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Daily cost optimization in a utility network with renewable energy sources and energy storage
2018 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The growing consequentiality of the role of renewable energy sources alongside energy storage devices in the potency and power market in this sector has magnetized the attention of many researchers in this field. The technical potentials indicate the ability to utilize renewable energy resources and energy storage equipment in the network. In order to increase the utilization of these resources in the network, it should be examined from an economic perspective. Therefore, in this master thesis, it has been tried to optimize the effect of using these systems on minimizing the daily cost of electric power generation in the electricity grid. After the technical and economic introduction of the equipment used in the network, the economic and technical model of the network is specified. The goal is to calculate the minimum cost of daily electrical energy production, along with using all the technical and security constraints of the network. The result of the optimization calculations is the amount of power produced by the power plants, the time schedule of operating the storage system during the day and the lowest production cost. The technical and economic model in addition to the optimization algorithm based on the particle swarm optimization is implemented in the MatLab software environment. A standard IEEE network is used to model the data. Simulation results demonstrate the high potential of the storage system to reduce costs and increase the operating efficiency of the network so that the use of a central storage system in the proper bus of the network can reduce the cost of energy production by up to 3%. Also, the use of these new systems at the appropriate capacity can delay network upgrades to 16 years in provided the increasing the demand (equivalent to 2% per annum).

Place, publisher, year, edition, pages
2018. , p. 54
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-37926OAI: oai:DiVA.org:hh-37926DiVA, id: diva2:1246296
Educational program
Master's Programme in Renewable Energy Systems, 60 credits
Supervisors
Examiners
Available from: 2018-09-10 Created: 2018-09-07 Last updated: 2018-09-10Bibliographically approved

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Engineering and Technology

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • 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