Driving data center PUE, efficiency

06/09/2015


Source: HP Data Center Facilities ConsultingReliability considerations

Most reliability strategies revolve around the use of multiple power and cooling modules. For example, the systems can be arranged in an N+1, N+2, 2N, or 2(N+1) configuration. The basic module size (N) and the additional modules (+1, +2, etc.) are configured to pick up part of the load (or even the entire load) in case of module failure, or during a scheduled maintenance event. When all of the UPS modules, air-handling units, and other cooling and electrical equipment are pieced together to create cohesive power-and-cooling infrastructure designed to meet certain reliability and availability requirements, then efficiency values at the various loading percentages should be developed for the entire integrated system (see Table 1). When all of these components are analyzed in different system topologies, loss curves can be generated so the efficiency levels can be compared to the reliability of the system, assisting in the decision-making process.

When we use the language of reliability, the terminology is important. For example, “reliability” is the probability that a system or piece of equipment will operate properly for a specified period of time under design operating conditions without failure. Also, “availability” is the long-term average fraction of time that a component or system is in service and is satisfactorily performing its intended function. These are just two of the many metrics that are calculated by running reliability analyses.

One of the general conclusions often drawn from reliability studies is that data center facilities with large IT loads have a higher chance of component failure than data centers with small IT loads. Somewhat intuitive, the more parts and pieces in the power-and-cooling infrastructure, the higher the likelihood of a component failure. Also, system topology will drive reliability as found when comparing electrical systems with N, N+2, and 2(N+1) configurations. These systems will have probabilities of failure (over a 5-year period) that range from a high of 83% (N) to a low of 4% [2(N+1)].

When analyzing the energy performance of data centers that use this module design, it becomes evident that at partial-load conditions, the higher reliability designs will exhibit lower overall efficiencies. This is certainly true for UPS and PDU equipment and others that have low efficiency at low-percent loading.

Understanding that PUE is comprised of all energy use in the data center facility, the non-data center areas can be large contributors to the total energy consumption of the facility. While it is not advisable to underestimate the energy consumption of non-data center areas, it is also not advisable to overestimate. Like most areas in commercial buildings, there are changes in occupancy and lighting over the course of days, weeks, and months, and these changes will have to be accounted for when estimating energy use. When performing energy estimations, develop schedules that turn lights and miscellaneous electrical loads on and off, or assign a percentage of total load to the variable. It is best to ascertain these schedules directly from the owner. If unavailable, industry guidelines and standards can be used.

Certainly, no two data centers are exactly the same, but developing nomenclature and an approach to assigning operating schedules to different rooms within the data center facility will be of great assistance when energy-use calculations are started:

  • Data center: primary room(s) housing computer, networking, and storage gear; raised floor area or data hall
  • Data center lighting: lighting for data center(s) as defined above
  • Secondary lighting: lighting for all non-data center rooms, such as UPS, switchgear, battery, etc.; also includes appropriate administrative areas and corridors
  • Miscellaneous power: non-data center power for plug loads and systems such as emergency management services, building management systems, fire alarm, security, fire-suppression system, etc.
  • Secondary HVAC: cooling and ventilation for non-data center spaces including UPS rooms. It is assumed that the data center spaces have a different HVAC system than the rest of the building.

The relationship between the IT systems, equipment, and the cooling system is an important one. The computers rely heavily on the cooling system to provide adequate air quantity and temperature. Without the proper temperature, the servers and other IT equipment might experience slower processing speed or even a server-initiated shutdown to prevent damage to internal components. There are a number of ways to optimize air flow and temperature.

 Air-management and -containment strategies

Proper airflow management creates cascading efficiency through many elements in the data center. If done correctly, it will significantly reduce problems related to re-entrainment of hot air into the cold aisle, which is often the culprit of hot spots and thermal overload. Air containment will also create a microenvironment with uniform temperature gradients, enabling predictable conditions at the air inlets to the servers. These conditions ultimately allow for the use of increased server-cooling air temperatures, which reduces the energy needed to cool the air. It also allows for an expanded window of operation for economizer use.

