Hierarchical price coordination of heat pumps in a building network controlled using model predictive control
File(s)
Author(s)
Type
Journal Article
Abstract
Decarbonisation of the building sector is driving the increased use of heat pumps. As increased electrification of the heating sector leads to stress on the electricity grid, the need for district level coordination of these heat pumps emerges. This paper proposes a novel hierarchical coordination methodology, in which a price coordinator reduces the total instantaneous power demand of a building network below a power supply limit using a price signal. Each building has a model predictive controller (MPC) which maximises thermal comfort and minimises electricity costs. An additional term in the MPC objective function penalises the heat pump power demand quadratically, which when multiplied by a pseudo electricity price allows the price coordinator to reduce the peak power demand of the building network. A 2 building network is studied to analyse the price coordinator algorithm’s behaviour and demonstrate how this approach yields a trade off between comfort, energy consumption and peak demand reduction. A 100 building network case study is then presented as a proof of concept, with the price coordinator approach yielding results similar to that of a centralised controller (less than 0.7% increase in energy consumption per building per year) and a roughly fourfold decrease in computation time.
Date Issued
2019-11-01
Date Acceptance
2019-09-05
Citation
Energy and Buildings, 2019, 202
ISSN
0378-7788
Publisher
Elsevier BV
Journal / Book Title
Energy and Buildings
Volume
202
Copyright Statement
© 2019 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/
Identifier
https://www.sciencedirect.com/science/article/pii/S0378778819307042?via%3Dihub
Subjects
09 Engineering
12 Built Environment and Design
Building & Construction
Publication Status
Published online
Article Number
109421
Date Publish Online
2019-09-18