Comparison of wind power estimates from the ECMWF reanalyses with direct turbine measurements

Kiss, Péter; Varga, László; Jánosi, Imre M.

doi:10.1063/1.3153903

Cited by 30 publications

(16 citation statements)

References 37 publications

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“…Most interesting are studies where the resulting wind power time series have been compared against historical records. Kiss et al [8] appears to be first to compared nacelle measurements of wind speed and power generation from two turbines in Hungary to the ERA-40 reanalysis data set. They found a "satisfying agreement" with proper calibration of the conversion model.…”

Section: Previous Studiesmentioning

confidence: 99%

Validation of Danish wind time series from a new global renewable energy atlas for energy system analysis

Andresen

Søndergaard

Greiner

2015

Energy

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We present a new high-resolution global renewable energy atlas (REatlas) that can be used to calculate customised hourly time series of wind and solar PV power generation. In this paper, the atlas is applied to produce 32-year-long hourly model wind power time series for Denmark for each historical and future year between 1980 and 2035. These are calibrated and validated against real production data from the period 2000 to 2010. The high number of years allows us to discuss how the characteristics of Danish wind power generation varies between individual weather years. As an example, the annual energy production is found to vary by ±10% from the average. Furthermore, we show how the production pattern change as small onshore turbines are gradually replaced by large onshore and offshore turbines. Finally, we compare our wind power time series for 2020 to corresponding data from a handful of Danish energy system models. The aim is to illustrate how current differences in model wind may result in significant differences in technical and economical model predictions. These include up to 15% differences in installed capacity and 40% differences in system reserve requirements.

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Section: Previous Studiesmentioning

confidence: 99%

Validation of Danish wind time series from a new global renewable energy atlas for energy system analysis

Andresen

Søndergaard

Greiner

2015

Energy

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“…Both ERAInterim (Dee et al, 2011) and NCEP (Kalnay et al, 1996) reanalyses cover the whole period 1997-2007 for which VGV data are available to calibrate the loss functions (see Sect. 3.1).…”

Section: Meteorological Datamentioning

confidence: 99%

High-resolution refinement of a storm loss model and estimation of return periods of loss-intensive storms over Germany

Donat

Pardowitz²,

Leckebusch

et al. 2011

Nat. Hazards Earth Syst. Sci.

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Abstract.A refined model for the calculation of storm losses is presented, making use of high-resolution insurance loss records for Germany and allowing loss estimates on a spatial level of administrative districts and for single storm events. Storm losses are calculated on the basis of wind speeds from both ERA-Interim and NCEP reanalyses. The loss model reproduces the spatial distribution of observed losses well by taking specific regional loss characteristics into account. This also permits high-accuracy estimates of total cumulated losses, though slightly underestimating the country-wide loss sums for storm "Kyrill", the most severe event in the insurance loss records from 1997 to 2007. A larger deviation, which is assigned to the relatively coarse resolution of the NCEP reanalysis, is only found for one specific rather smallscale event, not adequately captured by this dataset.The loss model is subsequently applied to the complete reanalysis period to extend the storm event catalogue to cover years when no systematic insurance records are available. This allows the consideration of loss-intensive storm events back to 1948, enlarging the event catalogue to cover the recent 60+ years, and to investigate the statistical characteristics of severe storm loss events in Germany based on a larger sample than provided by the insurance records only. Extreme value analysis is applied to the loss data to estimate the return periods of loss-intensive storms, yielding a return period for storm "Kyrill", for example, of approximately 15 to 21 years.Correspondence to: M. G. Donat

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“…Due to geographic constraints in the Carpathian basin, Hungary is not very rich in wind energy [7][8][9][10][11][12], and electricity production is extremely intermittent at each site (see Figure 2). Typical capacity factors (the ratio of mean and rated output power) at working turbines hardly exceed 25%, particular values are at K: 19.92% ± 23.71%, 17.42% ± 22.61%, 20.89% ± 24.98%; at M 1: 20.76% ± 11.55%, 22.33% ± 12.58%, 20.27% ± 11.24%; and at M 2: 21.26% ± 11.66%, 23.16% ± 12.24%, 21.55%±11.58% in three consecutive full years shown in Figure 1.…”

Section: M2mentioning

confidence: 99%

Contrasting Electricity Demand with Wind Power Supply: Case Study in Hungary

Kiss

Varga²,

Jánosi

2009

Energies

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Abstract:We compare the demand of a large electricity consumer with supply given by wind farms installed at two distant geographic locations. Obviously such situation is rather unrealistic, however our main goal is a quantitative characterization of the intermittency of wind electricity. The consumption pattern consists of marked daily and weekly cycles interrupted by periods of holidays. In contrast, wind electricity production has neither short-time nor seasonal periodicities. We show that wind power integration over a restricted area cannot provide a stable baseload supply, independently of the excess capacity. Further essential result is that the statistics are almost identical for a weekly periodic pattern of consumption and a constant load of the same average value. The length of both adequate supply and shortfall intervals exhibits a scale-free (power-law) frequency distribution, possible consequences are shortly discussed.

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Comparison of wind power estimates from the ECMWF reanalyses with direct turbine measurements

Cited by 30 publications

References 37 publications

Validation of Danish wind time series from a new global renewable energy atlas for energy system analysis

Validation of Danish wind time series from a new global renewable energy atlas for energy system analysis

High-resolution refinement of a storm loss model and estimation of return periods of loss-intensive storms over Germany

Contrasting Electricity Demand with Wind Power Supply: Case Study in Hungary

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