A probabilistic model for characterising heat pump electrical demand versus temperature

Amy Anderson; Bruce Stephen; Rory Telford; Stephen McArthur

doi:10.1109/ISGT-Europe47291.2020.9248942

A probabilistic model for characterising heat pump electrical demand versus temperature

Amy Anderson, Bruce Stephen, Rory Telford, Stephen McArthur

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

5 Citations (Scopus)

63 Downloads (Pure)

Abstract

The introduction of electric heat pumps as an alternative to gas based systems for space heating offers a potential pathway for reducing the carbon emissions produced to meet domestic heating demand in the UK. The adoption of heat pumps has the potential to significantly re-shape typical domestic load profiles, however uptake within the UK is currently limited and the effects of wide-scale adoption on distribution networks is not well understood. Heat pump demand is highly sensitive to temperature, lessening load profile diversity, but is also influenced by behavioral routine and is therefore not entirely deterministic. This study develops a probabilistic demand model from real customer heat pump data for translating electrical heat pump demand/air temperature relations to account for regional variation. A LV network heat pump penetration study is performed to demonstrate how residential network impact can be assessed using the model.

Original language	English
Title of host publication	2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	1030-1034
Number of pages	5
ISBN (Print)	9781728171005
DOIs	https://doi.org/10.1109/ISGT-Europe47291.2020.9248942
Publication status	Published - 10 Nov 2020
Event	2020 IEEE PES Innovative Smart Grid Technologies Europe - The Hague, Netherlands Duration: 26 Oct 2020 → 28 Oct 2020 https://ieee-isgt-europe.org/

Conference

Conference	2020 IEEE PES Innovative Smart Grid Technologies Europe
Abbreviated title	ISGT Europe 2020
Country/Territory	Netherlands
City	The Hague
Period	26/10/20 → 28/10/20
Internet address	https://ieee-isgt-europe.org/

Keywords

heat pumps
low carbon technologies
load modelling
uncertainty

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10.1109/ISGT-Europe47291.2020.9248942

Anderson-etal-ISGT2020-A-probabilistic-model-for-characterising-heat-pump-electrical-demandAccepted author manuscript, 679 KB

Cite this

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title = "A probabilistic model for characterising heat pump electrical demand versus temperature",

abstract = "The introduction of electric heat pumps as an alternative to gas based systems for space heating offers a potential pathway for reducing the carbon emissions produced to meet domestic heating demand in the UK. The adoption of heat pumps has the potential to significantly re-shape typical domestic load profiles, however uptake within the UK is currently limited and the effects of wide-scale adoption on distribution networks is not well understood. Heat pump demand is highly sensitive to temperature, lessening load profile diversity, but is also influenced by behavioral routine and is therefore not entirely deterministic. This study develops a probabilistic demand model from real customer heat pump data for translating electrical heat pump demand/air temperature relations to account for regional variation. A LV network heat pump penetration study is performed to demonstrate how residential network impact can be assessed using the model.",

keywords = "heat pumps, low carbon technologies, load modelling, uncertainty",

author = "Amy Anderson and Bruce Stephen and Rory Telford and Stephen McArthur",

note = "{\textcopyright} 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. ; 2020 IEEE PES Innovative Smart Grid Technologies Europe, ISGT Europe 2020 ; Conference date: 26-10-2020 Through 28-10-2020",

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month = nov,

day = "10",

doi = "10.1109/ISGT-Europe47291.2020.9248942",

language = "English",

isbn = "9781728171005",

pages = "1030--1034",

booktitle = "2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)",

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Anderson, A , Stephen, B, Telford, R & McArthur, S 2020, A probabilistic model for characterising heat pump electrical demand versus temperature. in 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe). IEEE, Piscataway, NJ, pp. 1030-1034, 2020 IEEE PES Innovative Smart Grid Technologies Europe, The Hague, Netherlands, 26/10/20. https://doi.org/10.1109/ISGT-Europe47291.2020.9248942

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T1 - A probabilistic model for characterising heat pump electrical demand versus temperature

AU - Anderson, Amy

AU - Stephen, Bruce

AU - Telford, Rory

AU - McArthur, Stephen

N1 - © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

PY - 2020/11/10

Y1 - 2020/11/10

N2 - The introduction of electric heat pumps as an alternative to gas based systems for space heating offers a potential pathway for reducing the carbon emissions produced to meet domestic heating demand in the UK. The adoption of heat pumps has the potential to significantly re-shape typical domestic load profiles, however uptake within the UK is currently limited and the effects of wide-scale adoption on distribution networks is not well understood. Heat pump demand is highly sensitive to temperature, lessening load profile diversity, but is also influenced by behavioral routine and is therefore not entirely deterministic. This study develops a probabilistic demand model from real customer heat pump data for translating electrical heat pump demand/air temperature relations to account for regional variation. A LV network heat pump penetration study is performed to demonstrate how residential network impact can be assessed using the model.

AB - The introduction of electric heat pumps as an alternative to gas based systems for space heating offers a potential pathway for reducing the carbon emissions produced to meet domestic heating demand in the UK. The adoption of heat pumps has the potential to significantly re-shape typical domestic load profiles, however uptake within the UK is currently limited and the effects of wide-scale adoption on distribution networks is not well understood. Heat pump demand is highly sensitive to temperature, lessening load profile diversity, but is also influenced by behavioral routine and is therefore not entirely deterministic. This study develops a probabilistic demand model from real customer heat pump data for translating electrical heat pump demand/air temperature relations to account for regional variation. A LV network heat pump penetration study is performed to demonstrate how residential network impact can be assessed using the model.

KW - heat pumps

KW - low carbon technologies

KW - load modelling

KW - uncertainty

U2 - 10.1109/ISGT-Europe47291.2020.9248942

DO - 10.1109/ISGT-Europe47291.2020.9248942

M3 - Conference contribution book

SN - 9781728171005

SP - 1030

EP - 1034

BT - 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

PB - IEEE

CY - Piscataway, NJ

T2 - 2020 IEEE PES Innovative Smart Grid Technologies Europe

Y2 - 26 October 2020 through 28 October 2020

ER -

A probabilistic model for characterising heat pump electrical demand versus temperature

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