Products - Data Center Infrastructure - Delta Electronics (Singapore)

Data Center Infrastructure

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Success Cases

Delta’s Data Center Solutions Help Formosa Plastics Group (FPG) Create its New Energy-Efficient Backbone Enterprise Data Center

Delta's Modular Dynamic Data Center provides full support for Capital Airport Power and Energy Command Center

Delta UPS and DCIM solutions power new, green data center and data lab for Bytesnet

Success Cases

Delta’s Data Center Solutions Help Formosa Plastics Group (FPG) Create its New Energy-Efficient Backbone Enterprise Data Center

Delta's Modular Dynamic Data Center provides full support for Capital Airport Power and Energy Command Center

News

07/22/2021Delta Recognized by NASSCOM as a Prominent Electric Infrastructure Provider in the Indian Data Center Ecosystem

06/03/2021Delta Named as Winner of China Telecom Global’s Excellent Technical & Service Partners Award in EMEA

10/02/2019Delta Unveils Data Centre Infrastructure Solutions at Data Centre World Singapore 2019

Technical Articles

11/25/2019Efficient Management of the Data Center's Engineering Infrastructure

The tools for automating control and monitoring tasks in data centers are relatively new to the market. The first products of this kind offered various features, including keeping records of equipment as well as controlling its movement and maintenance. Today, it is not just a matter of drawing beautiful diagrams of server rooms with database binding. Nowadays, modern systems make it possible to solve a wide variety of tasks related to the operation of a data center in real time. In this article, we will take a look at the problems arising in this industry and try to look for ways to address them. Scaling Diversity Two control loops can be distinguished in the engineering infrastructure of a data center. One deals with cooling and distribution of power at the rack level, while the other works at the level of the entire facility and deals not only with power and air conditioning but also various auxiliary subsystems (fire suppression, access control, and others). Often, these loops and even their components are independent of each other and are operated by different teams of operators. Companies are not always willing to purchase integrated solutions for engineering infrastructure management. Usually, commercial data centers do not have such an option. However, in the corporate segment, it is not uncommon for the company's management to try to save money and to agree to include only fragmented systems for air-conditioners and UPS in the estimate. Lack of communication between control circuits, different levels of automation of the data center subsystems, and a fleet of different equipment vendors complicate the coordinated work of all parts of the facility, making optimization impossible. Control Modes In the worst case small scale scenario, data center subsystems are controlled manually, and the installation and movement of equipment are documented using Microsoft Excel. Often, the paperwork is a mess, which is quite natural since keeping a correct database using spreadsheets is a very challenging task. When the quantity of racks is measured in tens, problems with manual accounting are inevitable. Replacement of equipment in such a data center takes place only as a failure occurs, which increases overhead costs and downtime in the event of an accident. If downtime is critical for data center owners, the reactive control model is used. In this case, the troubleshooting procedure is regulated, and the accompanying paperwork is maintained. However, the process is based on the experience of employees and their knowledge of a particular data center. In case of an accident, the problem is eliminated quickly enough, but there are serious difficulties when it comes to prevention due to the lack of opportunities for a comprehensive analysis of the causes of a malfunction. In a situation when only a couple of experts know how to deal with all the processes of facility management and in case, for example, one expert is dismissed, new problems arise. A more advanced management model is always service-oriented. It assumes the presence of complete paperwork covering all subsystems of a facility. It clearly defines the rules and procedures for replacement and the preventive maintenance of equipment, and keeps a thorough accounting of its installation and movement, while operational services prepare reports on the parameters of engineering systems, accidents, and actions taken by personnel to eliminate them. The main feature of the service-oriented approach to data center management is proactivity. This model not only allows analyzing the causes of errors but also anticipating problems before they occur. Workarounds to quickly restore the availability of services can be established. Of course, such an approach is impossible without the introduction of a single automated monitoring and dispatching system for all critical data center subsystems. Practice shows that employee actions often cause their failures. There is always a shortage of highly-skilled experts, but if the dispatching center is automated and all the facility maintenance rules and regulations are formalized, most of the personnel need only basic knowledge. Monitoring and Dispatching About ten years ago, DCIM (Data Center Infrastructure Management) solutions, which combine all engineering subsystems into a single logical structure, appeared on the market. The first versions of DCIM allowed drawing up schemes/plans of objects and maintaining paperwork, but now their functionality has changed significantly. Modern solutions can interact with the monitoring tools built into the equipment of different manufacturers and connect additional sensors, controllers, signal converters, and data collection systems. Most often, information on energy consumption at all levels, up to the rack level, temperature and humidity in racks, cooling systems and inside ducts, as well as data on fluid leaks are collected. It is the minimum necessary to accomplish the intended purpose. Once DCIM is in place, the customer receives an integrated monitoring and control environment that will include all the critical subsystems and even IT equipment in some cases. Its main task is to combine the data streams coming from the maximum number of