Model reduction for Model Predictive Control of district and communal heating systems within cooperative energy systems
File(s)Manuscript_unmarked.pdf (3.68 MB)
Accepted version
Author(s)
Lyons, Ben
O'Dwyer, Edward
Shah, Nilay
Type
Journal Article
Abstract
The benefits of applying advanced control approaches such as Model Predictive Control to the building energy domain are well understood. Furthermore, to facilitate the decarbonisation of the sector, district heating, communal heating and heat pumps are set to become more common, leading to a greater need to employ advanced approaches to enable flexible integration with the power grid whereby buildings can provide flexibility services to mitigate grid stress. The development of models that are complex enough to capture the behaviour of large numbers of buildings without introducing excessive computational effort remains a challenge. In this paper, an approach is proposed in which model reduction techniques based on Hankel Singular Value Decomposition are applied in cooperation with state-of-the-art building energy modelling tools to produce models of large numbers of buildings that remain tractable within an MPC framework. The approach is demonstrated using a case study in which a MPC is developed for a 95-flat communal heating system. Centralised and decentralised approaches are considered, particularly in their respective ability to incorporate externally imposed constraints on the supply.
Date Issued
2020-04-15
Date Acceptance
2020-02-15
Citation
Energy, 2020, 197, pp.1-10
ISSN
0360-5442
Publisher
Elsevier BV
Start Page
1
End Page
10
Journal / Book Title
Energy
Volume
197
Copyright Statement
© 2020 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
Commission of the European Communities
Engineering & Physical Science Research Council (E
Identifier
https://www.sciencedirect.com/science/article/pii/S0360544220302851?via%3Dihub
Grant Number
691895
EP/S016627/1
Subjects
Energy
0913 Mechanical Engineering
0914 Resources Engineering and Extractive Metallurgy
0915 Interdisciplinary Engineering
Publication Status
Published online
Article Number
117178
Date Publish Online
2020-02-20