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A platform for research: civil engineering, architecture and urbanism
Investigating the impact of energy efficiency on the urban-scale energy flexibility potential of single-family houses
In recent years, a significant number of studies have indicated the potential benefits of leveraging the thermal mass in buildings to generate flexible energy demand through demand response schemes. However, differences in energy-efficiency and storage capacity across buildings give rise to the question of whether neighborhoods populated with different building typologies are equally capable of leveraging flexible consumption to reduce peaks during daily operation as well as to lower the capacity requirements that apply to initial sizing of DH components and networks. In this study, we use hourly smart meter data from a real district heating system and Bayesian inference to calibrate physics-based models of the district heating demand of single-family houses (i.e. space heating and domestic hot water) to investigate the flexibility potential of neighborhoods composed of different building typologies. Using coordinated optimization to determine the heating strategy in the residential buildings, we document that flexible heating consumption of the involved buildings can reduce the needed DH capacity between 13% and 17.1% over a fiveyear period depending on which group of buildings that are activated. Newer (i.e. more energy-efficient) buildings were capable of realizing larger peak reductions while also being the most efficient in doing so. It thus seems favorable to target the most energy-efficient buildings in a DH system first when implementing DR schemes.
Investigating the impact of energy efficiency on the urban-scale energy flexibility potential of single-family houses
In recent years, a significant number of studies have indicated the potential benefits of leveraging the thermal mass in buildings to generate flexible energy demand through demand response schemes. However, differences in energy-efficiency and storage capacity across buildings give rise to the question of whether neighborhoods populated with different building typologies are equally capable of leveraging flexible consumption to reduce peaks during daily operation as well as to lower the capacity requirements that apply to initial sizing of DH components and networks. In this study, we use hourly smart meter data from a real district heating system and Bayesian inference to calibrate physics-based models of the district heating demand of single-family houses (i.e. space heating and domestic hot water) to investigate the flexibility potential of neighborhoods composed of different building typologies. Using coordinated optimization to determine the heating strategy in the residential buildings, we document that flexible heating consumption of the involved buildings can reduce the needed DH capacity between 13% and 17.1% over a fiveyear period depending on which group of buildings that are activated. Newer (i.e. more energy-efficient) buildings were capable of realizing larger peak reductions while also being the most efficient in doing so. It thus seems favorable to target the most energy-efficient buildings in a DH system first when implementing DR schemes.
Investigating the impact of energy efficiency on the urban-scale energy flexibility potential of single-family houses
Hedegaard, Rasmus Elbæk (author) / Kristensen, Martin Heine (author) / Petersen, Steffen (author)
2020-11-01
Hedegaard , R E , Kristensen , M H & Petersen , S 2020 , ' Investigating the impact of energy efficiency on the urban-scale energy flexibility potential of single-family houses ' , Paper presented at uSIM2020 , Edinburgh , United Kingdom , 12/11/2020 - 12/11/2020 . < https://39e38bfc8bfe017f9f2d17df1-16003.sites.k-hosting.co.uk//uSIM2020//Papers/Session%20A3/2.%20Hedegaard.pdf >
Conference paper
Electronic Resource
English
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