available sources. The information is collected and processed in real time, which gives the service personnel a complete picture of the functioning of all subsystems of the data center, including, if necessary, its computing power. This is where we see yet another advantage of DCIM, which is reducing the impact of human factors on the performance of data center subsystems. The Problem of Choice There could be different scenarios for its introduction, but it is best to lay down DCIM at the design stage of the facility. There are also options for integrating existing stand-alone subsystems using equipment from different manufacturers. The choice of a solution at the design stage of the data center does not cause any problems; it is usually done by a system integrator who helps pick the necessary hardware and software. The situation with an existing data center is much more complicated. In this case, it is necessary to gather a working group, including representatives of all interested departments. It is required to make a list of all the parameters and nodes of the infrastructure that will be monitored, and arrange them in descending order of importance. Next, it is necessary to audit the protocols and means of communication supported by the infrastructure equipment, as well as to consider what additional sensors and controllers will have to be installed. With all this information, you can select the necessary software solutions, list additional equipment, and calculate the project budget. It is an excellent idea to outsource the introduction of DCIM into the existing object completely. Errors at the design stage will cost more than the system integrator services. Initially, DCIM systems were local, but now many developers begin to offer them as a service (SaaS). This approach allows for a significant reduction in capital expenditures. Optimization Points The main item in the structure of the data center's operating expenditures is the cost of electricity. The operation of IT equipment and cooling systems racks up high electric bills. Therefore, optimizing energy consumption is a priority. It depends on a vast number of external and internal factors. For example, climate and weather conditions, including seasonal changes, directly affect cooling systems. One can also add peaks and drops in the load on computing and telecommunications equipment and dozens of other nuances. It is impossible to take them all into account manually, but the DCIM system will allow you to accumulate real operating statistics and analyze them, identifying problem areas in the infrastructure of the facility. One of the most critical indicators for a data center is the Power Usage Effectiveness (PUE) coefficient, which shows how much power is spent on IT load operation and how much is spent on auxiliary needs, such as cooling and UPS operation, and losses in the distribution system. It is calculated by dividing total energy consumption by IT equipment consumption. Until recently, the PUE factor of 1.6 to 2.0 has been considered acceptable. Now, however, the market requires more efficient data centers, so the struggle for the values starting from 1.1 to 1.2 is on. Most often, consumption is measured at the output of the UPS, at the output of the power distribution unit, and for the actual use of IT equipment. Based on the data obtained, it is possible to determine the energy efficiency of the data center quite accurately. However, the PUE does not reflect all the nuances associated with it. This factor is still important, but it does not allow, for example, taking into account the downtime of servers or identifying problematic hot spots. Also, reducing the PUE to values close to one often comes at the expense of reducing the reliability of the data center—accidents and a reduction of the service life of equipment can negate the effect of energy savings. Modern control systems collect energy consumption data from servers, racks, and distribution equipment. It is even possible to monitor each socket. Statistics on the consumption of critical resources can be visualized in an easy-to-understand form, which makes it easier to find the most energy-intensive areas and to optimize costs. Load reduction periods can also be identified to schedule maintenance during these periods. Consumption peak analysis allows keeping the power reserve in the range of 10%-15% instead of 30%-40%, as in the case of manual control. Moreover, that's significant savings, too. DCIM-class solutions also monitor other engineering subsystems. For example, they help map the airflow to identify problematic areas of the air conditioning and climate control system, which is second only to IT equipment in terms of electricity consumption in the data center. Do not forget about troubleshooting even before serious problems occur, prevention, and rapid elimination of the issues, which increases the reliability of the infrastructure and also reduces costs. Manual control is possible only in the case of a small server room, but when there are dozens or even hundreds of racks in the server room, the introduction of DCIM becomes a necessity. Industry Outlook So far, we have only talked about the engineering infrastructure, because IT infrastructure management is considered a separate task. Usually, this is done using systems that are not related to DCIM. When it comes to commercial data centers, the work of IT equipment is in the area of the responsibility of customers. However, the development of virtualization and converged/hyperconverged architecture is gradually changing the situation. Today, developers are developing the solutions that enable real-time monitoring of the status of virtual servers on individual physical devices, and IT vendors are embedding a vast number of sensors in their products to monitor power consumption and temperature. Effective load planning in virtual environments must cover all levels: operating systems and applications, servers, storage systems, telecommunications equipment, and communication channels, and, of course, physical resources, such as power, cooling, humidification, and others. DCIM solutions are no longer a "thing in itself" in large corporate data centers. Their close integration with virtualization platforms and IT infrastructure management systems is only a matter of the near future. InfraSuite Manager - Data Center Infrastructure Management (DCIM)

