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Distributed Photovoltaics, Household Electricity Use and Electric Vehicle Charging: Mathematical Modeling and Case Studies
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences. (Built Environment Energy Systems Group)
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 [en]
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: urn:nbn:se:uu:diva-243159ISBN: 978-91-554-9162-8 (print)OAI: oai:DiVA.org:uu-243159DiVA: diva2:786249
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
List of papers
1. Simulating dispersed photovoltaic power generation using a bimodal mixture model of the clear-sky index
Open this publication in new window or tab >>Simulating dispersed photovoltaic power generation using a bimodal mixture model of the clear-sky index
2015 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Improved probability distribution models for power generation are useful e.g. forprobabilistic power flow simulations. This paper presents a distribution modelfor photovoltaic (PV) power generation based on the clear-sky index.With the use of minute-resolution data on globalhorizontal irradiation (GHI) we fit unimodal normal,bimodal normal and trimodal normal mixture distributionfamilies to the clear-sky index. Based on Kolmogorov-Smirnov (K-S) teststhe best fit distribution family consisting of a bimodal normal distribution isthen used for estimating an aggregate clear-sky index for multipledispersed locations that are assumed to be uncorrelated in terms of sky clearness.For five or more locations the aggregate clear-sky indexfollows a normal distribution due to the central limit theorem.Models for solar radiation on tilted planes and PV power generation areapplied to the clear-sky index to generate probability distributions for anarbitrary PV system.

National Category
Engineering and Technology
Research subject
Engineering Science
Identifiers
urn:nbn:se:uu:diva-242439 (URN)
Conference
EU PVSEC - 31st European Photovoltaic Solar Energy Conference and Exhibition, 14-18 September, 2016, Hamburg, Germany
Available from: 2015-01-26 Created: 2015-01-26 Last updated: 2016-05-27Bibliographically approved
2. On a Probability Distribution Convolution Approach to Clear-Sky Index and a Generalized Ångström Equation
Open this publication in new window or tab >>On a Probability Distribution Convolution Approach to Clear-Sky Index and a Generalized Ångström Equation
(English)Manuscript (preprint) (Other academic)
Abstract [en]

We show that by modeling solar beam irradiance approximately as a simple Bernoulli distribution and diffuse irradiance as a Gamma distribution, a generalized Ångström equation relating solar irradiation to sunshine hours follows directly as aconsequence of the convolution of beam and diffuseirradiance distributions into a distribution for the clear-sky index.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:uu:diva-242441 (URN)
Available from: 2015-01-26 Created: 2015-01-26 Last updated: 2017-10-27Bibliographically approved
3. Characterizing probability density distributions for household electricity load profiles from high-resolution electricity use data
Open this publication in new window or tab >>Characterizing probability density distributions for household electricity load profiles from high-resolution electricity use data
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.

Keyword
Household electricity use, Stochastic modeling, Probability density distributions, Weibull distribution
National Category
Energy Engineering
Identifiers
urn:nbn:se:uu:diva-240062 (URN)10.1016/j.apenergy.2014.08.093 (DOI)000345470100036 ()
Available from: 2015-01-05 Created: 2015-01-05 Last updated: 2017-12-05Bibliographically approved
4. PHEV Home-Charging Model Based on Residential Activity Patterns
Open this publication in new window or tab >>PHEV Home-Charging Model Based on Residential Activity Patterns
Show others...
2013 (English)In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 28, no 3, 2507-2515 p.Article in journal (Refereed) Published
Abstract [en]

Plug-in hybrid electric vehicles (PHEVs) have received an increased interest lately since they provide an opportunity to reduce greenhouse gas emissions. Based on the PHEV introduction level in the car park, the charging behaviors in an area will induce changes in the load profiles of the power system. Hence, it becomes important to investigate what impact a given PHEV introduction level has on load profiles due to expected charging behavior of residents. This paper proposes a new model for generating PHEV home-charging patterns by combining PHEV usage with synthetic activity generation of residents' electricity-dependent activities. The synthetic activity data are simulated based on time-use data collected in time diaries, and define the basis for calculations of the PHEV home-charging behavior as well as the resident's electricity consumption. The proposed model is generic and can be used where similar residential time-use data are available. Based on the underlying activities, the model estimates the total load profile due to residential load as well as the variation in the load profile. The resulting load profiles can be used in load shaving studies in order to investigate what type of activities, PHEV usage or other, may be moved to hours with lower demand.

