In order to measure progress, one needs a base line, so the first step is to take a rough energy inventory of all your major equipment. This "clipboard approach" involves using a clamp-on ammeter to monitor the current on each unit's power inputs to quickly establish the facility's base-line consumption. In a typical 1-5MW enterprise data center, only 10 to 20 measurements will allow you to account for 80 to 90 percent of your energy budget, although not at any great degree of granularity. While this rough inventory will probably be somewhat inaccurate (+/- 20 percent), it will still provide a very good starting point that identifies the major power loads-and the biggest opportunities for energy savings.
Once you've recorded the power consumption of all your major subsystems, create a matrix which groups the subsystems into three functional categories:
1. IT (servers and storage)
2. Other (cooling and power distribution loss)
The base-line audit of our "typical" data center reveals that cooling accounts for 50 percent of our power bill, with another 14 percent eaten by power distribution losses and 2 percent used for lighting. Our servers use a bit over 23 percent of the power, with the storage arrays accounting for another 10 percent. This means that only 500kW-or 33 percent of the 1.5MW it consumes-is actually used for data processing.
This is very typical of what you'd expect to see in a mature facility. Whatever your particular results are, they will give you a good idea of where the bulk of the power is going, and will help you to identify the most rewarding energy conservation strategies to pursue at this time.
Use the base-line measurements you took to create a matrix that normalizes the potential energy savings of each strategy with respect to the data center's overall power consumption. For example, an improvement that cuts your cooling system's energy consumption by 20 percent should be multiplied by 50 percent (the fraction of the overall power budget that the cooling system consumes) to give you a normalized savings of 10 percent. Using this matrix makes it easy to identify the biggest energy-saving opportunities for your particular facility.