09/17/2019The evolution of data center cooling

There are around 8.5 million data centers in the world. 3 million of them are located in the US alone, if you count the smaller ones, too. That's nearly a data center for every 100 people. And they make up nearly 2% of all the electricity consumed in America as well. What happens to all that power? 100% of the electricity consumed by IT hardware is converted into heat. But servers don't like heat. So, you need powerful (but efficient) data center cooling. Cooling by conventional methods requires power though, too. So much power, in fact, that cooling can represent over 50% of the total power requirement of a data center. That basically makes our data centers enormous electric heaters. And we keep building more of them. It's a trend that threatens to make sustainability more difficult for businesses and even countries. Luckily, there are more efficient alternatives to conventional data center cooling methods. The measuring stick used to determine how efficient a data center's cooling system operates is known as Power Usage Effectiveness, or PUE. The lower your PUE, the better. It's the ratio of the total power used by a data center to the energy delivered to the IT hardware. A rating of 2.0 is considered standard, 1.4 is good, and 1.0 is the best PUE rating you can achieve. Doing it the old-fashioned-way: raised floor cooling For the last half century or so, most data centers were cooled with pressurized air from a raised floor. A CRAC (Computer Room Air Conditioner) or a CRAH (Computer Room Air Handler) cools air that is moved by constant speed fans. This type of system worked fine when compute densities were low, and efficiency was not at the top of anyone's priority list. But the disadvantages became more meaningful over time. PUEs of over 2.0 are common here, for instance. A big problem with this type of cooling is the temperature gradient from the bottom of the rack to the top, which is known as stratification. The servers near the floor get the coolest air, and the servers at the top of the rack often have a considerably warmer inlet temperature. If you increase the air flow to mitigate this problem, efficiency decreases because air is now streaming past the face of the server rack and mixing with hot return air. Consequently, containment strategies such as hot aisle/cold aisle configurations were developed. These layouts also reduce recirculation, which occurs when hot air from the back of the server gets drawn back in the front, potentially resulting in dangerous equipment temperature levels. Modern precision cooling solutions Cooling technology has come a long way since the days of constant-speed fans blowing air into a raised floor. The increase in density has made these advances necessary. With cold air containment and hot air containment designs, the limitations of stratification and bypass have been largely overcome. In-row cooling units allow for even greater efficiency. Here, variable speed fans installed in cooling units that are integrated into the rows themselves allow data center operators to control temperatures and energy consumption with much greater precision. The energy consumed by these variable-speed fans is significantly lower than with systems that use constant-speed fans. The use of economizers is on the rise It's hard to imagine that after decades of building data centers, the future of cooling them could be so very open and undecided. The underlying physics has not changed. Yet approaches still vary greatly. Part of this can be explained by climatic differences in geographic locations around the globe. One of the most promising strategies to save energy when cooling data centers is known as free cooling or economizing. In this approach, outside air is used in a cooling tower or to blow off heat from a chiller. This method is of course dependent on the temperature of air outside the data center being low enough to provide the necessary cooling. Cooler climates have a decided advantage here. Electricity is not the only resource a data center consumes Some alternative methods of cooling data centers that use cooling towers consume significant quantities of water. Yet many data centers are in drought-stricken parts of the world. Even when they're not, water is a valuable natural resource that we must always try to conserve. This would, on the surface at least, appear to be an advantage for dry cooling systems. Taking a more holistic view, however, we must also consider that the steam phase of a fossil fuel power plant also consumes water. So much water, that the extra power required by dry cooling systems results in higher water consumption for dry cooling in total versus onsite cooling towers. Fresh air cooling tempts with low PUE The only thing that is certain is that new approaches will be necessary. And there is no shortage of them! One of the most promising but also problematic approaches uses fresh outside air to cool the datacenter. With fresh air, PUEs that get very close to 1.0 are possible, as Yahoo has demonstrated with its “chicken coop” design. But bringing fresh air into the datacenter involves several challenges. First, outdoor temperatures need to be cool enough to provide safe inlet temperatures for the IT equipment. Otherwise, backup cooling systems are necessary. But humidity and dust are difficult problems to solve for as well. If humidity in the data center is too low, the risk of electrostatic discharge increases. Recent research, however, downplays the risk of ESD to IT equipment. Especially when servers are mounted in the rack, the risk of damage is low. And when technicians are working on data center equipment, it is always best practice to wear a grounded wrist strap. Excess humidity, on the other hand, may pose a greater risk. As air becomes more humid, it collects more dust particles, which can then gather on IT equipment. As the dust particles collect, they insulate components and make cooling more difficult. Zinc particles can also be deposited on circuits through humid air, eventually leading to shorts. Thus, air that is too humid requires dehumidification, which in turn consumes power and makes that low PUE less attractive. Another considerable issue with fresh air cooling is dust and smoke. Depending on the particulate matter in the air, fresh air cooling can require expensive filters. And even with good filtration in place, there is a risk that the extremely sensitive fire suppression systems in a modern data center can be triggered by air pollutants brought in by fresh air cooling. Immersion cooling Power line transformers require greater cooling than air cooling permits. This is achieved by submerging the circuits in a dielectric fluid, generally mineral oil. Since the oil conducts heat but not electricity, it does not damage the components. Immersion cooling can also be used for servers. With this method, heat is removed from the electronics much more efficiently than with air cooling. Vendors are now offering submersion cooling solutions for data center applications. How cool does your equipment truly need to be? IT equipment is rated according to classes defined by the American Society of Heating, Refrigeration, and Air Conditioning Engineers (ASHRAE) Technical Committee. These classes (A1 through A4) are part of a set of guidelines that ASHRAE has developed to determine the optimal temperature and humidity levels for data center hardware. A1 has the narrowest allowable temperature range. But many IT hardware makers are now producing A2-class equipment or even A3, which can give data centers greater flexibility in their cooling choices. Therefore, it is wise to carefully examine cooling requirements for your equipment instead of merely following the standard ASHRAE recommendations for classes A1-A4. Yes, of course, the hotter your equipment runs, the less reliable it will be. But the cost of a hardware failure is calculable. By forecasting the increased risk of failure with rising temperatures, it is possible to calculate the savings gained from cooling less versus the cost of an increased failure rate. And many companies are replacing their IT equipment after as little as three years anyway. In this case, the impact of higher temperatures may not be significant. Experimentation will lead to greater efficiency The most efficient cooling designs use free cooling or fresh air cooling in some form. Often, CRAC is required as a backup when outdoor conditions (hot, humid summer days) cannot provide enough cooling to meet a data center's requirements. One of the keys that we're seeing in all these pioneering designs, however, is that the building structure always plays an integral role. The days of planning a building, stuffing as much IT equipment into the whitespace as possible and thinking about cooling later may be over. New data center concepts will need to be architected with cooling in mind from the outset. A Dutch company, for instance, has implemented a system that removes heat from the building using a giant rotating aluminum disc known as the Kyoto disc. Half of the disc is inside the building and half is outside. As the disc rotates, it warms up inside and transfers the heat it has collected to the outdoor air by the time it returns. But the disc itself is rather large and requires a considerable amount of space for the interior and exterior areas the disc rotates through. Another option, instead of simply dumping of the waste heat into the environment, is to make good use of it. Projects already exist in which datacenters have been integrated with district heating and cooling systems. In this way, waste heat from the data center is being used to heat homes. This may be the most sustainable example of all. And district cooling systems offer a very efficient way to cool the data center, too. These are very exciting times, there are great competitive advantages to be gained by achieving high cooling efficiencies. The question of how to best achieve this is still completely open.

