Research on Intelligent Air Conditioning System of Data Center

2014 ◽  
Vol 602-605 ◽  
pp. 928-932
Author(s):  
Min Li ◽  
Yun Wang ◽  
Zheng Qian Feng ◽  
Wang Li
Keyword(s):  
Heat Exchange ◽  
Energy Saving ◽  
Data Center ◽  
Air Conditioning ◽  
Data Centers ◽  
Cooling Efficiency ◽  
Exchange System ◽  
Air Conditioning System ◽  
Running Time ◽  
Heat Exchange System

By studying the energy-saving technologies of air-conditioning system in data centers, we designed a intelligent air conditioning system, improved the cooling efficiency of air conditioning system through a reasonable set of hot and cold aisles, reduced the running time of HVAC by using the intelligent heat exchange system, an provided a reference for energy saving research of air conditioning system of data centers.

Data Center Room Air Conditioning Energy Consumption Analysis

2014 ◽  
Vol 672-674 ◽  
pp. 518-521
Author(s):  
Li Fei Song ◽  
Tao Li ◽  
Qi Fen Li ◽  
Lin Hui Zhao ◽  
Xin Zhao ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Conservation ◽  
Energy Saving ◽  
Data Center ◽  
Air Conditioning ◽  
Field Research ◽  
Northern China ◽  
Air Conditioning System ◽  
Energy Consumption Analysis ◽  
Energy Saving Technology

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.

Energy saving analysis of evaporative cooling composite air conditioning system for data centers

2021 ◽  
Vol 186 ◽  
pp. 116506
Author(s):  
Zongwei Han ◽  
Xiaoqing Sun ◽  
Haotian Wei ◽  
Qiang Ji ◽  
Da Xue
Keyword(s):  
Energy Saving ◽  
Air Conditioning ◽  
Data Centers ◽  
Evaporative Cooling ◽  
Air Conditioning System

scholarly journals Multi-Objective Optimization of Energy Saving Control for Air Conditioning System in Data Center

Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1474 ◽  
Author(s):  
Leehter Yao ◽  
Jin-Hao Huang
Keyword(s):  
Energy Saving ◽  
Air Temperature ◽  
Data Center ◽  
Air Conditioning ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Air Conditioning System ◽  
Multi Objective ◽  
Control Scheme ◽  
Energy Saving Control

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.

scholarly journals Towards Energy Efficiency in Data Centers: An Industrial Experience Based on Reuse and Layout Changes

2021 ◽  
Vol 11 (11) ◽  
pp. 4719
Author(s):  
Romulos da S. Machado ◽  
Fabiano dos S. Pires ◽  
Giovanni R. Caldeira ◽  
Felipe T. Giuntini ◽  
Flávia de S. Santos ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Saving ◽  
Data Center ◽  
Air Conditioning ◽  
Data Centers ◽  
Energy Resources ◽  
Cooling Power ◽  
Industrial Experience ◽  
Use Of Resources

Data centers are widely recognized for demanding many energy resources. The greater the computational demand, the greater the use of resources operating together. Consequently, the greater the heat, the greater the need for cooling power, and the greater the energy consumption. In this context, this article aims to report an industrial experience of achieving energy efficiency in a data center through a new layout proposal, reuse of previously existing resources, and air conditioning. We used the primary resource to adopt a cold corridor confinement, the increase of the raised floor’s height, and a better direction of the cold airflow for the aspiration at the servers’ entrance. We reused the three legacy refrigeration machines from the old data center, and no new ones were purchased. In addition to 346 existing devices, 80 new pieces of equipment were added (between servers and network assets) as a load to be cooled. Even with the increase in the amount of equipment, the implementations contributed to energy efficiency compared to the old data center, still reducing approximately 41% of the temperature and, consequently, energy-saving.

scholarly journals Assessing a Multi-Objective Genetic Algorithm with a Simulated Environment for Energy-Saving of Air Conditioning Systems with User Preferences

