A combined Markov-chain and bottom-up approach to modelling of domestic lighting demand

Widén, Joakim; Nilsson, Annica M.; Wäckelgård, Ewa

doi:10.1016/j.enbuild.2009.05.002

Cited by 183 publications

(97 citation statements)

References 14 publications

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“…These data have been analysed previously in a behavioural study connected to the measurement survey [18] and for validation of the load models in refs. [19,20,21]. They have therefore been carefully examined for consistency and quality.…”

Section: Electricity Demand Datamentioning

confidence: 99%

Impacts of different data averaging times on statistical analysis of distributed domestic photovoltaic systems

Widén

Wäckelgård

Paatero³

et al. 2010

Solar Energy

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The trend of increasing application of distributed generation with solar photovoltaics (PV-DG) suggests that a widespread integration in existing low-voltage (LV) grids is possible in the future. With massive integration in LV grids, a major concern is the possible negative impacts of excess power injection from on-site generation. For power-ow simulations of such grid impacts, an important consideration is the time resolution of demand and generation data. This paper investigates the impact of time averaging on high-resolution data series of domestic electricity demand and PV-DG output and on voltages in a simulated LV grid. E ects of 10-minutely and hourly averaging on descriptive statistics and duration curves were determined. Although time averaging has a considerable impact on statistical properties of the demand in individual households, the impact is smaller on aggregate demand, already smoothed from random coincidence, and on PV-DG output. Consequently, the statistical distribution of simulated grid voltages was also robust against time averaging. The overall judgement is that statistical investigation of voltage variations in the presence of PV-DG does not require higher resolution than hourly.1

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Section: Electricity Demand Datamentioning

confidence: 99%

Impacts of different data averaging times on statistical analysis of distributed domestic photovoltaic systems

Widén

Wäckelgård

Paatero³

et al. 2010

Solar Energy

Self Cite

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“…The probability of turning on lights was modeled as a decision, based on the lighting level and occupant movement. Since these studies were mainly based on small office buildings [21,23] and residential buildings [24], suggesting a strong need to conduct more research on lighting energy use in large office buildings.…”

Section: Introductionmentioning

confidence: 99%

“…Reinhart used the Lightswitch-2002 model to evaluate the energy savings from different lighting control strategies. Joakim Wide´n et al [24] used Markov chains to estimate the probability of occupant movement. The probability of turning on lights was modeled as a decision, based on the lighting level and occupant movement.…”

Section: Introductionmentioning

confidence: 99%

Data analysis and stochastic modeling of lighting energy use in large office buildings in China

Zhou

Yan

Hong

et al. 2015

Energy and Buildings

107

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“…Occupancy and activity profiles are then used as determinant in the switch-on events of consumer operated appliances. Lighting models that include dependence on irradiance levels have also been established allowing lighting seasonal variations to be modelled [9], [10].…”

Section: Introductionmentioning

confidence: 99%

Discrete elastic residential load response under variable pricing schemes

McKenna

Keane

2014

IEEE PES Innovative Smart Grid Technologies, Europe

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A combined Markov-chain and bottom-up approach to modelling of domestic lighting demand

Cited by 183 publications

References 14 publications

Impacts of different data averaging times on statistical analysis of distributed domestic photovoltaic systems

Impacts of different data averaging times on statistical analysis of distributed domestic photovoltaic systems

Data analysis and stochastic modeling of lighting energy use in large office buildings in China

Discrete elastic residential load response under variable pricing schemes

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