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Optimal sizing of the wind farm and wind farm transformer using MILP and dynamic transformer rating
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electromagnetic Engineering. (QED Asset Management group)ORCID iD: 0000-0002-4065-715X
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering.
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electromagnetic Engineering.ORCID iD: 0000-0002-2964-7233
2022 (English)In: International Journal of Electrical Power & Energy Systems, ISSN 0142-0615, E-ISSN 1879-3517, Vol. 136, p. 107645-107645, article id 107645Article in journal (Refereed) Published
Abstract [en]

An increase in electricity demand and renewable penetration requires electrical utilities to improve and optimize the grid infrastructure. Fundamental components in this grid infrastructure are transformers, which are designed conservatively based on static rated power. However, load and weather change continuously and hence, transformers are not used most efficiently. For this reason, new technology has been developed: Dynamic transformer rating (DTR). Applying DTR makes it possible to load transformers above the nameplate rating without affecting their lifetime expectancy. This study uses DTR for short-term and long-term wind farm planning. The optimal wind farm is designed by applying DTR to the power transformer and using it as an input to a Mixed-Integer Linear Programming (MILP) model. Regarding the transformer thermal analysis, the linearized top oil model of IEEE Clause 7 is selected. The model is executed for 4 different types of power transformers: 63 MVA, 100 MVA, 200 MVA and 400 MVA. As a result, it is obtained that the net present value for the investment and the capacity of the wind farm increase linearly with respect to the size of the transformer. Then, a sensitivity analysis is carried out by modifying the wind speed, the electricity price, the lifetime of the transformer and the selected weather data. From this sensitivity analysis, it is possible to conclude that wind resources and electricity price are critical parameters for the wind farm’s feasibility.

Place, publisher, year, edition, pages
Elsevier BV , 2022. Vol. 136, p. 107645-107645, article id 107645
Keywords [en]
Electrical and Electronic Engineering, Energy Engineering and Power Technology
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-303928DOI: 10.1016/j.ijepes.2021.107645ISI: 000710414200006Scopus ID: 2-s2.0-85116893118OAI: oai:DiVA.org:kth-303928DiVA, id: diva2:1605087
Funder
StandUp for WindSwedish Energy AgencySweGRIDS - Swedish Centre for Smart Grids and Energy Storage
Note

QC 20211110

Available from: 2021-10-21 Created: 2021-10-21 Last updated: 2024-03-15Bibliographically approved

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Morozovska, KaterynaLaneryd, TorHilber, Patrik

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CiteExportLink to record
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Citation style
  • apa
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