Measurements of household electricity and domestic hot water use in dwellings and the effect of different monitoring time resolution

Bagge, Hans; Johansson, Dennis

doi:10.1016/j.energy.2011.02.037

Cited by 32 publications

(19 citation statements)

References 8 publications

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“…For example, in [146], the maximum power consumption using a 10-min time resolution is 6 times higher than a 1-h time resolution. However, it was shown in [106] that the rescheduling interval can be increased from 3 to 10 min with little consequence.…”

Section: Consequencementioning

confidence: 95%

See 1 more Smart Citation

Home energy management systems: A review of modelling and complexity

Beaudin

Zareipour

2015

Renewable and Sustainable Energy Reviews

387

206

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a b s t r a c tThe increasing demand for electricity and the emergence of smart grids have presented new opportunities for home energy management systems (HEMS) in demand response markets. HEMS are demand response tools that shift and curtail demand to improve the energy consumption and production profile of a dwelling on behalf of a consumer. HEMS usually create optimal consumption and production schedules by considering multiple objectives such as energy costs, environmental concerns, load profiles, and consumer comfort.The existing literature has presented several methods, such as mathematical optimization, model predictive control, and heuristic control, for creating efficient operation schedules and for making good consumption and production decisions. However, the effectiveness of the methods in the existing literature can be difficult to compare due to diversity in modelling parameters, such as appliance models, timing parameters, and objectives.The present paper provides a comparative analysis of the literature on HEMS, with a focus on modelling approaches and their impact on HEMS operations and outcomes. In particular, we discuss a set of HEMS challenges such as forecast uncertainty, modelling device heterogeneity, multi-objective scheduling, computational limitations, timing considerations, and modelling consumer well-being.The presented work is organized to allow a reader to understand and compare the important considerations, approaches, nomenclature, and results in prominent and new literary works without delving deeply into each one.

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Section: Consequencementioning

confidence: 95%

“…However, the works in [14,34,54,146] suggest that these may not necessarily the most suitable parameters for residential energy scheduling. As such, it is important to use proper parameters in order to have a balance among the scheduling horizon, rescheduling interval, and time resolution.…”

Section: Computational Considerationsmentioning

confidence: 96%

Home energy management systems: A review of modelling and complexity

Beaudin

Zareipour

2015

Renewable and Sustainable Energy Reviews

387

206

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“…The study found large seasonal differences with regard to space heating, while the DHW consumption remained quite stable along the year. Another example is Bagge and Johansson [1], who made a detailed analysis of high-resolution measurements (6 s intervals) of 72 Swedish apartments' DHW consumption (as well as electricity consumption). The study found that the size of the time intervals between measurements influences the measured extreme values (power consumption); thus, the maximum DHW consumption was 40% higher at a 6 s resolution than at a 60 s resolution.…”

Section: Studies Of Energy Load Profiles Of Householdsmentioning

confidence: 99%

Cluster analysis of residential heat load profiles and the role of technical and household characteristics

Carmo

Christensen

2016

Energy and Buildings

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“…Domestic hot water usage is responsible for between 17 and 39% of household energy demand [1,2]; consequently, domestic hot water tanks represent a potentially significant source of energy storage to accommodate the large and intermittent demands of instantaneous power that occur throughout the day in a typical dwelling [3]. The transition towards renewable energy sources has led to an increased focus on the potential application of demand side management strategies for electric domestic hot water systems [4,5].…”

Section: Introductionmentioning

confidence: 99%