This thesis investigates if the profitability of a wind farm can be increased by reducing itscontracted grid capacity. Two years of SCADA data is cleaned from non- and partialperformance which is used to estimate a wake reduced annual power time series. Stochasticmodels of production losses are applied to translate the wake reduced annual power timeseries. Ice losses are modelled with a 3-state Markov chain. The statistical properties arecalculated by identifying ice events in the SCADA. With the IEA task19 IceLoss algorithm areice events identified in the SCADA signal. An ice loss factor of 86 % is estimated for Juktanduring 2019. The results indicate that profitability can be increased by reducing the (contracted)grid capacity. Furthermore, the optimized grid capacity is shown to have low sensitivity to powerprice and ice losses. This finding is valuable since the power price market and weather areinherently difficult to predict. It follows that the prediction uncertainties of these inputs are lesssignificant when calculating the optimized grid capacity.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-474995 |
| Date | January 2022 |
| Creators | Wall, Patrik |
| Publisher | Uppsala universitet, Elektricitetslära |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | UPTEC F, 1401-5757 ; 21058 |
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