modelling and control of a free cooling system for data centers

Abstract Data centers are facilities hosting a large number of servers dedicated to data storage and management. In recent years, their power consumption has increased significantly due to the power density of the IT equipment. In particular, cooling represents approximately one third of the total electricity consumption, therefore efficiently cooling data centers has become a challenging problem and it represents an opportunity to reduce both IT energy costs and emissions environmental impact. The efficiency of computers room air conditioning (CRAC) systems can be increased using both advanced control techniques and new free cooling technologies, such as the indirect adiabatic cooling (IAC), that is the humidification of air under adiabatic conditions. Water sprinkled by spray nozzles humidifies and cools down the air taken from the outside, which then cools down the computers room air by means of a crossflow heat exchanger. In this way, the process air temperature is economically reduced and the cooling process is effective even when the outside temperature is warmer than that desired in the computers room. Beside the traditional approach, that improves energy efficiency of CRAC systems through advanced hardware design, nowadays advanced control systems offer the opportunity to improve both efficiency and performance by mostly acting on software components. In particular, a model-based paradigm can result very useful in the design of the controller. This approach involves three main steps: plant modelling, controller design, and simulations. In this paper, First-Principle Data-Driven (FPDD) techniques have been considered in the modelling phase, in order to obtain a model as simple as possible but accurate enough. All the main components of the plant, such as fans, spray nozzles, heat exchanger, and the computers room have been taken into account and they have been calibrated exploiting real data. The dynamics of the computers room variables (e.g. temperature) are slower than those of the components of the cooling system, due to higher thermal inertias of the computers room. Therefore, fans, heat exchanger, and spray nozzles are described by static models, whereas the computers room is described by a LTI dynamic model. Once obtained a model of the plant, a simulation environment based on Matlab/Simulink is designed accordingly. The developed control system is hierarchical: a supervisor determines the best combination of CRAC water and process air flows which minimizes the total power consumption, while satisfying the cooling demand. This system energy management problem is formulated as a non-linear optimization problem, subject to internal air condition requirements and system operating constraints. The optimization problem is repeatedly solved at each supervision period by using a population based stochastic optimization technique (Particle Swarm Optimization). Results of simulations show that the proposed control system is effective and minimizes the input electric power while satisfying both the data center thermal load and system operating constraints

Progettazione e simulazione di un sistema di "cruise control" in ambiente Matlab/Simulink

In questo elaborato viene analizzato e simulato un sistema di Cruise control in ambiente Matlab e Simulink. Dopo una prima fase di modellizzazione matematica del problema, viene condotta una analisi dinamica del sistema in catena aperta ed in catena chiusa e vengono progettati controllori con diversi approcci (PID, luogo delle radici, analisi in frequenza) con lo scopo di migliorare il comportamento dinamico del sistema e soddisfare le specifiche di progetto assegnat

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

Modelling and Control of Cooling Systems for Data Center Applications

Al giorno d'oggi, l'industria dei Data Center ricopre un ruolo fondamentale nello sviluppo dell'economia mondiale e sta crescendo in maniera rapida e costante. Peraltro, la crescente sensibilit\ue0 verso tematiche di risparmio energetico, dei cambiamenti climatici, e di sviluppo sostenibile, coinvolge anche le nuove politiche industriali. Ad esempio, se si tiene conto che circa la met\ue0 dell\u2019energia tipicamente consumata in un Data Center viene utilizzata per il raffreddamento delle apparecchiature informatiche, l\u2019efficienza energetica deve essere considerata l\u2019obiettivo primario nelle fasi di progettazione e di gestione dell\u2019infrastruttura di raffreddamento. In questa Tesi, si considera il problema di ottimizzare il funzionamento dei sistemi di raffreddamento nei Data Center. L\u2019obiettivo principale \ue8 quello di massimizzare l\u2019efficienza energetica di tali sistemi, fornendo al contempo la capacit\ue0 frigorifera necessaria a raffreddare le apparecchiature e i server. Specificatamente, viene proposto un approccio di controllo gerarchico basato su due livelli, in cui un supervisore determina i set-point ottimali per i controllori locali di basso livello. Il livello di supervisione sfrutta un algoritmo di ottimizzazione Extremum Seeking non basato su modello, che garantisce flessibilit\ue0 e robustezza al variare delle condizioni operative. In particolare, viene presentato uno schema Newton-like Phasor-based che permette di migliorare la convergenza e la robustezza dell'algoritmo. Le prestazioni dell\u2019architettura sono state verificate in silico per ottimizzare il funzionamento di un sistema di raffreddamento evaporativo indiretto e di un'unit\ue0 di raffreddamento a immersione in liquido. Le simulazioni vengono eseguite sfruttando modelli First-Principle Data-Driven dei sistemi considerati e i risultati confermano l'efficacia dell'approccio proposto