E3S Web Conf.
Volume 312, 202176th Italian National Congress ATI (ATI 2021)
|Number of page(s)||12|
|Section||Smart Energy Systems|
|Published online||22 October 2021|
Demand response strategies in residential buildings clusters to limit HVAC peak demand
1 Università Politecnica delle Marche, Dipartimento di Ingegneria Industriale e Scienze Matematiche, Via Brecce Bianche 12, 60131, Ancona, Italy
2 Consiglio Nazionale delle Ricerche, Istituto per le Tecnologie della Costruzione, Viale Lombardia 49, 20098, San Giuliano Milanese (MI), Italy
3 KU Leuven, Department of Mechanical Engineering, B-3000, Leuven, Belgium
* Corresponding author: firstname.lastname@example.org
Due to the increasing spread of residential heating systems electrically powered, buildings show a great potential in producing demand side management strategies addressing their thermal loads. Indeed, exploiting the intrinsic characteristics of the heating/cooling systems (i.e. the thermal inertia level), buildings could represent an interesting solution to reduce the electricity peak demand and to optimize the balance between demand and supply. The objective of this paper is to analyse the potential benefits that can be obtained if the electricity demand derived from the heating systems of a building cluster is managed with demand response strategies. A simulation-based analysis is presented in which a cluster of residential archetypal buildings are investigated. The buildings differ from each other for construction features and type of heating system (e.g. underfloor heating or with fan coil units). By supposing to be able to activate the energy flexibility of the single building with thermostatic load control, an optimized logic is implemented to produce programmatically an hourly electricity peak reduction. Results show how the involvement of buildings with different characteristics depends on the compromise that wants to be achieved in terms of minimization of both the rebound effects and the variation of the internal temperature setpoint.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.