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Home   /   Post Doctorat   /   Distributed multiagent resources allocation. Application to district heating

Distributed multiagent resources allocation. Application to district heating

Computer science and software Engineering sciences Mathematics - Numerical analysis - Simulation

Abstract

Heating district networks in France fed more than one million homes and deliver a quantity of heat equal to about 5% of the heat consumed by the residential and tertiary sector. Therefore, they represent a significant potential for the massive introduction of renewable and recovery energy. However, heating networks are complex systems that must manage large numbers of consumers and producers of energy, and that are distributed in extended and highly branched geographical zones. The aim of the SIGMA project, realized in collaboration among the CEA-LIST and the CEA-LITEN, is to implement an optimal and dynamic management of heating networks. We propose a multidisciplinary approach, by integrating the advanced network management using Multi-Agent Systems (MAS), by taking into account spatial constraints using Geographic Information Systems (GIS) and by considering simplified physical models of transport and recovery of heat.
The post-doc’s goal is to design mechanisms for dynamically allocating resources that consider the geographical information from the GIS and the predictions of consumption, production and losses calculated with the physical models. In this way, several characteristics of the network will be considered: the continuous and dynamic aspect of the resource; sources with different behaviors, capabilities and production costs; the dependence of consumption / production to external aspects (weather, energy price); the internal characteristics of the network (losses, storage capacity). The coupling with a GIS should allow implementing self-configuration mechanisms for the management of different networks and different levels of granularity obtained by reduction of the original GIS. The MAS should dynamically establish the link between the suitable simplified models and the desired level of granularity and then it will create the agents needed to represent the system.

Laboratory

Département Métrologie Instrumentation et Information (LIST)
Laboratoire Informations Modèles et Apprentissage
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