Fill out this form to register your intent to complete this project.
Fill out this form to submit your solution to this project and qualify for the rewards.
 | Improve performance, stability, and cost effectiveness of data centers by designing a cooling algorithm that keeps the system running as efficiently as possible. |
Data centers are growing at an amazing rate. They enable cloud computing and accessing incredible resources from anywhere across the globe. At their core, data centers house many power-hungry computers. Maintaining these computers at ideal temperatures allows them to perform at peak capacity and minimizes downtime. Cooling data centers requires large amounts of energy. Cooling too aggressively can increase costs and the carbon footprint of data centers, while under cooling can force systems offline or damage expensive equipment. Intelligently cooling data centers given an understanding of the heat loads and cooling dynamics can help provide the highest uptime with the lowest carbon footprint.
Work with Simscape™ Fluids™ to create a plant and controller for a data center cooling system with dynamic loads using MATLAB® and Simulink®. The model should be detailed enough to capture important dynamics. Dynamic loads include outside environmental conditions and server loads. The heat generated should vary with load and temperature. The cooling system should have a level of fidelity that includes performance under various operating conditions. A baseline thermostatic controller should be developed, and this should be improved with predictive or more intelligent control. Demonstrate that the advanced control system can keep temperature in the desired range. Demonstrate whether the control can allow for a greater performance envelope for the data center. Compute the difference in carbon footprint of using a baseline vs. advanced controller.
Suggested steps:
- Perform a literature search to understand data center loads and cooling systems.
- Create a dynamic data center cooling model.
- Model different loads that the data center can experience such as times of increased load or high external temperatures.
- Create a baseline by implementing a simple controller.
- Create a predictive controller using information such as expected load and external temperature.
- Demonstrate the value of your controller in keeping the data center temperature controlled and compare the carbon footprint of the cooling system with different controllers.
Advanced project work:
Extend the work to predict component failures with different controllers and optimal placement of critical loads within the data center.
- Simscape Fluids documentation
- Ebrahimi, Khosrow, Gerard F. Jones, and Amy S. Fleischer. "A review of data center cooling technology, operating conditions and the corresponding low-grade waste heat recovery opportunities." Renewable and Sustainable Energy Reviews 31 (2014): 622-638.
- Moazamigoodarzi, Hosein, et al. "Influence of cooling architecture on data center power consumption." Energy 183 (2019): 525-535.
- A. Mousavi, V. Vyatkin, Y. Berezovskaya and X. Zhang, "Towards energy smart data centers: Simulation of server room cooling system," 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA), Luxembourg, Luxembourg, 2015, pp. 1-6, doi: 10.1109/ETFA.2015.7301573.
Contribute to the performance, reliability, and efficiency of data centers worldwide.
Big Data, Sustainability and Renewable Energy, Cloud Computing, Control, Deep Learning, Modeling and Simulation, Parallel Computing, Predictive Maintenance
Bachelor, Master's
Dedicated discussion forum to ask/answer questions, comment, or share your ideas for solutions for this project.
196
