Imperial College London
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Dr Salvador Acha

Faculty of Engineering, Department of Chemical Engineering

Senior Research Fellow
 
 
 
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Contact

 

+44 (0)20 7594 3379salvador.acha Website CV

 
 
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Location

 

453AACE ExtensionSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Gonzato:2019:10.1016/j.enbuild.2019.109421,
author = {Gonzato, S and Chimento, J and ODwyer, E and Bustos-Turu, G and Acha, S and Shah, N},
doi = {10.1016/j.enbuild.2019.109421},
journal = {Energy and Buildings},
title = {Hierarchical price coordination of heat pumps in a building network controlled using model predictive control},
url = {http://dx.doi.org/10.1016/j.enbuild.2019.109421},
volume = {202},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Gonzato,S
AU  - Chimento,J
AU  - ODwyer,E
AU  - Bustos-Turu,G
AU  - Acha,S
AU  - Shah,N
DO  - 10.1016/j.enbuild.2019.109421
PY  - 2019///
SN  - 0378-7788
TI  - Hierarchical price coordination of heat pumps in a building network controlled using model predictive control
T2  - Energy and Buildings
UR  - http://dx.doi.org/10.1016/j.enbuild.2019.109421
UR  - https://www.sciencedirect.com/science/article/pii/S0378778819307042?via%3Dihub
UR  - http://hdl.handle.net/10044/1/73707
VL  - 202
ER  -
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