DECENT final project presentation: AI based modeling and optimization for consumer flexibility management
In DECENT project, AI technologies, namely artificial neural networks and model-based planning and control have been utilized for modelling and optimization of buildings and associated energy systems. Five different case studies were investigated in the project ranging from office building load forecsting to automated HVAC optimization.
In this presentation Jussi Kiljander (VTT) presented the overall approach, called Energy Management Agent and elaborated the results with practical example on a selected case study. This is a presentation from the final presentation of the DECENT project. DECENT stands for DEcentralized Cross-comodity ENergy-sharing in smarT neighborhoods. More info at https://decent.future-iot.org/
DECENT is a BMWi/ Business Finland funded project that ran from 2018-2021 with the consortium TUM, fortiss, Framatome, IBDM in Germany, and VTT, Enerim, and Wirepas on the Finnish side.
Enabling cross-commodity energy sharing for a more sustainable future! High potential lays in the more and more decentralized energy production and storage in Europe. However, the emerging flexibility potential can currently not be used due to a missing technological, economical, and legal base.
DECENT targets all three aspects:
- The project develops an ICT solution for cross-commodity sharing and management of energy (electricity, heating, cooling and storage) in smart neighborhoods.
- Based on the novel infrastructure, business models will be evaluated.
- Relevant legal implications will be assessed and recommendations towards policy makers will be given.
The project follows an agile, iterative development process by setting up a virtual smart neighborhood that consists of real hardware and co-simulations distributed at the partner’s sites. The continuously tested ICT solution enables local decentralized energy trading through blockchain technology, taking into account the interests of all stakeholders. The linking of different energy resources is supported by AI and enables their optimal use across building boundaries. The evaluation of the resulting new business models leads to recommendations regarding the current legal framework.