Energy Technology and Computer Science

We focus on the convergence of energy technology and computer science, particularly in artificial intelligence (AI), machine learning (ML), the Internet of Things (IoT), and cybersecurity. This approach emphasizes sustainability and environmental considerations, targeting a green transition and ensuring the high security of critical infrastructures. AI and ML optimize energy transmission, storage, and consumption, while IoT enhances integration through real-time monitoring, and cybersecurity ensures system integrity. Our research encompasses the operation, control, and maintenance planning of energy systems, the integration of renewable energy resources, and the use of power electronic converters in electricity grids. Additionally, we explore technological applications of AI, ML, IoT, and cybersecurity. We also emphasize user experience in healthcare and pedagogy in software education.

Head of Section: Mehdi Savaghebi.

Technology Implementation

We are passionate about delivering world-leading research and creating a significant impact on society, aiming to be at the forefront of university-industry collaboration within the energy technology and computer science fields. Our mission is to bring new technologies to society by emphasizing the implementation processes within cutting-edge research, world-class teaching, and continuous industrial collaboration. We concentrate on addressing the needs and challenges of implementation and operation within the industrial sector, focusing on high technology readiness levels (TRLs) in our research, and educating talented engineers to excel in energy technology and computer science.

Research Areas and Applications

  • Renewable energy integration in smart energy systems
  • Power electronics in electricity grids
  • Maintenance planning and asset management in critical infrastructures
  • AI and machine learning applications
  • IoT and embedded systems
  • Optimization and security of digital systems and communication

Collaborations

The Section’s main education and research collaborations are with SMEs and larger national and international companies in the following branches:

  • Operators of energy systems and infrastructure
  • Renewable energy industry
  • SMEs providing electrification solutions for remote and rural areas
  • Consultancy sector within energy sector
  • Providers of technologies for operation, automation, fault detection and digitalization of energy systems
  • IT, communication and electronics companies
  • Agriculture sector
  • The healthcare sector and healthcare technology providers

Disciplines

  • Energy Systems
  • Renewable Energy
  • Power Electronics
  • Control Systems
  • AI and Machine Learning
  • Cyber Security and Communications
  • Software Development

Competences

  • Control of power electronic converters in power grids and renewable energy systems
  • Operation, control, and fault detection in energy systems
  • Simulation and experimental tests of power electronics, electric machines, IoT and communication systems
  • Exploring the interplay between operations research and machine learning to address underlying data dependencies and noisy data points
  • Development of methods for time series modeling and prediction using Bayesian approaches
  • Development of software systems and frameworks that offer cybersecurity for citizens and organization
Group photo
Photo: Thomas Hjort Jensen

Partners

EUDP logo
Landbrugsstyrelsen logo
UFMA

Employees

Research staff