Lieu de la soutenance : Chambre ED109, Faculté d’Automatique et Science de l’Ordinateur, Université Politehnica de Bucarest, Bucarest, Roumanie – disponible à visioconférence.
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Les membres du jury :
- Stéphane PLOIX, Directeur de thèse, Professeur, Grenoble INP-UGA, Grenoble, France
- Sergiu Stelian ILIESCU, Co-Directeur de thèse, Professeur, Université Politehnica de Bucarest, Bucarest, Romania
- Ioana FAGARASAN, Co-encadrante, Professeur, Université Politehnica de Bucarest, Bucarest, Romania
- Christian GHIAUS, Rapporteur, Professeur, INSA Lyon, Lyon, France
- Stéphane Grieu, Rapporteur, Professeur, Université de Perpignan, Perpignan
- Frédéric WURTZ, Examinateur, Directeur de Recherche CNRS, G2Elab, Grenoble, France
- Romain BOURDAIS , Examinateur, Professeur, CentraleSupélec, Rennes, France
- Florin POP , Examinateur, Professeur, Université Politehnica de Bucarest, Bucharest, Romania
- Julie DUGDALE, Invitée, Professeur, Laboratoire LIG, UGA, Grenoble, France
Abstract :
This research study explores control strategies for energy systems, giving due consideration to human involvement and personal preferences, dissatisfaction, and motivation. The aim is to create a paradigm shift from traditional approaches where control strategies often overlook the behaviour of people. As an alternative, this study introduces the actor-service-system paradigm, a novel approach for designing innovative energy systems that significantly incorporate human actors.
The proposed solution, applied in the context of energy communities, refers to a recommendation system acting as a service that facilitates the interaction between people
acting as community members and the pure technical system consuming or producing energy. Several proposed service implementations demonstrate how optimization problems may be shaped to provide solutions that maximize system performance and minimize user dissatisfaction when adhering to recommendations. Since in energy communities people
voluntarily join to share energy and foster environmental benefits, the recommendation system capitalises on the potential psychological, motivational and social aspects that may be involved in such an organisation. Subsequently, several interaction and behaviour models are proposed, along with associated recom- mendation strategies developed on optimisation principles. The idea is to demonstrate how stochastic models or Hidden Markov models may represent suitable solutions for describing how people react to recommendations in their daily energy consumption behaviour, while interaction models implemented as multi-agent systems represent a way of organising the community around the recommendation system. Altogether, these elements harmonise human effort and comfort to achieve various objectives set by the community in terms of energy performance.
The effectiveness of the proposed methods is demonstrated through several case studies. These studies show concrete examples of the recommendation system’s impact on contrasting communities and highlighting the actor-service-system paradigm common role. The recommendation system embodies the core idea of future control techniques, positioning the service as a decision-aiding assistant and emphasising the psychological significance of recommendations in enhancing performance or fostering long-term sustainable behaviours.
