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About us Faculty of Behavioural and Social Sciences Psychology Research Units Social Psychology

Efficient demand and supply matching by incentivizing end-users in buildings - MatchIT

Social Psychology

Smart grids promise a formation of a reliable electricity infrastructure that can meet demand with a high security of supply under possibly varying and affordable prices. While the energy is generated in a distributed fashion using solar panels, wind turbines and combined heat-power systems, it can be also stored, for example, using batteries. For such formation to be realized, an electricity infrastructure linking households, commercial buildings and industrial buildings needs control options and interventions that are efficient, intelligent and socially acceptable. Such options and interventions require an interdisciplinary approach that integrates multiple technological and social science disciplines. We propose an interdisciplinary framework that uses innovative control methods and intelligent automated techniques to improve the demand/supply matching that are acceptable to end-users. We develop distributed control methods that combine financial and social incentives with the physics of the electricity infrastructure in an optimal way. Within the electricity infrastructure, we focus on buildings where sensors collect indoor information. We realize intelligent techniques that use that information and automatically coordinate the use of HVAC and appliances in accordance to the infrastructure situation (congestion, energy pric

Researchers and partners

Behavioural and Social Sciences, Psychology
University of Groningen, outside of Behavioural and Socials Sciences
Partners outside of the University of Groningen
  • Carlo Fischione - KTH Royal Institute of Technology (Stockholm, Sweden)

Education

Selection of BA and MA student projects
  • Values, incentives, technology
  • Values, incentives, technology

University's focus areas

  • Energy
  • Sustainable Society

More information

Last modified:29 March 2021 10.17 a.m.
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