Cloudberry consists of 12 subprojects


1. Datacenter's interaction with the national energy system
This is a multidisciplinary project where various aspects of data centers interaction with the surrounding energy system, both as a consumer and producer, are studied with regard to possible data center development options. The focus is both on the connection with the energy system and on developing an impact assessment of potential data center development opportunities.

The project will identify different ways of data center integration with the surrounding energy system as well as to identify possible development options for data centers in different scales by utilizing national energy system optimization model TIMES-Sweden.

PhD student Simin Hajizadeh, Supervisor Anna Krook Riekkola



2. Multifunctional data centers
This is a collaboration between the architecture- and construction management and building technology groups at LTU, a data center operator and a construction company. The project aims to develop a data-driven demonstrator to evaluate the potential of integrated multifunction data centers and support design and production planning. It will assess and value the possible integrations of data centers in an urban environment in order to support local community activities through energy synergies.

The project will look at datacenters as part of an urban energy system contributing to a circular approach within an urban metabolism. It will also measure the value of reusing waste-heat to achieve a win-win situation between the energy suppliers, datacenters and waste heat users.

PhD student Cristina Ramos Cáceres, Supervisors: Marcus Sandberg, Adolfo Sotoca



3. Quality and credibility when simulating cooling in data centers
The purpose of the project is to increase energy efficiency in data centers through the development of advanced simulation models and experimental tools. The goal is to develop reliable tools that can be used to optimise and control the cooling of data centers at different levels, from components and subsystems to entire data centers. The produced tools will be used for simulation driven development of cooling methods as well as overall design optimisation. 

The project will look at quality and reliability of numerical modeling and experimental measurement and determine the
exergetic losses and quality of the cooling airflow. It will also do situational modeling, transient behavior and CRAC failure analysis and look at ways to asses the fluid flow situation.

PhD student Henrik Barestrand, Supervisors Staffan Lundström, Anna-Lena Ljung, Jon Summers



4. Transient simulations of data center dynamic thermal management arrangements
The project aims to develop a simulation tool to capture the dynamics of thermofluidics for the cooling of large-scale distributed IT systems, commonly found in modern data centers. A validated, quick, simulation tool will be able to analyse the benefits of different layouts at data centers and heat dissipation methods in case of alternating loads as well as disturbances and errors. 

The project will use the Lattice Boltzmann Method (LBM) to simulate thermal conditions in a data center, utilize multiple Graphics Processing Units (GPUs) for large simulations and validate different LB methods and CFD models with sensor data from data center. It will also implement ability to use LBM as a training and testing system for air conditioning control systems.

PhD student Johannes Sjölund, Supervisor Jon Summers



5. Evaluation of energy recovery solutions for data centers
A major problem with data centers is that the residual heat generated during the cooling process is rarely used because it often has low temperature and a large volume flow.

In this project, possible heat recovery methods will be evaluated in detail where the goal is to visualise which methods and techniques are possible to use as well as whether they are energy efficient enough to become profitable. Another important aspect to study is how these affect the operation of data centers, as well as the ability to take advantage of all residual heat.

PhD student Hampus Ljungkvist, Supervisor Mikael Risberg



6. Design of distribution networks for energy efficient data center operations
This project aims to review the design of the internal grid within a data center with respect to energy efficiency and reliability. Different distribution network solutions will be studied. New knowledge about opportunities and limitations with energy efficiency of studied options will be developed, as well as existing and expected levels of interference in the data center tension. 

Project 6.A
This sub-project will look at components of data center, loss analysis of components, result analysis, create mathematical models as well as to look at rack power, server fans and total power consumed.

PhD student Kazi Main Uddin Ahmed, Supervisors Math Bollen, Sarah Rönnberg


Project 6.B
This sub-project will evaluate potential reliability issues with different types of internal grid configurations, study power quality phenomena within an AC and DC grid, study harmonic propagation within an AC and DC grid, including different types of grounding as well as to study the power quality impact on LV and MV grids from data centers.

PhD
student Jil Sutaria, Supervisors Sarah Rönnberg, Math Bollen



7. The impact of data centers on the electricity market with an increased share of renewable electricity generation
The project will look at techno-economical grounds and incentives for participation in markets providing capacity and flexibility.
It will evaluate potential instruments and financial incentives, study markets for system services and network services linked to energy intensive industry, study balancing power and operational reserves as well as deployment of mega datacenters and similar energy intense industries in Sweden and their integration with the electricity market. The project will also study potential economical incentives how an increased number of mega datacenters and other energy intense industries can contribute to an increased share of renewable production.

PhD student Manuel Alvarez, Supervisors Math Bollen, Sarah Rönnberg



8. SimBerry - Flexible and large-scale simulation of interaction between district heating
and remote cooling networks and data centers

The purpose of the project is to develop methods and tools to dynamically create digital twins of complete district heating and remote cooling networks with recovery of waste heat from data centers. The work is based on previous results where a unique digital twin for a district heating system using an automated model generation method has been created.  

The project wil use Simulink as a co-simulation platform, automatic control simulation and logging of signals, forming the test bed for simulation. The goal is to improve flexibility and study how a large-scale digital twin can be made dynamic with respect to functionality and validation facilities.

PhD student Johan Simonsson, Supervisors Wolfgang Birk, Khalid Atta



9. Proximity liquid cooling inside data centers for direct heat recovery 
The project focuses on theoretical and experimental analysis of liquid-cooled IT systems for direct heat recovery. The aim of the subproject is to develop a one-dimensional theoretical flow and heat exchange model that captures both energy and exergy losses when transferred into thermally charged refrigerants. Another goal is to experimentally validate the theoretical model against a true heat transfer system.

The project will look at direct heat recovery from data centers using proximity liquid cooling without any requirement to upgrade the heat.

PhD student Sebastian Fredriksson, Supervisors Wolfgang Birk, Jon Summers, Khalid Atta



10. Automated maintenance of energy-efficient data centers
Maintenance costs represent a large proportion of total operating costs in large industrial plants such as data centers. Large-scale data centers employ large personnel groups to perform maintenance tasks such as, for example, to replace broken servers and components. The goal of the project is to investigate appropriate methods for intelligent and automated server room maintenance systems and measure the impact on data center energy efficiency.

The project will look at predictive maintenance design to help determine the conditions of in-service equipment in order to estimate when maintenance should be performed.

PhD student Yulia Berezovskaya, Supervisor Chen-Wei Yang



11. Resource efficiency in software processes and communication in data clouds
and data centers

THe project will address energy consumption early in the chain by studying and increasing the efficiency of software. A goal for the project is to bring containers to an additional level of resource efficiency in the context of data centers and distributed devices in society. 

The project will study a general software architecture that provides resource-efficient methods for virtualisation of software processes and communication between them in a distributed environment.

PhD student Lara Lorna Jiménez, Supervisor Olov Schelén



12. Resource efficiency in distributed ledgers and smart contracts
The project will study the distributed distribution area and smart contracts, often including so-called blockchains and hash graphs. These solutions often consume large amounts of energy. The plan is to study resource efficiency in such systems, to define requirements and solutions, to evaluate options, and to define balance between requirements and energy costs.

PhD student Ahmed Afif Monrat, Supervisor Olov Schelen, Karl Andersson