06/21/2019Modularity as a Requirement for ICT Infrastructure Engineering Systems

The problem of rapid growth in the volume of processed data has become more pressing than ever before. To address this problem, we need massive computing power, which is already growing exponentially and requiring the construction of new data centers, increasing the power density per rack, and improving energy efficiency. The facilities built several years ago must be upgraded to meet the continually changing industry requirements. Today, no one considers a data center as a completed one-off project. Every data center is built taking into account a further gradual increase of its capacity. At a time when scaling has become a significant issue in the construction of data centers, the modular approach and smart manufacturing solutions such as prefabricated buildings, come to the aid of the designers. With the help of the solutions above, you can delay the launch of currently unnecessary parts of the data center, which can then be quickly put into operation as needed. There are many myths and legends around prefabricated buildings, some of which this article will try to debunk. What Makes it Different From Traditional Solutions? All data center subsystems can be divided into three main categories: power supply, air-conditioning, and IT load. Let's include the telecommunication part with the latter to make things simpler. The modular approach means manufacturing these subsystems or their components as functionally complete products. It can be a factory-fitted cabinet or even a container intended for outdoor installation. The modular element can be defined as any sufficiently large prefabricated unit. However, it is usually either a container solution with some engineering infrastructure already installed at the factory or a solution that can be assembled into rack-mounted arrays that feature a chassis with a mounted busbar trunking system, a cable tray system, and other systems. This approach significantly simplifies the installation and commissioning of a data center. All the modules are tested at the production stage, which eliminates compatibility problems and various malfunctions that may slow down the commissioning process. Ideally, almost all of the engineering and rack-mount components of the server rooms are assembled at the same factory where a thorough check that simulates the load also takes place. Special heaters can be installed in cabinets instead of servers. After inspection, the system is disassembled for transportation, packaged, and delivered to the customer for further assembly onsite. Process parallelization speeds up commissioning even more. While the customer is dealing with the site and server room preparation, the data center is already being manufactured in the factory. The Reason Why Containers Haven't Taken Over the World The use of prefabricated modules allows for a faster response to ever-changing needs. It is possible to increase the capacity or, conversely, to dismantle resources that are no longer required. Containerized data centers can be moved from one place to another if necessary, but they are not a universal solution despite all their advantages. The reason for this is rather trivial—maximum legal dimensions for loads transported on public highways are relatively small. If you make a server room out of one container, it will be rather difficult to place a row of racks with all communications in it. The server cell will turn out to be too constricted, and there will be very little space left for equipment maintenance. It is only possible to increase the dimensions to a specific limit because delivering oversized containers can turn out to be way more expensive than their manufacturing. Such solutions are best used for small and mobile data centers. They can be quickly deployed on the spot and just as quickly taken apart when there is no more need for them. Sometimes, containers are used for purposes such as the expansion of traditional data centers if, for example, there is a possibility of building another server room. Building large container data centers have remained an idealistic notion, but the development of modularity in modern data centers has taken a different path. For the most part, modern data centers are still built of concrete or prefabricated metal structures, and use sandwich panels. In this case, only the elements of engineering infrastructure, rack equipment, and even IT-loads are modular. The main idea is to develop a standard solution once that can be replicated later, increasing its capacity and performance as needed. Modularity in Power Supply There are ready-made modular designs for quick installation of rack-mounted equipment and all the necessary busbar trunking and cable tray systems. Convergent and hyperconvergent solutions have been developed to put the IT load on the modular rails. Modularity is the most difficult to introduce for air-conditioning or uninterruptible power supply systems, but there are possible options. Modularity is now available for UPS solutions and such products are gaining popularity. Their advantages are distinct: the system's power can be increased in relatively small increments by adding additional battery cabinets. Installation and maintenance are also simplified, and, in the event of an accident, only a part of the UPS, which can be replaced by the data center staff on their own, is damaged. CAPEX and OPEX Using a modular approach does not reduce capital expenses, but allows them to extend over the entire life cycle of a data center, which averages ten years. At the same time, operating expenses are reduced, and the object's payback period is much shorter. It is possible to create a modular data center project that is divided into several phases, increasing its capacity as the demand for it grows. Scalability of modular solutions is excellent, and each subsequent phase of modernization most often does not affect the previous ones. This means complete independence already at the design phase, and that even deep modernization of the entire facility can be completed in phases. Forecasts Today, the global data center construction industry is witnessing a trend towards the so-called hyperscale. Global technology companies are building big data centers that can handle dozens or even hundreds of megawatts of load. For the most part, these projects are implemented by search engines, cloud solution providers, and large social networks such as Microsoft, Amazon, Google, or Facebook. In Russia, as far as we know, Yandex is attempting this. Specific modular solutions are already actively used in the engineering infrastructure of such data centers. Analysts have different views on the growth prospects of the hyperscale segment; some of them forecast growth of up to 40% per year. Given the emerging trend of moving information systems to the cloud, even this assessment does not look overly optimistic. Modular solutions are also increasingly used when it comes to smaller projects. Today, this is a significant trend in the data center design and construction industry, which drives leading equipment manufacturers to regularly expand their lines of smart manufacturing solutions.