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 344
Author(s):  
Alejandro Humberto García Ruiz ◽  
Salvador Ibarra Martínez ◽  
José Antonio Castán Rocha ◽  
Jesús David Terán Villanueva ◽  
Julio Laria Menchaca ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Energy Saving ◽  
User Satisfaction ◽  
Air Conditioning ◽  
State Of The Art ◽  
User Preferences ◽  
The State ◽  
Nsga Ii ◽  
Air Conditioning System

Electricity is one of the most important resources for the growth and sustainability of the population. This paper assesses the energy consumption and user satisfaction of a simulated air conditioning system controlled with two different optimization algorithms. The algorithms are a genetic algorithm (GA), implemented from the state of the art, and a non-dominated sorting genetic algorithm II (NSGA II) proposed in this paper; these algorithms control an air conditioning system considering user preferences. It is worth noting that we made several modifications to the objective function’s definition to make it more robust. The energy-saving optimization is essential to reduce CO2 emissions and economic costs; on the other hand, it is desirable for the user to feel comfortable, yet it will entail a higher energy consumption. Thus, we integrate user preferences with energy-saving on a single weighted function and a Pareto bi-objective problem to increase user satisfaction and decrease electrical energy consumption. To assess the experimentation, we constructed a simulator by training a backpropagation neural network with real data from a laboratory’s air conditioning system. According to the results, we conclude that NSGA II provides better results than the state of the art (GA) regarding user preferences and energy-saving.

Thermodynamic Estimate of Minimal Dissipation for Heat Exchange System

2008 ◽  
Author(s):  
Andrei A. Akhremenkov ◽  
Anatoliy M. Tsirlin ◽  
Vladimir Kazakov
Keyword(s):  
Heat Exchanger ◽  
Heat Exchange ◽  
Heat Load ◽  
Point Of View ◽  
Exchange System ◽  
Heat Exchange System ◽  
Heat Exchange Surface ◽  
Minimal Dissipation ◽  
The Difference ◽  
Exchange Surface

In this paper we consider heat exchange system from point of view of Finite-time thermodynamics. At first time the novel estimate of the minimal entropy production in a general-type heat exchange system with given heat load and fixed heat exchange surface is derived. The corresponding optimal distribution of heat exchange surface and optimal contact temperatures are also obtained. It is proven that if a heat flow is proportional to the difference of contacting flows’ temperatures then dissipation in a multi-flow heat exchanger is minimal only if the ratio of contact temperatures of any two flows at any point inside heat exchanger is the same and the temperatures of all heating flows leaving exchanger are also the same. Our result based on those assumptions: 1. heat transfer law is linear (17); 2. summary exchange surface is given; 3. heat load is given; 4. input tempretures for all flows are given; 5. water equivalents for all flows are given.

scholarly journals The Analysis for Energy Consumption of Marine Air Conditioning System Based on VAV and VWV

2018 ◽  
Vol 38 ◽  
pp. 04012
Author(s):  
Sai Feng Xu ◽  
Xing Lin Yang ◽  
Zou Ying Le
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Air Conditioning ◽  
Water Volume ◽  
Pump System ◽  
Air Conditioning System ◽  
Variable Air Volume ◽  
Air Volume ◽  
Marine Air ◽  
Variable Water

For ocean-going vessels sailing in different areas on the sea, the change of external environment factors will cause frequent changes in load, traditional ship air-conditioning system is usually designed with a fixed cooling capacity, this design method causes serious waste of resources. A new type of sea-based air conditioning system is proposed in this paper, which uses the sea-based source heat pump system, combined with variable air volume, variable water technology. The multifunctional cabins’ dynamic loads for a ship navigating in a typical Eurasian route were calculated based on Simulink. The model can predict changes in full voyage load. Based on the simulation model, the effects of variable air volume and variable water volume on the energy consumption of the air-conditioning system are analyzed. The results show that: When the VAV is coupled with the VWV, the energy saving rate is 23.2%. Therefore, the application of variable air volume and variable water technology to marine air conditioning systems can achieve economical and energy saving advantages.

Sign in / Sign up

Export Citation Format

Share Document