National Category
Engineering and Technology
Research subject
Engineering Science with specialization in Solid State Physics
Identifiers
urn:nbn:se:uu:diva-195823 (URN)10.1109/TPWRS.2012.2230193 (DOI)000322989900046 ()
Available from: 2013-02-27 Created: 2013-02-27 Last updated: 2017-12-06Bibliographically approved
5. A Bernoulli Distribution Model for Plug-in Electric Vehicle Charging based on Time-use Data for Driving Patterns
Open this publication in new window or tab >>A Bernoulli Distribution Model for Plug-in Electric Vehicle Charging based on Time-use Data for Driving Patterns
2014 (English)In: Proceedings of IEEE International Electric Vehicle Conference (IEVC), 2014Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a Bernoulli distribution model for plug-in electric vehicle (PEV)charging based on high resolution activity data for Swedish drivingpatterns. Based on the activity ``driving vehicle" from a time diary studya Monte Carlo simulation is made of PEV state of chargewhich is then condensed down to Bernoulli distributions representingcharging for each hour during weekday and weekend day. Thesedistributions are then used as a basis for simulations of PEVcharging patterns. Results regarding charging patterns for a numberof different PEV parameters are shown along with a comparison with resultsfrom a different stochastic model for PEV charging. A convergence test forMonte Carlo simulations of the distributions is also provided.In addition to this we show that multiple PEV charging patterns are representedby Binomial distributions via convolution ofBernoulli distributions. Also the distribution for aggregatecharging of many PEVs is shown to be normally distributed. Finally a fewremarks regarding the applicability of the model are given along witha discussion on potential extensions.

National Category
Other Engineering and Technologies
Research subject
English
Identifiers
urn:nbn:se:uu:diva-242437 (URN)10.1109/IEVC.2014.7056224 (DOI)
Conference
IEEE International Electric Vehicle Conference (IEVC), 17-19 Dec. 2014, Florence, Italy
Available from: 2015-01-26 Created: 2015-01-26 Last updated: 2016-05-27Bibliographically approved
6. Household electricity use, electric vehicle home-charging and distributed photovoltaic power production in the city of Westminster
Open this publication in new window or tab >>Household electricity use, electric vehicle home-charging and distributed photovoltaic power production in the city of Westminster
Show others...
2015 (English)In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 86, 439-448 p.Article in journal (Refereed) Published
Abstract [en]

In this paper we investigate household electricity use, electric vehicle (EV) home-charging and distributed photovoltaic (PV) power production in a case study for the city of Westminster, London. Since it is economically beneficial to maximize PV power self-consumption in the UK context the power consumption/production patterns with/without introducing EV home-charging on the household level is investigated. Additionally, since this might have an effect on the electricity use on an aggregate of households a large-scale introduction of EV charging and PV power production in the entire city of Westminster is also investigated. Household electricity consumption and EV home-charging are modeled with a Markov-chain model. PV power production is estimated from solar irradiation data from Meteonorm for the location of Westminster combined with a model for photovoltaic power production on tilted planes. The available rooftop area is estimated from the UK map geographic information database. EV home-charging increases the household electricity use mainly during evening with a maximum during winter whereas PV produces power during daytime with maximum during summer. On the household level this mismatch introduces variability in power consumption/production, which is shown to be less prominent for the large-scale scenario of the entire city of Westminster.

