A real-life assessment on the effect of smart appliances for shifting households’ electricity demand

Kobus, C.B.A.; Klaassen, E.A.M.; Mugge, Ruth; Schoormans, Jan

doi:10.1016/j.apenergy.2015.01.073

Cited by 117 publications

(53 citation statements)

References 33 publications

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“…Use of night tariffs to reduce energy bills had been adopted by one-third of the respondents, even though the night tariff was only 10% 0.02 €/kWh) lower than the normal tariff. This result is in line with the statement made by Kobus et al [6] that by providing a dynamic price signal, users have a monetary incentive to move their electricity consumption to off-peak hours. Although renewable energy generation accounted for only 5.8% of the Dutch energy generation in 2015 [30], 14% of the respondents declared that their electricity was generated partly) from renewable energy resources.…”

Section: Household Energy Saving Actions and Smart Technology Ownershipsupporting

confidence: 81%

“…5 ''Other" includes students and unemployed. 6 ''Other" includes a shared house or apartment and student dormitory. 7 ''Constant" means that the heating system is always turned on at a constant temperature set-point.…”

Section: Measurementioning

confidence: 99%

“…Kobus et al [6] stated that the most important factor in motivating and activating users is to provide them with a dynamic price signal. Users then have a monetary incentive to move their electricity consumption to off-peak hours.…”

Section: Introductionmentioning

confidence: 99%

“…To date, most of the studies on building energy flexibility have focused on physical characteristics of buildings and have been completed using measurements, modelling, and simulation [5][6][7][8][9][10][11][12][13]. Existing research on users has primarily been conducted in community or district scale pilot projects for demonstration smart grid technologies [14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

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Are building users prepared for energy flexible buildings?—A large-scale survey in the Netherlands

Dane

Finck

et al. 2017

Applied Energy

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h i g h l i g h t sAwareness of smart grids is the highest among respondents aged 20-29 years old. Willingness to use smart technologies and change energy behaviour are interdependent. Potential flexible building users were found to be 11% of the respondents. Building energy flexibility might play a crucial role in demand side management for integrating intermittent renewables into smart grids. The potential of building energy flexibility depends not only on the physical characteristics of a building but also on occupant behaviour in the building. Building users will have to adopt smart technologies and to change their daily energy use behaviours or routines, if energy flexibility is to be achieved. The willingness of users to make changes will determine how much demand flexibility can be achieved in buildings and whether energy flexible buildings can be realized. This will have a considerable impact on the transition to smart grids. This study is thus to assess the perception of smart grids and energy flexible buildings by building users, and their readiness for them on a large scale. We attempted to identify the key characteristics of the ideal user of flexible buildings. A questionnaire was designed and administered as an online survey in the Netherlands. The questionnaire consisted of questions about the sociodemographic characteristics of the current users, house type, household composition, current energy use behaviour, willingness to use smart technologies, and willingness to change energy use behaviour. The survey was completed by 835 respondents, of which 785 (94%) were considered to have provided a genuine response. Our analysis showed that the concept of smart grids is an unfamiliar one, as more than 60% of the respondents had never heard of smart grids. However, unfamiliarity with smart grids increased with age, and half of the respondents aged 20-29 years old were aware of the concept. Monetary incentives were identified as the biggest motivating factor for adoption of smart grid technologies. It was also found that people would be most in favour of acquiring smart dishwashers (65% of the respondents) and refrigerator/freezers (60%). Statistical analysis shows that people who are willing to use smart technologies are also willing to change their behaviour, and can thus be categorised as potentially flexible building users. Given certain assumptions, 11% of the respondents were found to be potentially flexible building users. To encourage people to be prepared for energy flexible buildings, awareness of smart grids will have to be increased, and the adoption of smart technologies may have to be promoted by providing incentives such as financial rewards. a r t i c l e i n f o

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Section: Household Energy Saving Actions and Smart Technology Ownershipsupporting

confidence: 81%

Section: Measurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Are building users prepared for energy flexible buildings?—A large-scale survey in the Netherlands

Dane

Finck

et al. 2017

Applied Energy

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“…Hence, the uncertainty about limitations of DR algorithms due to the differences in customers' real-life (power consumption) habits remains largely unresolved. To address this gap, Kobus et al [24] conducted a longitudinal study for one year over 77 Dutch households. Each household was given a smart washing machine, and an energy management system that received daily dynamic prices.…”

Section: State Of the Art In Residential Flexibility Assessmentmentioning

confidence: 99%

Modeling and analysis of residential flexibility: Timing of white good usage

et al. 2016

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Challenges that smart grids aim to address include the increasing fraction of supply by renewable energy sources, as well as plain rise of demand, e.g., by increased electrification of transportation. Part of the solution to these challenges lies in exploiting the opportunity to steer residential electricity consumption (e.g., for flattening the peak load or balancing the supply and demand in presence of the renewable energy production). To optimally exploit this opportunity, it is crucial to have insights on how flexible the residential demand is. Load flexibility is characterized by the amount of power, time of availability and duration of deferrable consumption. Residential flexibility however, is challenging to exploit due to the variation in types of customer loads and differences in appliance usage habits from one household to the other. Existing analyses of individual customer flexibility behavior in terms of timing are often based on inferences from surveys or customer load patterns (e.g., as observed through smart meter data): there is a high level of uncertainty about customer habits in offering the flexibility. Even though some of these studies rely on real world data, only few of them have quantitative data on actual flexible appliance usage, and none of them characterizes individual user behavior. In this paper, we address this gap and contribute with: (1) a new quantitative specification of flexibility, (2) two systematic methodologies for modeling individual customer behavior, (3) evaluation of the proposed models in terms of how accurately the data they generate corresponds with real world customer behavior, and (4) a basic analysis of factors influencing the flexibility behavior based on statistical tests. Experimental results for (2)-(4) are based on a unique dataset from a real-life field trial.

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Peak load characteristics of aggregated demand in a residential building in Osaka, Japan

Toosty,

Ono,

Shimoda

et al. 2023

Japan Architectural Review

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A statistical analysis of the 2‐year electricity consumption of 479 dwellings in a residential building was conducted to determine annual peak events and their contributing factors for four different aggregations of sizes 3, 10, 50, and 479. The diverse U‐shaped relationships between outdoor temperature and peak demand occurrence and the impact of the part of the week/year were identified for different aggregation sizes using generalized linear models and generalized linear mixed models. Furthermore, the contribution of each appliance on reducing the annual peak demand according to the aggregation size was clarified. The result indicates the significant demand response potential of living/dining room outlets and air conditioners, with a 15%–25% contribution to the peak demand in the interquartile range (IQR), regardless of the aggregation level. In addition, refrigerators contributed 10%–15% to the peak demand for the aggregation of sizes 10 and 479.

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A real-life assessment on the effect of smart appliances for shifting households’ electricity demand

Cited by 117 publications

References 33 publications

Are building users prepared for energy flexible buildings?—A large-scale survey in the Netherlands

Are building users prepared for energy flexible buildings?—A large-scale survey in the Netherlands

Modeling and analysis of residential flexibility: Timing of white good usage

Peak load characteristics of aggregated demand in a residential building in Osaka, Japan

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