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AI and smart energy systems

AI and machine learning techniques offer reliable solutions to transform data into valuable knowledge that can be applied in various stages of the life cycle to improve performance, reduce costs and pollutions.

Publisert: Endret:

Ongoing research on applied AI and machine learning in the field of smart energy systems:

  • Automated data filtering approach
  • Smart calibration of multi-hole measurement probes
  • Modeling and optimum operation of energy systems
  • Condition based monitoring and fault diagnostics
  • Digital twin for energy systems

Staff and researchers

Condition monitoring and fault diagnostics for distributed energy systems

Other ongoing relevant projects:

  • Advanced Gas and Carbon Dioxide Storage in Aquifer (AGaStor)
  • Innovation in Underground Thermal Energy Storages with Borehole Heat Exchangers (BHEsINNO)
  • Next generation micro gas turbines (NextMGT)
  • Energy System in Transition (ENSYSTRA)

Advanced Gas and Carbon Dioxide Storage in Aquifer (AGaStor)

Other ongoing relevant projects:

  • Condition monitoring and fault diagnostics for distributed energy systems
  • Innovation in Underground Thermal Energy Storages with Borehole Heat Exchangers (BHEsINNO)
  • Next generation micro gas turbines (NextMGT)
  • Energy System in Transition (ENSYSTRA)

Innovation in Underground Thermal Energy Storages with Borehole Heat Exchangers (BHEsINNO)

Other ongoing relevant projects:

  • Condition monitoring and fault diagnostics for distributed energy systems
  • Advanced Gas and Carbon Dioxide Storage in Aquifer (AGaStor)
  • Next generation micro gas turbines (NextMGT)
  • Energy System in Transition (ENSYSTRA)

Next generation micro gas turbines (NextMGT)

Other ongoing relevant projects:

  • Condition monitoring and fault diagnostics for distributed energy systems
  • Advanced Gas and Carbon Dioxide Storage in Aquifer (AGaStor)
  • Innovation in Underground Thermal Energy Storages with Borehole Heat Exchangers (BHEsINNO)
  • Energy System in Transition (ENSYSTRA)

Energy System in Transition (ENSYSTRA)

Green transition and sustainable development is all about using resources smarter and more efficiently. The researchers in the ENSYSTRA project seek to accelerate the transition to enable a more integrated mix of renewable energy.

The slow-moving development towards sustainable energy systems is not due to lack of technological solutions. It is rather economic, political and social factors that are to blame. Providing solutions that help the transition to move forward, requires close collaboration between engineers and social scientists. Only then can we avoid solutions that work technically but are not economically viable or socially acceptable.

Six UiS researchers participate in a research collaboration between six European universities and numbers of industry partners to educate highly qualified energy experts with the aim to provide Europe with more environmentally friendly energy systems. The goal is to find the most successful solution for developing a society with almost one hundred percent renewable energy. Energy and emission intensity of different pathways will be explored with the help of techno-economic and mathematical models. The findings will help in designing a more efficient and resilient energy system for the future.

The objective of this ENSYSTRA project is to identify the different pathways in which decarbonisation of the integrated energy system can be achieved.