Modelling of energy use patterns in the residential sector using linguistic variables

Michalik, Grazyna; Mielczarski, W.

doi:10.1109/isap.1996.501082

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…The in-depth analysis of 120 individuals by [5] focuses on the derivation of energy use patterns from information about the time of use, duration of usage and type of appliances used. This data, described by linguistic variables, is processed by fuzzy filters to consider a level of uncertainty for individual households.…”

Section: Clustering Of Appliancesmentioning

confidence: 99%

Approaching the diversity of unbalanced residential load in low-voltage grids by probabilistic load-flow simulation of cross-sectional data

Huppertz

Kopczynski

Zeise

et al. 2015

2015 IEEE Eindhoven PowerTech

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For the approximation of low-voltage grid dynamics we present an energy based bottom-up model to create highly diverse household load profiles. In an object-oriented approach, nodal loads are represented by classifications of appliances and distributed to the phases in order to consider the characteristically unbalanced load of residential customers over time. Probability parameters, regarding time of use, corresponding duration of use and the magnitude of power consumption, are derived from a combination of statistical data and global load profiles. These parameters build probability models from crosssectional data for specific points in time which are processed by a probabilistic load-flow along the time axis. A simulation of a rural low-voltage grid using detailed information about the topology, renewable energy sources and residential energy consumption is performed. Results are validated and compared to high-resolution measurements of the real grid. The proposed model -embedded in an appropriate simulation scheme -will support the further development of planning, operational and control strategies for today's and future low-voltage grids.

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Section: Clustering Of Appliancesmentioning

confidence: 99%

Approaching the diversity of unbalanced residential load in low-voltage grids by probabilistic load-flow simulation of cross-sectional data

Huppertz

Kopczynski

Zeise

et al. 2015

2015 IEEE Eindhoven PowerTech

View full text Add to dashboard Cite

show abstract

“…The conduction of surveys is time demanding and results are difficult to implement [1]. The goal of the modeling is the simulation of realistic load curves of customers.…”

Section: Introductionmentioning

confidence: 99%

A time series probabilistic synthetic load curve model for residential customers

Dickert¹,

Schegner²

2011

2011 IEEE Trondheim PowerTech

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For the planning and operation of low-voltage systems models of the loads are needed. Little is known about residential loads besides the fact that they have a diverse behavior. This means that each residential load has seldom a maximum demand and the maximum demands of several customers do rarely coincide. As the number of residential customers increases the load curve of the group is becoming smoother.The utilities have information about the customers' yearly energy consumption and can estimate the maximum load of a group of customers. So far this information was sufficient since little attention was turned on the low-voltage networks. With the development of smart grids and the integration of distributed generation a better understanding of residential customers has to be obtained.With the proposed bottom-up approach residential loads can be composed by looking at each possible and relevant appliance, respective power consumption, frequency of use, turn-on time, operating time as well as potential correlation between appliances. Measurements were carried out on different types of appliances to determine individual load curves and to analyze the sequence of operation. The uniqueness of the presented model is the computational step time of 30 seconds for a single residential load.

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Power System Planning and Operation in a Competitive Environment: the Contributions of Artificial Intelligence

Alba

1997

IFAC Proceedings Volumes

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Modelling of energy use patterns in the residential sector using linguistic variables

Cited by 3 publications

References 2 publications

Approaching the diversity of unbalanced residential load in low-voltage grids by probabilistic load-flow simulation of cross-sectional data

Approaching the diversity of unbalanced residential load in low-voltage grids by probabilistic load-flow simulation of cross-sectional data

A time series probabilistic synthetic load curve model for residential customers

Power System Planning and Operation in a Competitive Environment: the Contributions of Artificial Intelligence

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