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An Economical and Sustainable Optimized Data Center Design
Alzarooni, Abdalla Waheeb
Alzarooni, Abdalla Waheeb
Date
2025-11
Author
Advisor
Type
Thesis
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35.232-2025.41a Abdalla Waheeb Alzarooni.pdf
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Description
A Master of Science thesis in Engineering Systems Management by Abdalla Waheeb Alzarooni entitled, “An Economical and Sustainable Optimized Data Center Design”, submitted in November 2025. Thesis advisor is Dr. Noha Hussein. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form)
Abstract
Data centers are major electricity consumers, and their impact is magnified in hot climates where cooling demand is high. In the United Arab Emirates, rapid expansion of digital infrastructure combined with persistent high temperatures and a national target of net-zero emissions by 2050 intensifies the need for energy systems that reduce both energy cost and indirect CO₂ emissions. Addressing this challenge requires configurations that lower grid dependence and enhance renewable energy integration under realistic regional conditions. This research evaluates and optimizes a grid connected, solar assisted energy configuration for medium to large UAE data centers. The objective is to quantify how photovoltaic (PV) deployment, panel technology, and IT load conditions influence techno-economic performance and carbon emission reduction. Two detailed MATLAB Simulink models were developed, one for the combined grid–PV electrical supply and another for the water cooled chiller plant serving an average 6000 kW IT load. A structured Minitab based experimental framework was then implemented. Average IT load between 2000 to 6000 kW, and PV capacity between 10000 to 20000 panels were treated as continuous factors, while PV technology such as, crystalline silicon, CIS, CdTe and seasonal months of January, May, October were included as categorical factors. Results show that PV capacity, panel type, and seasonal solar availability dominate system behavior, whereas IT load dictates the cost and emission trade-off. Increasing PV deployment from 10000 to 20000 panels nearly doubles monthly solar generation and lowers total cost, with crystalline silicon delivering the highest yield. Carbon emission savings range from around 1.0×10³ to over 7.0×10³ tCO₂, peaking in May for large crystalline silicon installations. Optimization indicates that 2000 kW with 20000 panels in May is optimal for minimizing
cost and maximizing excess power, whereas 6000 kW with 20000 panels in May is preferred when prioritizing emission reduction. This work provides a quantitative framework for designing solar assisted data centers and supports national sustainability objectives by identifying practical pathways to reduce grid dependency and carbon footprint.