OREANDA-NEWS. Fujitsu Laboratories Ltd. today announced the development of highly accurate predictive technology for such metrics as temperature and humidity, enabling energy-saving operations of air-conditioning equipment in data centers.

With the aim of preventing global warming, there is a demand for energy-saving in data centers, particularly with air-conditioning equipment, which can account for between 30% and 50% of total electricity use. Now, to flexibly respond to the dynamic status changes that are issues unique to data centers, such as moving information equipment in and out and changing rack arrangements, Fujitsu Laboratories has developed a highly accurate prediction technology that sequentially builds a model that predicts air-conditioning effects from collected data, enabling reductions in air conditioner energy use.

With this technology, Fujitsu Laboratories has enabled reductions in data center electricity consumption, contributing to global warming prevention.

Details of this technology will be announced at the European Control Conference (ECC) 2016, an international conference which will be held June 29th in Aalborg, Denmark.

Currently, data center energy consumption is increasing along with growth in the data center market, and reports state that data center energy consumption accounts for 1-2% of all electricity use. Further increases in data center energy use are expected with the growth of IoT systems going forward. Reducing data center energy use may also be an important element in global warming prevention.

In order to reduce data center energy use, it is both important and effective to reduce the energy consumed by air-conditioning equipment, which accounts for between 30% and 50% of a data center's total energy use. Existing data center air-conditioning equipment operates on the basis of information from a variety of installed sensors so as to maintain the target temperature and humidity even when the operating rate of the ICT equipment it contains, such as servers, increases. When sensor data exceeds a set value, the system carries out rapid cooling for safety reasons, which causes air-conditioning to operate excessively.

In contrast, by using a method called model-based control (Figure 1), which is used in blast furnaces, automobiles, and robotics to predict future values, reductions in air-conditioning energy consumption in line with less excessive operations can be expected. However, the devices installed in the data center, such as information devices and air-conditioning equipment, as well as their layout, can change frequently (Figure 2). This means that the model, once built, will diverge from reality over time, reducing prediction accuracy and making it difficult to use in data centers.