09/21/2018The Pros and Cons of Lithium-Ion Batteries for Data Centers

Valve-Regulated Lead-Acid (VRLA) batteries are commonly used in three-phase sources of uninterruptible power supplies. Due to their weight and dimensions, they require that data centers have reinforced bearing structures. The performance characteristics of VRLA batteries also depend on the temperature, which increases the load on air conditioning systems. VRLA batteries are not particularly durable and need to be replaced on a regular basis, which also leads to increased operating costs. Since there are no economically viable alternatives to VRLA batteries, design engineers have had to put up with their shortcomings. But, the situation has changed in recent years for lithium-ion batteries. Up until now, it was not viable to use them in the uninterruptible power supply systems of data centers since there was no reasonable balance between price, energy, capacity, safety, and reliability. Thanks to advancements in electric vehicles, this problem has been solved. The first uninterruptible power supply systems powered by lithium-ion batteries hit the market in 2016. Now, they are offered by all of the leading players, and today this direction is considered the most promising. According to Bloomberg New Energy Finance report, by 2025, lithium-ion solutions will account for 40% of the market for UPSs used in data center. The Pros of Lithium-Ion Batteries Consumer electronics companies typically use lithium-ion cobalt batteries which feature capacities of several Ampere hours. These uninterruptible power supply systems come with rectangular lithium manganese cells. Their installed capacity is 60 Ampere hours, and they feature much longer service life and multiple degrees of failure protection. Individual modules and, sometimes, even individual cells are responsible for monitoring key performance parameters such as temperature, voltage, and current. Sometimes, power cabinets and even the entire system can be responsible for such a monitoring process. Monitoring is necessary to get full control over charging and discharging processes to prevent critical heating and irreversible chemical processes from occurring. Lithium-ion batteries also have a higher energy density (Wh/kg) and higher output power density (W/kg). With similar energy storage capacity, they weigh about three times less than lead acid batteries, which helps reduce the total mass of the system by about 60-80%. In recent years, data centers have aimed to increase their power density given their limitations on space and the need for more-efficient operations. More efficient use of available space is one of the most relevant tasks of data center owners. Compact lithium-ion batteries reduce the area occupied by a uninterrupted power supply system by 50-80%. Such batteries require less time for charging and feature a better self-discharge rate, which plays a major role in the event of frequent outages. When sitting idle, a lithium-ion battery loses about 1-2% of its charge per month. The most important advantage is its long service life. Lead acid batteries have a pretty short life cycle, from 3 to 6 years. Lithium-ion batteries, on the other hand, should last for about 10 years. Depending on chemistry, technology, and temperature, they can feature charging efficiency of up to 5,000 life cycles and are maintenance-free, while the average charging efficiency for lead acid batteries is only 700 life cycles. Total cost of ownership for a period of 10 years (average lifespan of UPS for data centers) decreased by 39% compared to lead acid batteries. Although it is an optimistic estimate, at least 10% of savings are guaranteed. There is only one serious flaw with lithium-ion batteries—the initial investment is significantly higher. That is why large data centers have been pioneers when it comes to the introduction of new solutions. It is much more important for such facilities to reduce TCO than to get any short-term benefits, and even a small percentage of monetary savings is enormous in this case. In addition, compact batteries allow for more efficient use of the available space, while reliable monitoring systems ensure better safety and stable performance. Lithium-ion batteries can operate at higher temperatures than VRLA without losing capacity, which reduces the load on cooling systems. Of course, there are even one-phase UPSs equipped with lithium-ion batteries. There are models for a variety of applications, starting with the largest data centers, industrial applications and ending with small server rooms and even individual racks. Expediency of Replacement The most important question that every end customer asks themselves eventually is: Is now the right time to upgrade our uninterrupted power supply system to lithium-ion batteries? To answer this question, the first thing to consider is the availability of technical capacity. New batteries are not available for all UPS models and significant hardware and embedded software upgrades may be required. Even at the same nominal voltage, the characteristics of battery charging and discharging will differ. The life expectancy of a typical UPS system in a data center is usually 10-15 years. Lead acid batteries work for 3-6 years whereas lithium-ion batteries last 10 years or even longer. At the beginning of the service life of a UPS system (less than 5 years old), replacing a significant portion of lead acid batteries will prove useful. However, when it comes to lithium-ion batteries they are most likely to last right up to the day when the UPS system gives out. If service life of your uninterrupted power supply system is nearing its middle point, battery service life may be longer, and in most cases it makes no sense to replace them. At the end of its service life, consideration should be given to replacing your entire UPS system with a new lithium-ion battery solution. However, even for an old UPS system, installing expensive batteries may be expedient. You should take into account the constant decline in their price, as well as the ratio of maintenance costs of the old system and the cost of its full replacement. Forecasts and Prospects Although UPS systems powered by lithium-ion batteries substantially reduce operating costs and the total cost of ownership, a large proportion of customers still use VRLA-time-tested solutions. This can be explained first of all by the fact that using lithium-ion batteries is only advantageous for a long-term perspective. However, it does significantly increase capital costs. In any case, customer interest in innovation is growing year after year and will only continue growing. For large data centers, the volume of savings can be enormous, so lithium-ion-powered systems will be increasingly used in the corporate sector. Lithium-ion chemistry keeps advancing too. New solutions and technologies will emerge over time, and the price of lithium-ion batteries will drop even further. ▼ An example of battery configurations in a data center : VRLA vs. Li-ion Batteries

