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Quantifying self-consumption of on-site photovoltaic power generation in households with electric vehicle home charging
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics. (BEESG)
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics. (BEESG)
2013 (English)In: Solar Energy, ISSN 0038-092X, E-ISSN 1471-1257, Vol. 97, 208-216 p.Article in journal (Refereed) Published
Abstract [en]

Photovoltaic (PV) power production and residential power demand are negativelycorrelated at high latitudes on both annual and diurnal basis. If PVpenetration levels increase, methods to deal with power overproduction in the localdistribution grids are needed to avoid costly grid reinforcements. Increased local consumption isone such option. The introduction of a home-chargedplug-in electric vehicle (PEV) has a significant impact on the household load and potentiallychanges the coincidence between household load and photovoltaic power production.This paper uses a stochastic model to investigate the effect on the coincidence between householdload and photovoltaic power production when including a PEV load. The investigationis based on two system levels: (I) individual householdlevel and (II) aggregate household level. The stochastic model produces theoretical high-resolutionload profiles for household load and home charged PEV load over time.The photovoltaic power production model is based on high-resolution irradiance data for Uppsala, Sweden.It is shown that the introduction of a PEV improves the self-consumption of the photovoltaicpower both on an individual and an aggregate level, but the increase is limited due to thelow coincidence between the photovoltaic power production pattern and the charging patterns of the PEV.

Place, publisher, year, edition, pages
2013. Vol. 97, 208-216 p.
National Category
Engineering and Technology
Research subject
Engineering Science with specialization in Solid State Physics
Identifiers
URN: urn:nbn:se:uu:diva-195831DOI: 10.1016/j.solener.2013.08.015ISI: 000326851400023OAI: oai:DiVA.org:uu-195831DiVA: diva2:608412
Available from: 2013-02-27 Created: 2013-02-27 Last updated: 2017-12-06Bibliographically approved
In thesis
1. Markov-chain modeling of energy users and electric vehicles: Applications to distributed photovoltaics
Open this publication in new window or tab >>Markov-chain modeling of energy users and electric vehicles: Applications to distributed photovoltaics
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Technological improvements and falling prices on photovoltaic panels andelectric vehicles suggest that they might become more common in future households.The introduction of a photovoltaic system and an electric vehiclehas considerable impact on the energy balance of a household. This licentiate thesis investigates the power consumption- and productionpatterns associated with the photovoltaic (PV) electricity production,household electricity consumption and home charged plug-in electric vehicle(PEV) electricity consumption. This investigation is carried out on both an individual and aggregate household level. The methodology used in this thesis is interdisciplinary but the maincontributions are mathematical modeling and simulations of the three main components. Theoretical estimates of electricityconsumption were constructed from extensions to the Wid\'{e}n Markov-chain model for generating synthetichousehold electricity use patterns. The main research contribution in thisthesis is the development and analysis of two extensions of this Markov-chain model: (I) Electricity use from a home charged PEV,(II) Flexibility of end-user power use. These two extensions were used in studiesregarding the coincidence - in particular the level of self-consumption - between PV electricityproduction and household electricity use. PV electricity production was modeledfrom high resolution solar irradiance data from the Ångström laboratory.\\Results show that the home charged PEV load would increase the household loadconsiderably. It was also shown that the level of correlation between PEV load and PVelectricity production was low, but that to some extent the PEV load could help increasethe self-consumption of PV power, both on individual and aggregate household level.\\The modeling and simulations of end-user flexibility showed that the householdload profile could be altered to a certain degree. It was also shown thatcertain flexibility setup could improve the self-consumption of PV power production, more so than theintroduction of a PEV.

Place, publisher, year, edition, pages
Uppsala: Uppsala universitet, 2012. 50 p.
National Category
Engineering and Technology
Research subject
Engineering Science with specialization in Solid State Physics
Identifiers
urn:nbn:se:uu:diva-195824 (URN)
Presentation
2012-12-10, Häggsalen, Ångströmlaboratoriet, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2013-02-27 Created: 2013-02-27 Last updated: 2013-02-27Bibliographically approved
2. 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

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Munkhammar, JoakimWidén, Joakim

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