Development of Standardized Domestic Hot Water Event Schedules for Residential Buildings

Hendron, Robert; Burch, Jay

doi:10.1115/es2007-36104

Cited by 50 publications

(38 citation statements)

References 4 publications

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“…Evarts and Swan [4] found higher DHW consumption in households of three people or less. The authors of the publication also noted higher unit consumption of hot water in homes with fewer residents, which is confirmed by the analysis Ahmed, Pylsy and Kurnitski [5], Merrigan [6], Georg, Pearre and Swan [7] and Hendron & Burch [8]. The authors found a linear relationship between the water consumption and the number of occupants.…”

Section: Modeling the Consumption Of Hot Watermentioning

confidence: 56%

Domestic hot water consumption in multi-apartment buildings

2017

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Abstract.The article presents the analysis of the hot water consumption in apartment buildings. This study was conducted basing on the data gathered from 626 apartments during two following years. By statistical analysis of the collected data, the correlation between the DHW consumption and both the size of the apartments and the number of occupants in the dwellings was evaluated. The dependencies between the hot water consumption and these two parameters were calculated. The results were compared to the data available in the literature. The article lists the areas of the greatest inaccuracies in the calculations basing on the available indicators and proposes an alternative method that corrects them. The results were used to develop a calculation model for daily hot water usage in multi-apartment buildings.

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Section: Modeling the Consumption Of Hot Watermentioning

confidence: 56%

Domestic hot water consumption in multi-apartment buildings

2017

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“…Also concerning occupants' modelling, it should be mentioned the tool created by NREL laboratory to create domestic hot water use in dwellings [42]. This has not been included in this work as it has been seen in previous works that domestic hot water use may not have a substantial impact in the overall heating energy demand [43], but the tool may be of great use when calculating global energy use in dwellings.…”

Section: Environmental Parameters For Building Energy Assessment Occmentioning

confidence: 98%

New optimisation methodology to uncover robust low energy designs that accounts for occupant behaviour or other unknowns

Ramallo-González

Blight

Coley

2015

Journal of Building Engineering

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a b s t r a c tThe use of software to aid in the design of buildings or to show compliance is now commonplace. This has led several authors to investigate the potential for using such software to automatically optimise a design, or to generate a variety of near-optimal designs. One area where this approach has been found useful is in minimising annual energy demand. It is known that any estimate of demand will depend not only on the architecture and constructions used, but on the preferences and behaviours of the occupants. This suggests which design is truly optimal will also depend on occupant behaviour. In this paper optimisation is carried out for an array of different occupant behaviours based on real records. It is found that the resultant designs are more robust in terms of predicted heating energy use and overheating than when only a single behaviour is considered. It is recommended that in future all such optimisations are made using a realistic spectrum of behaviours, and that the approach is expanded to include other elements of design that might show variance during construction, for example, U-values and air tightness. This, it is hoped, will reduce some of the risks of designing and asking people to occupy very low energy buildings. Importantly, it is found that the near-optimal building designs found under variable occupancy present different characteristics than when only a single statement of occupancy is used. Being cognisant of this reduces the potential for inappropriate designs to be created that rely on a serendipitous arrangement of design and occupancy parameters that might not be met on site or by the occupants.

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“…Different stochastic models for the DHW tap profile can be found in the literature (Becker and Stogsdill 1990;Jordan and Vajen 2001;Fairey and Parker 2004;Hendron and Burch 2007;Widén et al 2009). The approach within this work is based on the models of Jordan and Vajen (2001) and Widén et al (2009).…”

Section: Domestic Hot Watermentioning

confidence: 98%

Rule-based demand-side management of domestic hot water production with heat pumps in zero energy neighbourhoods

Coninck

Bætens

Sælens

et al. 2013

Journal of Building Performance Simulation

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Grid saturation has been reported in electricity distribution systems with a high penetration of photovoltaic (PV) systems. This saturation is often caused by overvoltage and results in curtailing or shutting down of the PV inverters, leading to a loss of renewable electricity generation. The presented work assesses the potential of rule-based demand-side management (DSM) applied to domestic hot water (DHW) production with heat pumps in dwellings for reducing the non-renewable energy use of the neighbourhood. The studied case consists of 33 single-family dwellings connected to a single phase distribution grid in a moderate European climate. Each dwelling is designed as a net-zero energy building by adequate design of a heat pump and PV system. A detailed dynamic simulation model is implemented by use of a cross-domain Modelica library for integrated district energy assessment. The user behaviour is obtained from a stochastic model based on Markov chains and survival analysis. Different rule-based DSM control strategies are applied to the individual dwelling's DHW systems. The results show that for balancing the PV production, active thermal energy storage in the DHW storage tanks is very promising. Even with very basic control algorithms and small storage tanks of 0.3 m 3 , curtailing losses can be reduced by 74%. This represents a net energy saving on a neighbourhood level of 3.4%.

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Development of Standardized Domestic Hot Water Event Schedules for Residential Buildings

Cited by 50 publications

References 4 publications

Domestic hot water consumption in multi-apartment buildings

Domestic hot water consumption in multi-apartment buildings

New optimisation methodology to uncover robust low energy designs that accounts for occupant behaviour or other unknowns

Rule-based demand-side management of domestic hot water production with heat pumps in zero energy neighbourhoods

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