09/20/2018The IoT is pushing data centers to the edge

Article writer: Mikael Berggren, Director of Business Development, Data Center Solutions, ICTBG, Delta Electronics (Netherlands) Off in the distance, the IT world has spotted a looming iceberg of data. The rapid growth of connected devices we call the Internet of Things (IoT) has set us on a collision course. It's time for evasive action, and the edge may be our best chance to steer clear of an impending data overload. Today alone, the world will generate an additional 2.5 exabytes of data. That's a lot, but it's nothing compared to where we're headed. Forecasts predict that, by 2025, vehicles will transfer 10 exabytes of data to and from the cloud each month. And that's just one application among many, not to mention the ones we haven't thought up yet. So how can we avoid exposing data centers to the largely hidden iceberg of data that is the Internet of Things? Consider that connections to the cloud will not always be fast enough and the capacity to deal with IoT-scale data isn't there at the backend even if they were. It quickly becomes clear that, in the future, we'll be forced to pick and choose which data actually make it all the way to the cloud. As Helder Antunes at Cisco has remarked, “In most scenarios, the presumption that everything will be in the cloud with a strong and stable fat pipe between the cloud and the edge device – that's just not realistic.” It all started with CDNs If we are willing to expand the definition of edge computing a bit beyond the technologies currently making headlines, it's really nothing new. Content delivery networks (CDNs) such as Akamai's have been around since the 90s, for instance. A CDN is a way of distributing static content across multiple sites to get that information closer to where it is actually being used. This has proven to be a very efficient model for delivering things like streaming video. Edge computing builds on that approach. But instead of the individual nodes near the edge of the network merely storing and serving content, they also receive and process data. After the advent of cloud computing, the existence of such intelligent nodes between users and the cloud data center was an important advance. This mashup has made possible a scenario in which we can now combine the heightened data protection and lower latency of on-premise solutions with the flexibility and accessibility of the cloud. What's changed A number of new applications are placing new demands on the way we move and process data. Autonomous vehicles, smart homes, and smart manufacturing all involve connected devices that generate useful data — tons of it. But raw data from sensors alone won't help you avoid a traffic jam, perform preventive maintenance on factory equipment, or get a text message that your daughter has arrived safely home. All of these things require some type of processing, be that real-time analytics, machine learning, or some other type of artificial intelligence. Right now, most of that processing is happening in big data centers. But as the demand for computer resources balloons, this is no longer a viable model. These use cases will be generating more data and requiring faster response times than the cloud can handle. Currently, only 10% of all data are processed outside the cloud or data center. Gartner predicts that by 2022, a whopping 50% of all data will be processed somewhere else (read: on the edge). Another development that will help define the edge in the future is the ongoing transition to 5G mobile networks in many countries including the US. Carriers are deploying or actively considering adding edge micro data centers in close proximity to their new mobile 5G base stations as they upgrade networks. Lots of rough edges There are a raft of new technologies inserting themselves into the space between the device and the cloud, all of them jockeying for position. You've got Microsoft Azure's IoT Edge, AWS Greengrass, AWS Lambda, and the Akraino Edge Stack that Intel is getting involved with, just to name a few. Horizontal or vertical? Among these up-and-coming edge technologies, there are both vertical solutions that cover everything from IoT devices and edge servers all the way to the cloud, as well as horizontal approaches that aim to add edge computing functionality to a broad range of devices, such as with apps running inside containers or a hypervisor on various devices within a given infrastructure. Risks and rewards By placing storage and computing resources closer to the source of the data, both latency and the amount of cloud bandwidth required are drastically reduced. But, what about security? That's something that will vary greatly across applications. Some experts believe that by limiting the amount of data travelling across the open internet, edge computing enhances security. And for companies with sensitive data that must not leave the premises, this is a big benefit. On the other hand, the addition of countless IoT devices and a separate level of infrastructure including edge servers gives malicious entities a larger attack surface. Because each additional endpoint you add could potentially be compromised and provide a pathway to infiltrate core networks. Who will have the edge? Another issue with moving infrastructure from the cloud to the edge is the question of ownership, operation, and maintenance. Companies have taken advantage of cloud computing in part because of its potential to drastically lighten their administrative and maintenance burdens. If computing infrastructure comes back home to the edge, who will own and operate it? These questions are difficult to answer now, because there is little clarity about which technologies will prevail in the end. One thing is certain: whoever is in charge of the edge data center of the future and however large or small that facility may turn out to be, efficiency will be a crucial factor. And it's not easy to beat large data centers for computing efficiency—or reliability for that matter. I believe that, for these reasons, there is no one-stop solution that will work for every client's edge computing use case. Every edge facility will need to be customized for the respective application. But whatever the size, tomorrow's data center infrastructure—especially power and cooling—will be more important as data gets pushed to the edge.

