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Optimization of a Household Battery Storage: The Value of Load Shift
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics.
2016 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Sweden’s energy system is facing major changes in the near future in order to reducecarbon emissions and to switch to sustainable energy sources. PV systems havebecome a sensible alternative for homeowners that want to be a part of this changeand at the same time reduce the cost of their electricity bill. To further improve theutilization of their PV system and to handle the intermittent nature of solar power,battery storages have become an interesting system complement. This thesisinvestigates how batteries can provide smart services; load shift and peak price energyutilization to a household. This is done by developing an optimized battery algorithmmodel that can provide these smart services which is compared to a simple batteryalgorithm. The results show that the developed battery optimization model works asintended. It performs both load shift and peak price energy utilization. The economicanalysis shows that the most profitable PV system and battery configuration is a 20kW PV system with a 5 kWh battery. The system has an internal rate of return, IRR,of 2.3% which does not reach Vattenfall’s weighted average cost of capital, WACC, at7%. The results also show that the battery cost is an important factors for a system'sprofitability. A larger battery system is more expensive and the increased yield doesnot cover the increased cost. Further research is needed to implement the optimizedbattery as a functional application since the model has access to a perfect forecast andthus a method for forecasting PV production and load profile of the household arecrucial to get similar results.

Place, publisher, year, edition, pages
2016. , 36 p.
Series
UPTEC ES, ISSN 1650-8300 ; 16012
Keyword [en]
Battery Storage, Load Shift, Energy, Photovoltaic, Optimization, Solar Power, Spot Price, Peak Price, Electricity, Power Management, Smart Services
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:uu:diva-298417OAI: oai:DiVA.org:uu-298417DiVA: diva2:946072
External cooperation
Vattenfall R&D
Educational program
Master Programme in Energy Systems Engineering
Supervisors
Examiners
Available from: 2016-07-05 Created: 2016-07-04 Last updated: 2016-07-05Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Language
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Output format
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