The concept of the data center was initially imported and gained widespread usage after 2005 with the rise of Internet companies. It became a crucial infrastructure, particularly on the Internet and IT industry. This led to the establishment of enterprise-built data centers (EDCs) and Internet data centers (IDCs), reaching a peak around 2010. The rapid growth of data centers in China, driven by emerging technologies like 5G and cloud computing, as well as increasing user demand, has resulted in a significant increase in electricity consumption. This poses new challenges for power supply and requires attention from various sectors to progress further.

Datacenter energy in China

Despite 15 years of rapid development, China has not yet established a unified data center energy efficiency index system, nor are their corresponding evaluation standards. As a result, the energy efficiency data released by each data center often fails to accurately reflect the actual energy consumption levels. The lack of comparability between energy efficiency results from different data centers creates inconvenience for the industry and hinders the achievement of energy conservation and emission reduction goals.

Today, based on research conducted by international organizations and the actual development of data centers in China, we will share four energy efficiency index evaluation guidelines that can be applied to edge data centers. These guidelines include the following indicators: Power Usage Effectiveness (PUE), local PUE, cooling/power supply load coefficient, and renewable energy utilization rate. We will also provide specific measurement methods for these indicators to ensure accurate evaluation of energy efficiency in these types of data centers.

Data center energy consumption composition

The power consumption of data centers primarily consists of IT equipment, refrigeration equipment, power supply and distribution systems, as well as lighting and other data center equipment that consume electricity.

Evaluation of data center energy efficiency indicators

These four energy efficiency indicators have been established based on the measurability, comparability, and optimization of data center energy efficiency. They serve as the fundamental indicators for evaluating data center energy efficiency.

1) Power Usage Effectiveness (PUE)

PUE is widely accepted and adopted as a measurement of data center infrastructure energy efficiency globally. Its calculation formula is as follows:

PUE = total power consumption of the data center ÷ power consumption of IT equipment

Total data center power consumption refers to the overall power consumed to maintain the normal operation of the data center. It includes the sum of power consumption from IT equipment, refrigeration equipment, power supply and distribution systems, and other facilities. Only the power consumption of IT equipment is considered “meaningful” electricity in a data center. The PUE value calculates how much of the total electrical energy provided to the data center is actually utilized by IT equipment. The range of PUE values is from 1.0 to ∞, where higher values indicate greater power consumed by supporting infrastructure such as cooling and power supply.

2) Partial PUE (pPUE)

Local power utilization efficiency is a derivative of the PUE concept. It evaluates and analyzes the energy efficiency of specific areas or equipment within data centers. When using the pPUE index for data center energy efficiency evaluation, different partitions (represented by Zones) within the data center are identified as needed. For example, a computer room in a multi-storey data center building or a container module in a container data center can be considered as Zones.

The PUE calculation formula for a Zone 0 data center is:

PUE = (N0 + N1 + N2 + I1 + I2) ÷ (I1 + I2)

The PUE calculation formula for Zone 1 and Zone 2 data centers is:

pPUE1 = (N1 + I1) ÷ I1

pPUE2 = (N2 + I2) ÷ I2

Local PUE reflects the energy efficiency of specific equipment or areas within the data center. Its value may be greater or less than the overall PUE. To improve the energy efficiency of the entire data center, it is generally necessary to start by enhancing the energy efficiency of equipment or areas with high local PUE values. pPUE is suitable for assessing energy efficiency locally, such as in containers, modular data centers, or larger data centers composed of multiple buildings and machine rooms.

3) Cooling Load Factor (CLF) and Power Load Factor (PLF)

CLF represents the cooling load factor and is defined as the ratio of power consumption of data center cooling equipment to IT equipment power consumption:

CLF = power consumption of refrigeration equipment ÷ power consumption of IT equipment

PLF represents the power supply load factor and is defined as the ratio of power consumption of power supply and distribution systems to IT equipment power consumption of data centers:

PLF = power consumption of power supply and distribution systems ÷ power consumption of IT equipment

CLF and PLF serve as complements and extensions to PUE. By separately calculating these two indicators, the energy efficiency of cooling systems and power supply and distribution systems can be further analyzed.

4) Renewable Energy Ratio (RER)

RER measures the utilization of renewable energy in data centers to promote the use of renewable, carbon-free, or low-emission energy sources. RER is calculated as follows:

RER = Powered by Renewable Energy ÷ Total data center power consumption

Renewable energy refers to energy sources that can be naturally replenished, including solar energy, wind energy, water energy, biomass energy, geothermal energy, and marine energy. Renewable energy is environmentally friendly or relatively harmless, widely distributed, and suitable for on-site development and utilization.

In addition to the above-mentioned indicators, data centers have other energy efficiency indicators that can be referenced, such as the Carbon Utilization Efficiency (CUE) and Carbon Emission Factor (CEF) proposed by TGG. However, considering China’s specific national conditions, the implementation of these standards will require time.

How to initiate the energetic change

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About Juan D. Guerra

Data centers have become significant energy consumers, and addressing environmental concerns cannot be delayed. Stay informed, stay connected. Join our newsletter to receive regular updates, insightful articles, and exclusive content straight to your inbox. Next article is about Artificial Intelligence Network: Enhancing Communication Capabilities . Stay ahead of the curve and never miss out on the latest news and trends. Subscribe today and be part of our community!, This article is credited to 前海乐成LEDC en 知乎。