07/09/2018The Building of a LEED-Certified Green Data Center

Rapid advances and the widespread adoption of data processing and communication technologies in recent years have led to a staggering amount of growth in IT equipment. Statistics indicate that data centers around the world now account for 3% of all global power consumption. The IDC estimates that the cost of energy consumption now amounts to 25% of the hardware costs in the IT industry. The figure is continuing to increase at a rate of 52% compounded annually. A peer-reviewed research report in 2016 found that the ICT industry will consume 20% of the global power output unless there is a significant increase in efficiency. By 2025, it will account for up to 5.5% of global carbon emissions, surpassed only by the U.S., China and India. Some industry analysts believe that by 2025, the cost of power consumed by data centers worldwide will exceed US$10 billion at today's electricity prices. Data centers consume a huge amount of power and governments are now fully aware of the need to reduce carbon emissions. It has become difficult for data centers to obtain sufficient power in some developed cities. For example, the Municipal Commission of Economy and Information Technology in Beijing has announced a ban on the construction and expansion of data centers. Energy efficiency has now become a top priority for data center development. Therefore, how do you build a truly “green and energy efficient” data center while ensuring a high level of data security and availability? A number of energy efficiency certifications for data centers have now emerged. The most representative of these is the LEED certification. LEED Green Building Rating System Leadership in Energy and Environmental Design (LEED) is a voluntary rating standard aimed at defining a complete and correct green building standard, promoting the development of green integration technologies, and providing practical technical guidelines for the construction of green buildings. LEED is currently considered the most comprehensive and influential standard among environmentally-friendly buildings, green buildings, and building sustainability rating standards available today. LEED is a performance-based standard that emphasizes the satisfaction of “Greening” requirements as a whole. It provides an environmental strategy for the design and management of buildings that reduces the emission of harmful greenhouse gases by reducing energy consumption and conserving materials. LEED embodies the logical use of resources and a holistic approach to building design. The LEED green building rating system focuses on the sustainability of a building throughout its entire life cycle including its design, construction, fine-tuning, operations and demolition. The total engagement and cooperation of developers, architects, structural engineers, mechanical-electrical engineers, lighting designers, landscapers, builders, and supervisory units are essential. LEED Certification Rating Components The LEED rating system and its technical framework are composed of five key aspects and various indicators. Environmental impact is assessed on the basis of the Integrative Process (2 points), Location and Transportation (18 points), Water Efficiency (12 points), Energy and Atmosphere (38 points), Materials and Resources (13 points), Indoor Environmental Quality (17 points), Innovation & Design Process (6 points), and Regional Priority (4 points). An overall score is assigned to each indicator. There are four possible certification levels, and a rating of platinum (≧80 points), gold (≧60 points), silver (≧50 points) or bronze (≧40 points) as shown in Fig. 1 is issued to reflect the level of greenness. ▲ Levels of LEED Certification Key Elements of a LEED Data Center As described above, a green data center's LEED rating can be considered a general assessment of the entire life cycle rather than looking only at the PUE. The LEED rating system contains the following key elements: Optimizing energy efficiency Maximize the energy efficiency of the data center and its systems to reduce the environmental and economic hazards posed by excessive energy consumption. Energy simulation software can be used to compare energy consumption throughout the year against the baseline values defined in ASHRAE 90.1 and to analyze the energy-saving measures. The potential energy-savings and impact on costs of all affected systems can be forecasted and a score calculated based on the percentage of energy savings. A report from the U.S. Department of Energy indicated that data centers consume 100 times more energy than a standard office. Real-world measures found in addition to the power consumed by IT equipment, air-conditioning and UPS accounted for 97.8% of power usage by non-IT equipment. Improving the efficiency of air-conditioning and UPS is therefore just as important as improving the efficiency of IT equipment. Energy management Measuring devices must be permanently installed and be able to collect data automatically. It must allow for remote access by users via web browsers. The energy consumption statistics must be sorted and analyzed through the energy management system to help users understand their energy consumption habits and identify wasted energy. The system also conducts energy efficiency monitoring with hourly, daily, monthly and annual management reports. The data must be retained for at least 18 months to provide a basis for continuous improvements to energy efficiency. Renewable energy Renewable energy systems can be used to reduce the energy costs of the project. The score is then calculated based on the percentage of energy consumption met from renewable sources. Environmentally-friendly products The use of environmentally-friendly refrigerants, the use of products with sustainability reports, and local products reduces the amount of environmental damage from carbon and GHG emissions during manufacturing and transportation. In other words, it is essential to reduce carbon emissions to a minimum. ▲ Environmentally-friendly refrigerant Construction management Non-hazardous construction and demolished building materials need to be recovered/and or re-used during the construction process to minimize the amount of waste produced. The air quality of the construction environment must be maintained, the techniques for working with volatile materials reviewed and management of the material inventory practiced. Commissioning Performance verification is a requirement for green data center applications. The ASHRAE Guidelines define commissioning as “a quality-oriented process for achieving, verifying, and documenting that the performance of facilities, systems and assemblies meets defined objectives and criteria.” The execution of the commissioning process involves the owner, design unit, and construction unit working together. The planning phase, design phase, construction phase, system performance testing upon completion of construction and operations maintenance management must all adhere to the Owner's Project Requirements (OPR) and Basic of Design. Commissioning can improve the energy efficiency of the data center. Operations & management Once personnel and equipment have taken over the site, a Data Center Infrastructure Management (DCIM) system with visualization support should assist the managers with the continuous monitoring of energy efficiency so that the actual operational performance can be compared against the original design requirements. The manager also gains a picture of operator habits to identify opportunities to reduce the waste energy and continue to calibrate/optimize the system. ▲ Illustration of the DCIM system with visualization support World's First LEED V4 Certified Non-Monolithic Data Center In March 2018, Delta's Wujiang Data Center became the first non-monolithic data center in the world to achieve the LEED v4 ID+C gold certification. Planning, design and construction were based on the B+ Chinese national standards and LEED green data center. In addition to the introduction of energy-efficiency solutions, a facial recognition