Development and analysis of hourly DHW heat use profiles in nursing homes in Norway

Ivanko, Dmytro; Walnum, Harald Taxt; Nord, Nataša

doi:10.1016/j.enbuild.2020.110070

“…To consider appropriate bounds on the power consumption, the maximum load shifted at time t is limited using (18) and (19). The maximum load shifted varies with time dependent on the reference load.…”

Section: Load Shiftingmentioning

confidence: 99%

Demand flexibility modelling for long term optimal distribution grid planning

Bødal¹,

Lakshmanan²,

Sperstad³

et al. 2022

Preprint

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<p>Optimization tools for long-term grid planning considering flexibility resources require aggregated flexibility models that are not too computationally demanding or complex. Still, they should capture the operational benefits of flexibility sufficiently accurately for planning purposes. This paper investigates the sufficiency of an aggregated flexibility model for planning tools by comparing it against a detailed flexibility model. Two different constraint formulations, namely based on recovery period and temporal proximity were tested to account for post activation dynamics of flexibility resources. The results show that the recovery period based formulation results in excessive demand reduction. The proximity constraint formulation on the other hand results in realistic activation of flexibility resources which represents an improvement over the base formulation without constraints for post activation dynamics.</p>

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“…EWH consumption data was collected from multiple single family houses in Norway for a duration of 285 days from March 2016 to February 2017 [18]. Data analysis of the smart meter data reveals that typical temperature hysteresis is 5 • C. The EWH has a lower temperature threshold T min of 70 • C to avoid the growth of legionella [19], and an upper threshold T max which is 75 • C. The typical value of thermal capacitance of the hot water tank is found to be 0.335 kWh/ • C. The average demand profile for 24 hours for a single family house is as shown in Fig. 1.…”

Section: Ewh Flexibilitymentioning

confidence: 99%

Demand flexibility modelling for long term optimal distribution grid planning

Bødal¹,

Lakshmanan²,

Sperstad³

et al. 2022

Preprint

0

View full text Add to dashboard Cite

<p>Optimization tools for long-term grid planning considering flexibility resources require aggregated flexibility models that are not too computationally demanding or complex. Still, they should capture the operational benefits of flexibility sufficiently accurately for planning purposes. This paper investigates the sufficiency of an aggregated flexibility model for planning tools by comparing it against a detailed flexibility model. Two different constraint formulations, namely based on recovery period and temporal proximity were tested to account for post activation dynamics of flexibility resources. The results show that the recovery period based formulation results in excessive demand reduction. The proximity constraint formulation on the other hand results in realistic activation of flexibility resources which represents an improvement over the base formulation without constraints for post activation dynamics.</p>

show abstract

“…Data analysis of the smart meter data reveals that typical temperature hysteresis is 5°C. The EWH has a lower temperature threshold T

^{min}

of 70°C to avoid the growth of Legionella [24], and an upper threshold T

^{max}

which is 75°C. The typical value of thermal capacitance of the hot water tank is found to be 0.335 kWh/°C.…”

Section: Modelling Of Flexibility Resourcesmentioning

confidence: 99%

Demand flexibility modelling for long term optimal distribution grid planning

Bødal

¹

,

Lakshmanan

²

,

Sperstad

³

et al. 2022

IET Generation Trans & Dist

7

0

View full text Add to dashboard Cite

Optimisation tools for long-term grid planning considering flexibility resources require aggregated flexibility models that are not too computationally demanding or complex. Still, they should capture the operational benefits of flexibility sufficiently accurately for planning purposes. This article investigates the sufficiency of an aggregated flexibility model for planning tools by comparing it against a detailed flexibility model. Two different constraint formulations, namely based on recovery period and temporal proximity, were tested to account for post activation dynamics of flexibility resources. The results show that the recovery period based formulation results in excessive demand reduction. The proximity constraint formulation on the other hand results in realistic activation of flexibility resources, which represents an improvement over the base formulation without constraints for post activation dynamics. The results show how a too simple model of the operational behaviour of demand flexibility may overestimate its benefits as an alternative or supplement to grid investments.

show abstract

Development and analysis of hourly DHW heat use profiles in nursing homes in Norway

Cited by 19 publications

References 23 publications

Demand flexibility modelling for long term optimal distribution grid planning

Demand flexibility modelling for long term optimal distribution grid planning

Demand flexibility modelling for long term optimal distribution grid planning

Demand flexibility modelling for long term optimal distribution grid planning

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