Modelling and control of cooling systems for data center applications

Nowadays, the Data Center industry is playing a leading role in the world economic development and it is growing rapidly and constantly. Beside this, it has become more concerned with energy consumption and the associated environmental effects. Since about half of the total energy consumption in a typical Data Center is devoted to cooling the IT equipment, energy efficiency must be the primary focus in the design and management of the cooling infrastructure. In this Thesis, we consider the problem of optimizing the operation of cooling systems in Data Centers. The main objective is that of maximizing the energy efficiency of the systems, while provisioning the required cooling demand. For this purpose, we propose a two-layer hierarchical control approach, where a supervisory high-level layer determines the optimal set-points for the local low-level controllers. The supervisory layer exploits an Extremum Seeking model-free optimization algorithm, which ensures flexibility and robustness against changes in the operating conditions. In particular, a Newton-like Phasor-based Extremum Seeking scheme is presented to improve the convergence properties and the robustness of the algorithm. The proposed control architecture is tested in silico in optimizing the operation of an Indirect Evaporative Cooling system and a Liquid Immersion Cooling unit. Simulations are performed by exploiting First-Principle Data-Driven models of the considered systems and the results demonstrate the effectiveness of the proposed approach.