Characterizing probability density distributions for household electricity load profiles from high-resolution electricity use data

Joakim Munkhammar, Jesper Rydén and Joakim Widén

Applied Energy, 2014, vol. 135, issue C, 382-390

Abstract: This paper presents a high-resolution bottom-up model of electricity use in an average household based on fit to probability distributions of a comprehensive high-resolution household electricity use data set for detached houses in Sweden. The distributions used in this paper are the Weibull distribution and the Log-Normal distribution. These fitted distributions are analyzed in terms of relative variation estimates of electricity use and standard deviation. It is concluded that the distributions have a reasonable overall goodness of fit both in terms of electricity use and standard deviation. A Kolmogorov–Smirnov test of goodness of fit is also provided. In addition to this, the model is extended to multiple households via convolution of individual electricity use profiles. With the use of the central limit theorem this is analytically extended to the general case of a large number of households. Finally a brief comparison with other models of probability distributions is made along with a discussion regarding the model and its applicability.

Keywords: Household electricity use; Stochastic modeling; Probability density distributions; Weibull distribution (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:135:y:2014:i:c:p:382-390

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DOI: 10.1016/j.apenergy.2014.08.093

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