How to Calculate the PUE of a Datacenter
The infrastructure and the processing unit in data center facilities consume huge amounts of energy. If a facility doesn't operate efficiently, its energy consumption is even higher. That's why it's critical to monitor the performance of a data center using metrics such as the PUE. So, what is PUE in data centers?
The operators can calculate it to evaluate working efficiency and measure the effect of the changes they've made to enhance the performance. So, how do they calculate the PUE of a data center?
In this post, we will learn many things about the average data center PUE and how lowering it can help reduce power consumption and costs.
Table of Contents
How to Calculate the PUE of a Data Center
How Often Should I Calculate the PUE of a Data Center?
1. Energy Reuse Effectiveness (ERE)
2. Water Usage Effectiveness (WUE)
3. Carbon Usage Effectiveness (CUE)
What is PUE in Data Centers?
PUE stands for Power Usage Effectiveness. It's a definition used to measure the energy efficiency, and is defined this way:
PUE = Total facility energy usage / IT equipment energy usage
In other words, PUE specifies the amount of power used to energize the cooling, lighting, and other support systems in a data center, compared to the energy used by the computer servers, storage devices, and networking equipment.
The average data center Power Usage Effectiveness can be in three possible values:
|
PUE Value |
Meaning |
|
PUE = 1 |
All energy is ideally used by the IT equipment. |
|
PUE > 1 |
Just some of the energy is used by IT equipment. |
|
PUE < 1 |
The data center is generating more energy than it is using (rare case). |
What is DCiE in Data Centers?
DCiE stands for Data Center Infrastructure Efficiency. Similar to the PUE, DCiE is also used to measure the efficiency of a data center.
As a matter of fact, DCiE is essentially the reciprocal of PUE:
DCiE = (1 / PUE) x 100
Below, you can see an example of the relationship between those metrics:
|
Efficiency Level |
PUE |
DCiE |
|
Highly Inefficient |
3.0 |
33% |
|
Inefficient |
2.5 |
40% |
|
Average |
2.0 |
50% |
|
Efficient |
1.5 |
67% |
|
Highly Efficient |
1.2 |
83% |
It's needless to say that higher DCiEs and lower PUEs are preferable for data centers to work as efficiently as possible. Enhancing the DCiE helps data center operators reduce their energy costs and environmental impact, and improve the reliability and performance of their IT infrastructure.
How to Calculate the PUE of a Data Center
To calculate the PUE and DCiE, a step-by-step procedure should be followed:
Step 1: Measure the total energy consumed by the data center over a certain period. Use energy meters or utility bills for your measurement.
Step 2: During the same period, measure the energy consumed by your IT equipment. Use energy meters or add up the power consumption of each device.
Step 3: Divide the total energy consumed (from Step 1) by the energy consumed by the IT equipment (from Step 2) to calculate the PUE.
Step 4: Reverse the value you calculated and multiply it by 100 to obtain the DCiE because it’s the inverse of the PUE.
Step 5: Interpret the results. See if the average PUE is more or less than unity. Refer to the table above in this post to interpret the number you've calculated.
Step 6: Analyze the results and find areas for improvement. If the value is high, the data center isn't performing efficiently and there are issues such as poor cooling or power distribution.
How Often Should I Calculate the PUE of a Data Center?
How often you need to calculate the average value depends on various factors, including:
- The size of the data center
- The complexity of the infrastructure
- Your energy efficiency goals
Despite this dependency, it's generally recommended that you calculate the average PUE at least once a month. It helps you monitor the energy efficiency and detect deviations from the expected energy consumption patterns.
Keep in mind that if there are considerable changes to your data center — such as adding new IT equipment or making changes to the cooling system — you need to recalculate the PUE to make sure your facility works efficiently.
The Importance of a Low Value
A low PUE shows that the facility is operating efficiently and the waste of energy is at a minimum. Data centers should try to minimize it to save energy costs and keep the environment green.
Here are the main advantages of reducing the average PUE:
- Lower Energy Costs: Reducing the energy used by various systems such as cooling and lighting leads to lower PUEs and energy costs.
- Improved Reliability: A low value improves the reliability and performance of IT equipment because the cooling and power distribution systems are operating more steadily.
- Lowered Environmental Impact: Data centers generate a huge amount of greenhouse gas emissions. Reducing their PUE can lower their carbon footprint.
- Improved Reputation: Lower values can help a data center differentiate itself from rivals and build a positive reputation in the industry.
- Scalability: A low PUE makes it easier to scale up operations as demand grows, without the need for additional energy and cooling infrastructure.
Other Efficiency Metrics
Except for PUE and DCiE, some other efficiency metrics are commonly used to evaluate the performance of a data center.
1. Energy Reuse Effectiveness (ERE)
ERE is used to measure the amount of energy that is reused or recycled, including the reuse of waste heat from IT equipment to provide hot water.
ERE = Total energy reused in the facility / Total energy consumed by the data center
2. Water Usage Effectiveness (WUE)
WUE is used to measure the amount of water used to support IT equipment, including the cooling water used by chillers.
WUE = Total annual water consumption by facility / Total IT equipment energy consumption
3. Carbon Usage Effectiveness (CUE)
CUE is used to measure the amount of carbon emission generated by a data center, including those from the use of electricity and other fuels.
CUE = Total carbon emissions generated by the facility / Total IT equipment energy consumption
Final Words
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