Exploring the impacts of consumer reaction to dynamic heat prices in district heating

• Nine consumer reaction types and five demand response scenarios are studied. • Automated controllers save up to 46% of heat costs by responding to dynamic price. • Manually complying with dynamic price saves up to 41% in costs with no upfront cost. • Dynamic price can solve demand and supply mismatch issues and reduce heat costs. • More consumers who comply with prices lead to more flexibility and lower heat costs. Dynamic price is considered a key demand response (DR) strategy that could be essential in solving demand and supply mismatch issues in the energy sector. As a dominant heating solution in northern Europe, district heating has a huge potential to support large-scale demand response. While the end-user consumption fee is currently flat for most district heating systems, a dynamic heat price can reflect the heat network’s production costs and carbon emission intensity, encouraging consumers to change their heat demand behavior. Still, the transition to dynamic price has not happened, mainly due to unknown impacts on consumers and operators. This study aims to reveal the impacts of dynamic heat prices on households with different reaction types and unveils potential savings compared to flat prices. We model a neighborhood consisting of consumers with no reaction, manual reaction, and automatic reaction to price. We then characterize the relationship between price and heat demand for different scenarios. It is shown that frequent thermostat adjustments are required to comply with prices, which can be overwhelming for consumers. Accordingly, occupants who only reduce their thermostat setting during expensive hours could reduce their heat costs by 34%. Automatic controllers can resolve this and can be designed to seamlessly react to price changes and save up to 46% of the heat costs. The study suggests that dynamic pricing can be leveraged to motivate consumers for load shifting, leading to decreased heating costs and decarbonization.

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Institutions

Publication Details

Journal
Energy and Buildings
Published
2025-08-22
DOI
https://doi.org/10.1016/j.enbuild.2025.116347
Citations
1
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.73

Funders

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article

Exploring the impacts of consumer reaction to dynamic heat prices in district heating

Reza Mokhtari, Henrik Madsen, Rongling Li
1 citations
Energy and Buildings
Integrated Energy Systems Optimization
0.73
article

Exploring the impacts of consumer reaction to dynamic heat prices in district heating

Reza Mokhtari, Henrik Madsen, Rongling Li
article en
1 citations

Abstract

• Nine consumer reaction types and five demand response scenarios are studied. • Automated controllers save up to 46% of heat costs by responding to dynamic price. • Manually complying with dynamic price saves up to 41% in costs with no upfront cost. • Dynamic price can solve demand and supply mismatch issues and reduce heat costs. • More consumers who comply with prices lead to more flexibility and lower heat costs. Dynamic price is considered a key demand response (DR) strategy that could be essential in solving demand and supply mismatch issues in the energy sector. As a dominant heating solution in northern Europe, district heating has a huge potential to support large-scale demand response. While the end-user consumption fee is currently flat for most district heating systems, a dynamic heat price can reflect the heat network’s production costs and carbon emission intensity, encouraging consumers to change their heat demand behavior. Still, the transition to dynamic price has not happened, mainly due to unknown impacts on consumers and operators. This study aims to reveal the impacts of dynamic heat prices on households with different reaction types and unveils potential savings compared to flat prices. We model a neighborhood consisting of consumers with no reaction, manual reaction, and automatic reaction to price. We then characterize the relationship between price and heat demand for different scenarios. It is shown that frequent thermostat adjustments are required to comply with prices, which can be overwhelming for consumers. Accordingly, occupants who only reduce their thermostat setting during expensive hours could reduce their heat costs by 34%. Automatic controllers can resolve this and can be designed to seamlessly react to price changes and save up to 46% of the heat costs. The study suggests that dynamic pricing can be leveraged to motivate consumers for load shifting, leading to decreased heating costs and decarbonization.

Energy and BuildingsVol. 347
Technical University of Denmark (DK)
European Commission, Energistyrelsen, Energiteknologisk udviklings- og demonstrationsprogram, H2020 European Research Council
Affordable and clean energy
Openalex Percentile: Top 24%
Integrated Energy Systems Optimization
0.73
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