The SunSTONE project aims to develop a tool for the smart control of district heating networks (DH). This new tool should be particularly relevant in the frame work of high solar fraction DH with seasonal thermal storage. Compared to existing work on the subject, SunSTONE innovates at physical modeling level, particularly by promoting exergo-economic approach multi-zone management of borehole thermal energy storage, and at stochastic modeling level by proposing Bayesian Networks for demand prediction and Influence Diagram for decision making. To achieve the development of a relevant tool, various interactions between academics and industrial partners are planned: data collection and analysis, definition of decision making criteria, tool validation and comparison.
