The improvement of the overall energy efficiency of the data center is inseparable from the improvement of the energy efficiency of its components, or the improvement of the energy efficiency of the equipment can directly and effectively improve the energy efficiency of the data center, such as improving the energy efficiency of servers and reducing power loss. To the bottleneck, its energy efficiency cannot be improved again or the cost rises sharply due to the improvement of energy efficiency. When difficulties in improving the energy efficiency of equipment are encountered, methods to improve the energy efficiency of the system are usually adopted. For example, through load optimization, the server can work in a highly energy-efficient state, and the standby server can be optimized. For matching, because the flexibility of energy efficiency in the system is relatively large, it usually starts from a small system, gradually introduces more variables, and involves more and more systems. At the same time, considering management factors, it has become an organizational method to improve energy efficiency way.

1. Product energy saving technology

1.1 Server

The essential role of a data center is to provide computing resources, and the largest proportion of data center energy consumption is the energy consumption of information equipment. It is unreasonable to simply pursue extremely low power usage efficiency (PUE) aside from computing power.

1.2 Rack-level energy-saving optimization technology

Cabinet-level energy-saving technologies mainly include: automatic power adjustment according to load changes caused by business volume and business type; adopting a complete power supply and distribution method to improve the power density of a single cabinet; increasing computing density, unified power supply and shared cooling management and other technical measures.

2. System energy efficiency improvement technology

Reasonable air-conditioning air organization at the end is the basis and premise of energy saving and consumption reduction of air-conditioning system. Increasing the supply and return air temperature of precision air conditioners and the supply and return water temperature of cooling sources, such as COOLNET Cybermaster Series and Cool-row Series precision air conditioning, has always been the consensus of energy saving in data center HVAC systems, but often the above energy-saving measures cannot achieve the theoretical high-efficiency energy-saving goals due to unreasonable end airflow. Reasonable airflow organization is reflected in the uniform distribution of air-conditioning cold airflow in the air inlet area of the cabinets in the data center room, and the temperature fields in the vertical and horizontal directions are in a relatively balanced state.

The application of AI intelligent control technology helps to improve the energy efficiency of data centers, and is mainly used in power supply and distribution systems and refrigeration and air conditioning systems. Increasing the use of renewable energy is a key step in reducing carbon emissions. The AI intelligent control technology is applied to the automatic control logic of the refrigeration and air conditioning system. By predicting outdoor weather parameters, analyzing load changes, calculating the characteristics of cold source equipment, optimizing the control logic of the cold source system, and maximizing the use of outdoor natural cold sources, the realization of High efficiency and energy saving of refrigeration system.

3. Improving energy efficiency at the organizational level

There are many factors that affect the energy consumption of data centers, including server systems, air conditioning and refrigeration systems, power supply and distribution systems, equipment room decoration, lighting, power distribution equipment, power supply and distribution cables, etc., and even the level of operation and maintenance will affect the data center. As a result, COOLNET Modular Data Center, Container Data Center Solutions could be the best choice for customer to control comsumption. Through the sub-item monitoring and analysis of the operating load and energy efficiency of each subsystem of the data center, the energy consumption problems existing in the operation of each subsystem are found, and the operation adjustment and technical improvement of each subsystem are targeted to reduce the cost of the data center. power consumption and improve overall energy efficiency.