The increasingly ubiquitous nature of computer and internet usage in our society, has driven advances in semiconductor technology, server packaging, and cluster level optimizations, in the IT industry. Not surprisingly this has an impact on our societal infrastructure with respect to providing the requisite energy to fuel these power hungry machines. Cooling has been found to contribute to about a third of the total data center energy consumption, and is the focus of this study. In this paper we develop and present physics based models to allow the prediction of the energy consumption and heat transfer phenomenon in a data center. These models allow the estimation of the microprocessor junction and server inlet air temperatures for different flow and temperature conditions at various parts of the data center cooling infrastructure. For a case study example considered, the chiller energy use was the biggest fraction of about 41% and also the most inefficient. The room air conditioning was the second largest energy component and also the second most inefficient. A sensitivity analysis of plant and chiller energy efficiency with chiller set point temperature and outdoor air conditions is also presented.
Real-time Efficient Operation of Decatizing Processes via a Geometric-based Extremum Seeking Control