Traditionally, effective airflow management is accomplished by using a number of approaches: hot-aisle/cold-aisle organization of the server cabinets; aligning of exhaust ports from other types of computers (such as mainframes) to avoid mixing of hot exhaust air and cold supply air; and maintaining proper pressure in the raised-floor supply air plenum; among others. But arguably the most successful air-management technique is the use of physical barriers to contain the air and efficiently direct it to where it will be most effective. There are several approaches that give the end user a choice of options that meet the project requirements:

 Hot-aisle containment: The tried-and-true hot-aisle/cold-aisle arrangement used in laying out the IT cabinets was primarily developed to compartmentalize the hot and cold air. Certainly, it provided benefits, compared to layouts where IT equipment discharged hot air right into the air inlet of adjacent equipment. Unfortunately, this circumstance still exists in many data centers with legacy equipment. Hot-aisle containment takes the hot-aisle/cold-aisle strategy and builds on it substantially. The air in the hot aisle is contained using a physical barrier, i.e., a curtain system mounted at the ceiling level and terminating at the top of the IT cabinets. Other, more expensive techniques use solid walls and doors that create a hot chamber that completely contains the hot air. This system is generally more applicable for new installations. The hot air is discharged into the ceiling plenum from the contained hot aisle. Because the hot air is now concentrated into a small space, worker safety must be considered—the temperatures can get quite high.

Cold-aisle containment: While cold-aisle containment may appear to be simply a reverse of hot-aisle containment, it tends to be much more complicated in its operation. The cold-aisle containment system can also be constructed from a curtain system or solid walls and doors. The difference between this and hot-aisle containment comes from the ability to manage airflow to the computers in a more granular way. When constructed out of solid components, the room can act as a pressurization chamber that will maintain the proper amount of air required by the servers via monitoring and adjusting the differential pressure. The air-handing units serving the data center are given instructions to increase or decrease air volume to keep the pressure in the cold aisle at a preset level. As the server fans speed up, more air is delivered; when they slow down, less is delivered. This type of containment has several benefits beyond traditional airflow management mentioned above.

Self-contained, in-row cooling: To tackle air-management problems on an individual level, self-contained, in-row cooling units are a good solution. These come in many varieties, such as chilled-water-cooled, air-cooled DX, low-pressure pumped refrigerant, and even carbon-dioxide-cooled. These are best applied when there is a small grouping of high-density, high-heat-generating servers that are creating difficulties for the balance of the data center. This same approach can be applied to rear-door heat exchangers that essentially cool down the exhaust air from the servers to room temperature.

Water-cooled computers: Not exactly a containment strategy, water-cooled computers contain the heat in the water loop that removes heat internally from the computers. Once the staple cooling approach for large mainframes for data centers of yore, sectors like academic and research that use high-performance computing continue to use water-cooled computers. The water-cooling keeps the airflow through the computer to a minimum (the components that are not water-cooled still need airflow for heat dissipation). Typically, a water-cooled server will reject 10% to 30% of the total cabinet capacity to the air—not a trivial number when the IT cabinet houses 50 to 80 kW of computer equipment. Some water-cooled computers reject 100% of the heat to the water. Water-cooling similarly allows for uniform cabinet spacing without creating hot spots. Certainly, it is not a mainstream tactic to be used for enhancing airflow management, but it is important to be aware of the capabilities for future applicability.

What's next?

Looking at the types of computer technology being developed for release within the next decade, one thing is certain: The dividing line between a facility’s power and cooling systems and the computer hardware is blurring. Computer hardware will have a much tighter integration with operating protocols and administration. Computing ability will include readiness and efficiency of the power and cooling systems, and autonomy to make workload decisions based on geography, historical demand, data transmission speeds, and climate. These are the types of strategies that, if executed properly, can significantly reduce overall data center energy use and reduce PUE far lower than today’s standards.


About the author

Bill Kosik is a distinguished technologist at HP Data Center Facilities Consulting. He is the leader of “Moving toward Sustainability,” which focuses on the research, development, and implementation of energy-efficient and environmentally responsible design strategies for data centers. He is a member of the Consulting-Specifying Engineer editorial advisory board.


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