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Workplace Electric Vehicle Solar Smart Charging based on Solar Irradiance Forecasting
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences.
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences.
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences.
2017 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The purpose of this bachelor thesis is to investigate different outcomes of the usage of photovoltaic (PV) power for electric vehicle (EV) charging adjacent to workplaces. In the investigated case, EV charging stations are assumed to be connected to photovoltaic systems as well as the electricity grid. The model used to simulate different scenarios is based on a goal of achieving constant power exchange with the grid by adjusting EV charging to a solar irradiance forecast. The model is implemented in MATLAB. This enables multiple simulations for varying input parameters. Data on solar irradiance are used to simulate the expected PV power generation. Data on driving distances are used to simulate hourly electricity demands of the EVs at the charging stations. A sensitivity analysis, based on PV irradiance that deviates from the forecast, is carried out. The results show what power the grid needs to have installed capacity for if no PV power system is installed. Furthermore, appropriate PV power installation sizes are suggested. The suggestions depend on whether the aim is to achieve 100 percent self-consumption of PV generated power or full PV power coverage of charging demands. For different scenarios, PV power installations appropriate for reducing peak powers on the grid are suggested. The sensitivity analysis highlights deviations caused by interference in solar irradiance. 

Place, publisher, year, edition, pages
2017. , 30 p.
Series
TVE, TVE-STS 17 002 maj
Keyword [en]
electric vehicle, smart charging, solar forecast, photovoltaic power, pv power, ev charging
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:uu:diva-323319OAI: oai:DiVA.org:uu-323319DiVA: diva2:1105950
External cooperation
Solelia Greentech AB
Educational program
Systems in Technology and Society Programme
Supervisors
Examiners
Available from: 2017-06-14 Created: 2017-06-05 Last updated: 2017-06-14Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
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Output format
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