Issue |
E3S Web Conf.
Volume 362, 2022
BuildSim Nordic 2022
|
|
---|---|---|
Article Number | 12003 | |
Number of page(s) | 6 | |
Section | Buildings and Flexibility | |
DOI | https://doi.org/10.1051/e3sconf/202236212003 | |
Published online | 01 December 2022 |
Integrating Thermal-Electric Flexibility in Smart Buildings using Grey-Box modelling in a MILP tool
1 SINTEF Community, Oslo, Norway
2 Norwegian University of Science and Technology (NTNU), Trondheim, Norway
In a smart grid setting, building managers are encouraged to adapt their energy operations to real-time market and weather conditions. However, most literature assume stationary temperature set points for heating and cooling. In this work, we propose a grey-box model to investigate how the energy flexibility of the thermal mass of the building may impact its energy flexibility potential as well as the investment decisions of the energy system within a building, by using an already developed investment decision tool, BUILDing’s OPTimal operation and energy design model (BUILDopt) (Lindberg et al. (2016)). As BUILDopt is a Mixed Integer Programming (MIP/MILP) tool, the flexibility models must be linear as well. We evaluate the energy flexibility potential, here called comfort flexibility, for use cases reflecting different heating systems (electric panel ovens vs. ground source heat pump) and operation (flexible vs. non-flexible). The case study of an Office building is performed, which considers electric specific demand, domestic hot water demand and space heating demand. Real historical data for weather and energy prices from Oslo are used, including grid tariffs related energy and monthly peak power. Most of the savings are obtained through peak load reduction, which can reach up to 13-16%. These and the savings from shifting demand away from peak prices lead to total savings of around 2%. Yet, these actions do not require additional investment in heat supply or storage components, nor in building renovations: only system measurement and control components are needed.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.