National Category
Energy Engineering
Research subject
Engineering Science with specialization in Solid State Physics
Identifiers
urn:nbn:se:uu:diva-236895 (URN)10.1016/j.enbuild.2014.10.006 (DOI)000347494900041 ()
Available from: 2014-11-25 Created: 2014-11-25 Last updated: 2017-12-05Bibliographically approved
7. Quantifying self-consumption of on-site photovoltaic power generation in households with electric vehicle home charging
Open this publication in new window or tab >>Quantifying self-consumption of on-site photovoltaic power generation in households with electric vehicle home charging
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.

National Category
Engineering and Technology
Research subject
Engineering Science with specialization in Solid State Physics
Identifiers
urn:nbn:se:uu:diva-195831 (URN)10.1016/j.solener.2013.08.015 (DOI)000326851400023 ()
Available from: 2013-02-27 Created: 2013-02-27 Last updated: 2017-12-06Bibliographically approved
8. On a probability distribution model combining household power consumption, electric vehicle home-charging and photovoltaic power production
Open this publication in new window or tab >>On a probability distribution model combining household power consumption, electric vehicle home-charging and photovoltaic power production
2015 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 142, 135-143 p.Article in journal (Refereed) Published
Abstract [en]

In this paper we develop a probability distribution model combining household power consumption, electric vehicle (EV) home-charging and photovoltaic (PV) power production. The model is set up using a convolution approach to merge three separate existing probability distribution models for household electricity use, EV home-charging and PV power production. This model is investigated on two system levels: household level and aggregate level of multiple households. Results for the household level show the power consumption/production mismatch as probability distributions for different time bins. This is further investigated with different levels of PV power production. The resulting yearly distribution of the aggregate scenario of multiple uncorrelated households with EV charging and PV power production is shown to not be normally distributed due to the mismatch of PV power production and household power consumption on a diurnal and annual basis.

National Category
Engineering and Technology
Research subject
Engineering Science with specialization in Solid State Physics
Identifiers
urn:nbn:se:uu:diva-243157 (URN)10.1016/j.apenergy.2014.12.031 (DOI)000350935100013 ()
Available from: 2015-02-05 Created: 2015-02-05 Last updated: 2017-12-05Bibliographically approved
9. Electric Vehicle Charging and Photovoltaic Power Production from Eight Solar Charging Stations in Sweden
Open this publication in new window or tab >>Electric Vehicle Charging and Photovoltaic Power Production from Eight Solar Charging Stations in Sweden
2014 (English)In: 4th Solar Integration Workshop: Proceedings of the 4th International Workshop on Integration of Solar Power into Power Systems, Darmstadt: Energynautics , 2014, 425-429 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper quantifies and analyzes data for electric vehicle (EV) charging and photovoltaic(PV) power production from eight charging stations in Sweden withadjacent PV power production provided by Solelia Greentech AB. This study aims toshow the grid interaction of EV charging and PV power production from these solar charging stationswhich are distributed in pairs at four different locations across Sweden. This study utilizesone minute resolution data on power consumption and production from between 281 and310 consecutive days depending on available solar charging station data. Each site, correspondingto two adjacent solar charging stations, has a specific setup regarding EV charging consumer availability.EV charging at two of the sites were available only for the local company/municipality employees and visitors to the company/municipalitywhile the other two sites were public. There was no economical charge for EV charging at any of the stations.Results show that EV charging magnitude and use patterns over timevaried considerably between the stations. Half of the stations had a net consumption of electricityand the other half of stations had a net production of electricity during the metering period.Self-consumption of PV power production was estimated to be between 0.2 and 10 percentdepending on station.

Place, publisher, year, edition, pages
Darmstadt: Energynautics, 2014
Keyword
Elbilsladdning, solelproduktion, dataanalys
National Category
Engineering and Technology
Research subject
Engineering Science
Identifiers
urn:nbn:se:uu:diva-236889 (URN)978-3-9816549-0-5 (ISBN)
Conference
4th International Workshop on Integration of Solar into Power Systems, 10-11 November 2014, Berlin, Germany
Available from: 2014-11-25 Created: 2014-11-25 Last updated: 2016-05-27Bibliographically approved

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