uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Characterizing probability density distributions for household electricity load profiles from high-resolution electricity use data
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics.
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics.
2014 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 135, 382-390 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2014. Vol. 135, 382-390 p.
Keyword [en]
Household electricity use, Stochastic modeling, Probability density distributions, Weibull distribution
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:uu:diva-240062DOI: 10.1016/j.apenergy.2014.08.093ISI: 000345470100036OAI: oai:DiVA.org:uu-240062DiVA: diva2:775974
Available from: 2015-01-05 Created: 2015-01-05 Last updated: 2017-12-05Bibliographically approved
In thesis
1. Distributed Photovoltaics, Household Electricity Use and Electric Vehicle Charging: Mathematical Modeling and Case Studies
Open this publication in new window or tab >>Distributed Photovoltaics, Household Electricity Use and Electric Vehicle Charging: Mathematical Modeling and Case Studies
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Technological improvements along with falling prices on photovoltaic (PV) panels and electric vehicles (EVs) suggest that they might become more common in the future. The introduction of distributed PV power production and EV charging has a considerable impact on the power system, in particular at the end-user in the electricity grid.

In this PhD thesis PV power production, household electricity use and EV charging are investigated on different system levels. The methodologies used in this thesis are interdisciplinary but the main contributions are mathematical modeling, simulations and data analysis of these three components and their interactions. Models for estimating PV power production, household electricity use, EV charging and their combination are developed using data and stochastic modeling with Markov chains and probability distributions. Additionally, data on PV power production and EV charging from eight solar charging stations is analyzed.

Results show that the clear-sky index for PV power production applications can be modeled via a bimodal Normal probability distribution, that household electricity use can be modeled via either Weibull or Log-normal probability distributions and that EV charging can be modeled by Bernoulli probability distributions. Complete models of PV power production, household electricity use and EV home-charging are developed with both Markov chain and probability distribution modeling. It is also shown that EV home-charging can be modeled as an extension to the Widén Markov chain model for generating synthetic household electricity use patterns. Analysis of measurements from solar charging stations show a wide variety of EV charging patterns. Additionally an alternative approach to modeling the clear-sky index is introduced and shown to give a generalized Ångström equation relating solar irradiation to the duration of bright sunshine.

Analysis of the total power consumption/production patterns of PV power production, household electricity use and EV home-charging at the end-user in the grid highlights the dependency between the components, which quantifies the mismatch issue of distributed intermittent power production and consumption. At an aggregate level of households the level of mismatch is shown to be lower.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2015. 93 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1224
Keyword
Distributed Photovoltaics, Household Electricity Use, Electric Vehicle Charging, Markov Chain Modeling, Probability Distribution Modeling, Data Analysis, Self-Consumption, Grid Interaction.
National Category
Energy Systems
Research subject
Engineering Science
Identifiers
urn:nbn:se:uu:diva-243159 (URN)978-91-554-9162-8 (ISBN)
Public defence
2015-03-27, Polhemsalen, Ångström Laboratory, Lägerhyddsvägen 1, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2015-03-04 Created: 2015-02-05 Last updated: 2015-03-12Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Authority records BETA

Munkhammar, JoakimRydén, JesperWiden, Joakim

Search in DiVA

By author/editor
Munkhammar, JoakimRydén, JesperWiden, Joakim
By organisation
Solid State PhysicsDepartment of Mathematics
In the same journal
Applied Energy
Energy Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 1001 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf