Data-driven green building modelling, energy management & building cluster federation
Integration of a large number of distributed energy resources (DERs), such as distributed wind and PVs systems as well as the increasing electrification of the heating and transport sector poses great challenges on distribution and transmission network operation. In this situation, local energy systems (LESs) and green buildings open up new possibilities to utilize local, renewable energy sources in a decentralized way as well as to provide operational support. However, their role and potential in urban areas are, yet, underdeveloped. Here, a major challenge is how to integrate the thousands of controllable elements in LESs and green buildings into traditional control or optimization frameworks while still guaranteeing optimal system-level objectives. In line with this, we aim to develop a new data-driven operational paradigm for LESs from cyber-physical-societal perspectives, with a special focus on DERs integration, LESs and green building flexibility exploring, and actor integration. The project comprises six Work Packages. TUDelft-BK is involved in WP3 (Data-driven green building modelling and energy management). The main tasks within this WP include data-driven modelling of green building, physics-integrated machine learning for building energy management, federation and coordination of building cluster energy information and design of energy saving scheme based on field lab validation.
|This research received funding from the Dutch Research Council (NWO) and National Natural Science Foundation of China (NSFC) in the framework of the Cooperation China-The Netherlands programme
Contribution to TU Delft: € 290.328
|Role TU Delft:
|September 2022 - September 2026
|TU Delft researchers:
TU Delft (EWI), The Hague University of Applied Science, PEPITe S.A, Geodan, Tsinghua University, Zhejiang Universit, Jibei Power Exchange Center Ltd. Co., Alliander