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The effect of missing data on wind resource estimation
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2011 (English)In: Energy, ISSN 0360-5442, Vol. 36, no 7, 4505-4517 p.Article in journal (Refereed) Published
Abstract [en]

Investment in renewable energy sources requires reliable data. However, meteorological datasets are often plagued by missing data, which can bias energy resource estimates if the missingness is systematic. We address this issue by considering the influence of missing data due to icing of equipment during the winter on the wind resource estimation for a potential wind turbine site in Norway. Using a mean-reverting jump-diffusion (MRJD) process to model electricity prices, we also account for the impact on the expected revenue from a wind turbine constructed at the site. While missing data due to icing significantly bias the wind resource estimate downwards, their impact on revenue estimates is dampened because of volatile electricity spot prices. By contrast, with low-volatility electricity prices, the effect of missing data on revenue estimates is highly significant. The seasonality-based method we develop removes most of the bias in wind resource and revenue estimation caused by missing data.

Place, publisher, year, edition, pages
2011. Vol. 36, no 7, 4505-4517 p.
Keyword [en]
Wind power, Missing data, Investment analysis
National Category
Information Systems, Social aspects
URN: urn:nbn:se:su:diva-66573DOI: 10.1016/ 000293115600060OAI: diva2:468714
authorCount :3Available from: 2011-12-21 Created: 2011-12-20 Last updated: 2011-12-21Bibliographically approved

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Siddiqui, Afzal
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