Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/AEC29DCE-6B06-440D-97C2-B8872E750DE5 | ||
| Year | 2015 | ||
| Type of Item | Diploma Work | ||
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| Bibliographic Citation | Ευγενία Διονυσοπούλου, "Ενεργειακά αποδοτικές λύσεις για ψύξη σε υπολογιστικά κέντρα (data centers)", Διπλωματική Εργασία, Σχολή Μηχανικών Περιβάλλοντος, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2015 https://doi.org/10.26233/heallink.tuc.24767 | ||
| Appears in Collections |
The rapid advancement of technology has led to the flood of the modern world with information and electronic data, which require efficient management and storage. Data management strategies are developed in data centers. The existence of these centers is crucial for most professional fields, such as computer science, industry, medicine and mobile technology.However, the uninterrupted operation of data centers is closely associated with high energy consumption, which according to surveys, accounts for 2% of global energy consumption. Simultaneously, the combustion of fossil fuels, with the purpose of meeting the energy needs in data centers, causes remarkable carbon emissions, which irreparably damage the environment. Therefore, scholars of data centers focus on finding innovative and energy-efficient solutions, relating mainly to the replacement of conventional energy sources with renewable sources.This thesis refers to finding energy efficient cooling solutions for an existing data center in Ancona, Italy. With the help of TRNSYS software, five change scenarios were tested in the primary cooling system, both separately and in combination. Specifically, in order to avoid, as was possible, the operation of traditional cooling units, three different free cooling scenarios were applied: indirect waterside freecooling, direct airside free cooling and direct waterside free cooling by using river water. Moreover, one more scenario was tested concerning an upgrade of the servers. The results of modeling were compared with each other and with the data’s center primary cooling system and led to the development of a combinatorial scenario, which was proved to be very efficient. In the context of combinatorial scenario achieved energy savings -25.1% of the total annual initial energy consumption and particularly -41.7% of the energy consumed annually for cooling. Finally, it is worth noting the reduction of CO2 emissions by 25.1%.
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