, based on the results of the energy audit, a technique for calculating the flows of harmful emissions in the production premise in the Production mode was developed and the thermal loads of the objects of the study were determined to achieve the set objectives. Possible options for air processing by technological conditioning systems including the minimization of energy costs are analyzed. For the assimilation of excess heat in the warm season and a rational choice of the air treatment process in order to save thermal energy consumption, techniques of air treatment with and without heating are proposed. In the cold season, it is proposed to carry out air conditioning using cold outdoor air. The versatility of the technique makes it possible to determine a process feasible in real conditions, including adjusting the processing scheme, in which air preheating is required.Results. The result of the research work is the development of a number of engineering and technical solutions to ensure the energy efficiency of the engineering system and improve the consumer quality of the research objects.Conclusion. Implementation of the developed measures for thermal protection of the research object and the use of energy-efficient engineering solutions will allow achieving the following results: to improve the consumer quality of buildings, to bring the parameters of the internal microclimate to the standard value; to extend significantly the service life of enclosing structures, to ensure the quality of the air intended for the technological process with a high degree of accuracy, to ensure energy savings for air conditioning through the use of the cold outdoor air; to maintain a minimum cooling temperature by mixing outdoor and recirculated air without the risk of frost formation on the surface of the heat exchanger and the formation of ice.
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Corazza, Matteo, Valentina Conti, Antonino Genovese, Fernando Ortenzi, and Maria Pia Valentini. "A Procedure to Estimate Air Conditioning Consumption of Urban Buses Related to Climate and Main Operational Characteristics." World Electric Vehicle Journal 12, no. 1 (February 18, 2021): 29. http://dx.doi.org/10.3390/wevj12010029.
Full textAbstract:
Public Transport (PT) planning requires a detailed evaluation of the fleet energy consumption, usually depending on the specific characteristics of the bus service network. These include topography, climate and operational features. In this work, we focus on the additional air conditioning (AC) energy consumption, proposing a method to evaluate the extra energy consumption based not only on climate variables, but also on the PT planned service. Results are presented for a large part of the provincial capitals and regions of Italy, and clearly show that overconsumption for air conditioning are significantly affected by the daily mileage distribution, with large variance even when climatic conditions are similar. The mileage data are extracted from GTFS databases, widely available for PT applications. The developed tool allows us to apply this methodology to any urban and extra-urban area. Reference AC consumption related to climate conditions are derived from a measurement campaign hold in Cagliari (Sardinia, Italy) during September 2018, within the National Research Program on the Electric System. A discussion on how to optimize the use of climatic data is also presented, resulting in the choice to use Heat Index as unique independent variable for air conditioning energy consumption calculation. A methodology to compute the Heat Index from climatic variables for large domains as, for instance, the Italian regions, was also developed.
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Aizaz, Ahmad, and Nauman Hafeez. "Resolving National Energy Crisis through Energy Efficient Appliances: Use of Ground Water Heat Pump for Air Conditioning Systems." Advanced Materials Research 983 (June 2014): 261–64. http://dx.doi.org/10.4028/www.scientific.net/amr.983.261.
Full textAbstract:
Energy crisis are deepening with every year passing by in a country like Pakistan. One of the major contributors of energy consumption in the domestic as well as in some commercial sector is the environment air conditioning (during summers) and heating systems (during winters). One possible solution to this national energy crisis is available in the form of tapping the available renewable natural resources of energy, specifically the Ground Water Heat Pumps (GWHP). Despite its wider applications in the advanced countries, the confidence in this technology is much feeble in less advanced countries, like Pakistan, mainly due to lack of awareness about the technology among the public and lack of subsoil temperature data for the scientific / engineering community. Thus, the aim of this study is to collect subsoil water temperature data of at least one particular location for over a year, and demonstrate the usefulness of sub soil ground water in improving the performance of conventional air-conditioning system both in cooling as well as in heating modes. This study shows significant improvement in the Coefficient of Performance (COP) of the Air Conditioner both in Cooling as well as in heating modes and thus reducing the expensive electricity consumption.