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A New Approach to Obtain Synthetic Wind Power Forecasts for Integration Studies
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electricity. (Wind Power)
Vattenfall, Evenemangsgatan 13, 169 92 Solna, Sweden.
Vattenfall, Evenemangsgatan 13, 169 92 Solna, Sweden.
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electricity.
2016 (English)In: Energies, ISSN 1996-1073, E-ISSN 1996-1073, Vol. 9, no 10, 800Article in journal (Refereed) Published
Abstract [en]

When performing wind integration studies, synthetic wind power forecasts are key elements. Historically, data from operational forecasting systems have been used sparsely, likely due to the high costs involved. Purely statistical methods for simulating wind power forecasts are more common,but have problems mimicking all relevant aspects of actual forecasts. Consequently, a new approach to obtain wind power forecasts for integration studies is proposed, relying on long time series of freely and globally available reforecasts. In order to produce synthetic forecasts with similar properties as operational ditto, some processing (noise addition and error reduction) is necessary. Validations with measurements from Belgium and Sweden show that the method is adequate; and distributions, correlations, autocorrelations and power spectral densities of forecast errors correspond well. Furthermore, abrupt changes when forecasts are updated and the existence of level and phase errors are reproduced. The influence from terrain complexity on error magnitude is promising, but more data is necessary for a proper validation.

Place, publisher, year, edition, pages
2016. Vol. 9, no 10, 800
Keyword [en]
wind power forecasting; synthetic forecasts; GEFS reforecast; power system studies; wind power integration; production planning; dispatch
National Category
Environmental Engineering
URN: urn:nbn:se:uu:diva-302835DOI: 10.3390/en9100800OAI: diva2:967993
Available from: 2016-09-11 Created: 2016-09-11 Last updated: 2016-10-06Bibliographically 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.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1428
Wind power, Wind power modelling, Intermittent renewables, Variability, Integration or renewables, Reanalysis data, Power system studies
National Category
Engineering and Technology
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)
Available from: 2016-10-07 Created: 2016-09-11 Last updated: 2016-10-11

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