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Correlation between wind power generation in the European countries
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electricity. (Wind Power)
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electricity.
2016 (English)In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 114, 663-670 p.Article in journal (Refereed) Published
Abstract [en]

The correlations between wind power generation in different countries are important for quantifying the reductions in variability when electrically interconnecting the countries. Hourly, country-wise time series of wind power output were generated for all European countries using MERRA reanalysis data. By comparing the model output with actual measurements, it is shown that this approach is appropriate for studying correlations. In order to deepen the analysis, correlation coefficients were not only computed for these time series, but also for the one hour step changes and for band-pass filtered data. The general pattern is that correlations reduce with separation distance in an exponential fashion and are highest for the long-term components (T > 4 months) and lowest for step changes and short-term components (T < 2 days). Interesting deviations from this pattern however exist. When comparing to earlier results for individual farms, the exponential decay is slower, in particular for step changes.

Place, publisher, year, edition, pages
2016. Vol. 114, 663-670 p.
Keyword [en]
Wind power, Correlation, MERRA reanalysis dataset, Filters
National Category
Other Engineering and Technologies not elsewhere specified
Identifiers
URN: urn:nbn:se:uu:diva-301383DOI: 10.1016/j.energy.2016.08.036ISI: 000387194800052OAI: oai:DiVA.org:uu-301383DiVA: diva2:954375
Available from: 2016-08-22 Created: 2016-08-22 Last updated: 2017-01-25Bibliographically approved
In thesis
1. Modelling Wind Power for Grid Integration Studies
Open this publication in new window or tab >>Modelling Wind Power for Grid Integration Studies
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

When wind power and other intermittent renewable energy (IRE) sources begin to supply a significant part of the load, concerns are often raised about the inherent intermittency and unpredictability of these sources. In order to study the impact from higher IRE penetration levels on the power system, integration studies are regularly performed. The model package presented and evaluated in Papers I–IV provides a comprehensive methodology for simulating realistic time series of wind generation and forecasts for such studies. The most important conclusion from these papers is that models based on coarse meteorological datasets give very accurate results, especially in combination with statistical post-processing. Advantages with our approach include a physical coupling to the weather and wind farm characteristics, over 30 year long, 5-minute resolution time series, freely and globally available input data and computational times in the order of minutes. In this thesis, I make the argument that our approach is generally preferable to using purely statistical models or linear scaling of historical measurements.

In the variability studies in Papers V–VII, several IRE sources were considered. An important conclusion is that these sources and the load have very different variability characteristics in different frequency bands. Depending on the magnitudes and correlations of these fluctuation, different time scales will become more or less challenging to balance. With a suitable mix of renewables, there will be little or no increase in the needs for balancing on the seasonal and diurnal timescales, even for a fully renewable Nordic power system. Fluctuations with periods between a few days and a few months are dominant for wind power and net load fluctuations of this type will increase strongly for high penetrations of IRE, no matter how the sources are combined. According to our studies, higher capacity factors, more offshore wind power and overproduction/curtailment would be beneficial for the power system.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2016. 114 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1428
Keyword
Wind power, Wind power modelling, Intermittent renewables, Variability, Integration or renewables, Reanalysis data, Power system studies
National Category
Engineering and Technology
Identifiers
urn:nbn:se:uu:diva-302837 (URN)978-91-554-9690-6 (ISBN)
Public defence
2016-11-04, Polhemsalen, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2016-10-07 Created: 2016-09-11 Last updated: 2016-10-25

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