system was also installed due to operational security requirements for personnel management. ▲ Delta's Wujiang data center Optimization of energy efficiency is the key for green data centers The Ministry of Industry and Information Technology (MIIT) in China also called for all new large cloud computing data centers constructed from 2015 onwards to achieve a power usage effectiveness (PUE) rating of less than 1.5. The Delta Wujiang data center's PUE for the year of 2017 was 1.29 and was 41% higher than required by the MIIT. Methods used include: ● Separation of cold/hot aisles The separation of cold and hot aisles is probably the simplest and most effective energy-saving measure as shown in Fig. 6. Separating the cold and hot areas greatly reduces the mixing of cold and hot air. It eliminates the vertical temperature gradient at the front of the rack that increases the temperature of IT equipment inlets, reduces cooling efficiency and results in IT equipment crashing due to overheating. At the same time, gradually increasing the temperature of the cold aisle through empirical testing can help reduce the amount of power consumed by air-conditioning. However, if the temperature exceeds 25℃ this may increase the power consumption of IT equipment instead and increase the likelihood of crashing from over-heating. Setting the cold aisle temperature to 25℃ can therefore accomplish the goal of optimizing the power consumption of air-conditioning. ▲ Separation of cold and hot aisles ● Placing in-row air-conditioning near hot spots for effective heat removal The air flow of modular data network equipment is generally horizontal so the use of modular in-row air-conditioning adheres to the same horizontal flow path. This reduces the distance to heat sources and greatly shortens the air circulation path as shown in Fig. 7. Static pressure loss by the fan and heat loss from the aisles are reduced for more effective removal of hot spots. ● Use modular system units Master-slave control is used by the main unit to collect the temperature and humidity parameters from multiple modules. The average is then used to realize synchronized control. ▲ Air flow of in-row air-conditioning illustrated ● High-performance inverter air-conditioning equipment The IT equipment deployed in data centers often needs to be gradually added during the course of operations. Air-conditioning equipment must also be included and redundancy factored in. The use of variable-speed air-conditioning in this situation increases flexibility. For low to medium loads when multiple in-row air-conditioning units are running simultaneously, the high-efficiency EC fan can run more slowly and the compressor can also vary the frequency for flow control. By adjusting the run speed based on actual load, power attrition can be reduced (e.g. lowering wind speed by 10% reduces power consumption by 27%) to achieve high efficiency at low loads. ▲ High-performance inverter air-conditioning equipment ● Leveraging natural resources (energy-saving new wind system) Analysis of the local climate data for Wujiang found that new wind can be introduced for natural cooling for half of the years shown in Fig. 9. Taking advantage of this outstanding natural resource will greatly reduce the consumption of energy. New wind fans and ventilation fans combined with PLCs were used for natural cooling with new wind as shown in Fig. 10. The introduction of new wind is based on the outdoor temperature, relative humidity, heat value and indoor requirements. When the outdoor requirements are all lower than the set values then new wind takes over. The in-row air-conditioning system can now be switched off to minimize energy consumption. ▲ Temperature distribution in China throughout the year ▲ Illustration of energy-saving new wind system ● High-efficiency modular UPS In conventional data centers the load is around 30~40% of the UPS. The efficiency of a conventional UPS is approximately 87%. If a high-efficiency modular UPS (DPH) is used instead, then its operating efficiency can be increased to 95%, or 8% higher than the conventional method. If the load is 100kW then this translates into 70,000 kWh in energy savings a year. Modular UPSs can be scaled to the IT equipment to keep the UPS running at high-efficiency. ▲ Comparison of high-performance modular UPS (DPH) and conventional UPS efficiency ▲ High-performance modular UPS (DPH) Continued optimization of the green data center and visual DCIM system The visualization component of the visual data center infrastructure management (DCIM) system supports category, time, organization, and indicator management. The energy usage analysis report can be presented as trend, bar and pie charts to give the manager a quick picture of critical information such as IT infrastructure operations and maintenance, asset management, utility and air-conditioning management, energy management, environmental control, security surveillance, access control and space configuration. A smart data center with DCIM can automatically adjust the data center environment to keep the IT equipment running normally. ▲ DCIM system with visualization support Green electricity from solar power Solar panels with 403.2 kWp of generating capacity were installed on the roof of the project building as shown in Fig. 13. The 430,000 kW of power generated every year for the factory and data center accounts for around 4.05% of the data center's annual power usage. The Delta data center at its Americas headquarters is completely powered by renewable energy. ▲ Solar power Green O&M - Automated Fault Detection and Diagnostics and Asset Inspection If a fault at the data center occurs due to power outage or human error then detection and recovery is relatively easy. What if a fault in the data center gradually crept in during routine operations? A data center is usually fitted with many sensors, drivers and equipment such that a massive amount of data is collected. If a sensor reports every second then that means 30 million entries in a year. If there are 100 sensors then that means 3.1 billion entries in a year. The Automated Fault Detection and Diagnostics (AFDD) function in the Data Center Infrastructure Management (DCIM) system converts this data into information then analyzes the information to produce the reports needed by the manager. Diagnosing faults at a data center is like a doctor seeing a patient. Analytical rules are formulated using different indicators and past experience to identify the likely location of the fault and remind the manager to undertake preventive maintenance. The reliability of the data center is then enhanced. Another function is asset inspection. Inspection targets are created through the system and a QR code applied to the target. Scanning the QR code with a mobile phone uploads the relevant inspection records to the system for analysis. Upper management can use the system for audits as well, reducing the amount of printed records and speeding up analysis. ▲ Automatic Fault Detection and Diagnosis example ▲ Asset inspection using a mobile phone Summary Living standards are gradually improving and technology is developing at a rapid pace. Saving energy to be green is an ideal that all people are now embracing. The emergence of IoT, AI, AR/VR, cloud, mobile and big data analytics technologies has made green, energy-efficient data centers the top priority in the development of the industry. The building of energy-efficient green data centers takes a certain amount of creativity and should not be constrained by conventional thinking. For example, Foxconn's data center in Guiyang takes advantage of Mother Nature's resources. For data center managers, a good DCIM system should be an integrated platform that simplifies management through automation, visualization and early-warning using AFDD. By making management and analysis faster and convenient for managers to carry out, by finding and correcting areas of low efficiency in IT, and by reducing carbon emissions, the ultimate goal of optimizing the performance and life cycle management of the data center can be achieved.