Monthly domestic hot water profiles for energy calculation in Finnish apartment buildings

Ahmed, Kaiser; Pylsy, Petri; Kurnitski, Jarek

doi:10.1016/j.enbuild.2015.03.051

Cited by 71 publications

(54 citation statements)

References 15 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 Watersupporting

confidence: 72%

“…According to the Canadian Mortgage and Housing Corporation [9], Canadian seniors' buildings consume less than 44% of the DHW comparing to the standard family apartment buildings. In another study the author noted that the presence of children caused a higher consumption rate of DHW [5]. Foekema and Engelsma [10] found that there is also a relationship between the frequency of use and duration of a shower and the age and size of households in Dutch residential building.…”

Section: Modeling the Consumption Of Hot Watermentioning

confidence: 99%

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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 Watersupporting

confidence: 72%

Section: Modeling the Consumption Of Hot Watermentioning

confidence: 99%

Domestic hot water consumption in multi-apartment buildings

2017

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“…George et al conducted a high‐resolution measurement in 119 houses in Canada and found a +6.8% variation of hot water consumption in cold periods and a −0.96% variation in warm periods. Ahmed et al conducted onsite data measurements in 185 apartments in Finland and found a +15.3% variation in cold periods and −17.4% in warm periods …”

Section: Methodsmentioning

confidence: 99%

“…Ahmed et al conducted onsite data measurements in 185 apartments in Finland and found a +15.3% variation in cold periods and −17.4% in warm periods. 28 The increase in hot water consumption in cold months is mainly due to the increase in hot water consumption per shower. 29 This point is also supported by the data collected in this study.…”

Section: T a B L E 1 General Information Of Each Occupantmentioning

confidence: 99%

Predictive control based on occupant behavior prediction for domestic hot water system using data mining algorithm

Cao

Hou

et al. 2019

Energy Science & Engineering

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Domestic hot water systems are a primary source of energy consumption in buildings, and present a promising future in terms of energy saving. Predictive control methods have been used to reduce energy consumption during an operation period. However, current methods lack consideration of occupant behavior, which significantly influences the prediction results. In this study, a data‐based predictive method is proposed to predict the shower behavior of occupants. A dataset was collected from seven occupants and was trained using support vector machine (SVM) to learn their showering habits. These results were used to predict the hot water demand. A comparative analysis shows that, in this way, the prediction results are more reliable under predictive control than predicting the hot water demand directly using SVM. A simulation of a domestic hot water system was then conducted. The results indicate that the proposed approach can reduce the heat loss from a hot water storage tank (ST) by up to 33% compared to a traditional control method, while maintaining a high assurance of the hot water supply (an insufficient hot water supply of less than 1%) with little change to the original system.

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“…• C and the drawing per person is 43 L/d [93]. Moreover, domestic hot water profiles exhibit significant peaks in the morning and in the evening due to occupant behavior [94].…”

Section: Demandmentioning

confidence: 99%

Sustainable Residential Energy Supply: A Literature Review-Based Morphological Analysis

Arens¹,

Schlüters²,

Hanke³

et al. 2020

Energies

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The decarbonization of the energy system will bring substantial changes, from supranational regions to residential sites. This review investigates sustainable energy supply, applying a multi-sectoral approach from a residential site perspective, especially with focus on identifying crucial, plausible factors and their influence on the operation of the system. The traditionally separated mobility, heat, and electricity sectors are examined in more detail with regard to their decarbonization approaches. For every sector, available technologies, demand, and future perspectives are described. Furthermore, the benefits of cross-sectoral integration and technology coupling are examined, besides challenges to the electricity grid due to upcoming technologies, such as electric vehicles and heat pumps. Measures such as transport mode shift and improving building insulation can reduce the demand in their respective sector, although their impact remains uncertain. Moreover, flexibility measures such as Power to X or vehicle to grid couple the electricity sector to other sectors such as the mobility and heat sectors. Based on these findings, a morphological analysis is conducted. A morphological box is presented to summarize the major characteristics of the future residential energy system and investigate mutually incompatible pairs of factors. Lastly, the scenario space is further analyzed in terms of annual energy demand for a district.

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Monthly domestic hot water profiles for energy calculation in Finnish apartment buildings

Cited by 71 publications

References 15 publications

Domestic hot water consumption in multi-apartment buildings

Domestic hot water consumption in multi-apartment buildings

Predictive control based on occupant behavior prediction for domestic hot water system using data mining algorithm

Sustainable Residential Energy Supply: A Literature Review-Based Morphological Analysis

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