The 3-hourly gridded ECMWF ERA-Interim climate reanalysis dataset, spanning 1979-2013, was used to investigate the spatial stationarity of the previously documented relationships between wind speeds and the North Atlantic Oscillation (NAO) state in Europe. Over much of western Europe, wind speeds were found to be affected strongly by the concomitant states of the secondary and tertiary atmospheric teleconnections, namely the East Atlantic (EA) and the Scandinavian (SCA) patterns. These modify the geographic positions of the NAO dipole and modulate the influence of the NAO on wind statistics on regional scales, producing non-stationarities in the NAO-wind speed relationships. The interactions of these teleconnections play an important role in modifying wind speeds within Europe. Finally, systematic north-south changes in the Weibull distribution scale and shape parameters are documented along the western margin of Europe, as a function of different states of the NAO, the EA and the SCA. These effects influence both monthly averaged wind speeds and the statistical distributions of 3-hourly wind data, implying strong impacts on wind energy resources and expected wind power production. The results have implications for regional to continent-scale long-term planning of wind-farm siting to minimise the impact of resource intermittency.
To study climate-related aspects of power system operation with large volumes of wind generation, data with sufficiently wide temporal and spatial scope are required. The relative youth of the wind industry means that long-term data from real systems are not available. Here, a detailed aggregated wind power generation model is developed for the Republic of Ireland using MERRA reanalysis wind speed data and verified against measured wind production data for the period 2001-2014. The model is most successful in representing aggregate power output in the middle years of this period, after the total installed capacity had reached around 500MW. Variability on scales of greater than 6 hours is captured well by the model; one additional higher resolution wind dataset was found to improve the representation of higher frequency variability. Finally, the model is used to hindcast hypothetical aggregate wind production over the 34-year period 1980-2013, based on existing installed wind capacity. A relationship is found between several of the production characteristics, including capacity factor, ramping and persistence, and two large-scale atmospheric patterns-the North Atlantic Oscillation and the East Atlantic Pattern.
Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. www.econstor.eu ESRI working papers represent un-refereed work-in-progress by researchers who are solely responsible for the content and any views expressed therein. Any comments on these papers will be welcome and should be sent to the author(s) by email. Papers may be downloaded for personal use only. Terms of use: Documents in The Impact of the North Atlantic Oscillation on Electricity Markets: A Case Study on IrelandJohn Curtis a,b , Muireann Á . Lynch a,b , Laura Zubiate c Abstract: The North Atlantic Oscillation (NAO) is a large-scale circulation pattern driving climate variability in north-western Europe. As the deployment of wind-powered generation expands on electricity networks across Europe the impacts of the NAO on the electricity system will be amplified. This study assesses the impact of NAO, via wind-power generation, on the electricity market considering thermal generation costs, wholesale electricity prices and wind generation subsidies. A Monte Carlo approach is used to model NAO phases and generate hourly wind speed time-series data, electricity demand and fuel input data. A least-cost unit commitment and economic dispatch model is used to simulate an island electricity system, modelled on the all-island Irish electricity system. The impact of NAO obviously depends on the level of wind capacity within an electricity system. Our results indicate that NAO phases can affect thermal generation costs by up to 8%, wholesale electricity prices by as much as €1.5/MWh, and that wind power generators receive on average 12% higher remuneration.
Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. In recent years there has been an increasing deployment of wind-powered generation technology, i.e. wind farms, on electricity networks across Europe. As this deployment increases it is important to understand how climate variability will affect both windpowered and non-renewable power generation. This study extends the literature by assessing the impact of NAO, via wind-power generation, on carbon dioxide emissions from the wider electricity system. A Monte Carlo approach is used to model NAO phases, generate hourly wind speed timeseries data, electricity demand and fuel input data. A unit commitment, least-cost economic dispatch model is used to simulate an entire electricity system, modelled on the all-island Irish electricity system. Our results confirm that the NAO has a significant impact on monthly mean wind speeds, wind power output, and carbon dioxide emissions from the entire electricity system. The impact of NAO on emissions obviously depends on the level of wind penetration within an electricity system but our results indicate that emissions intensity within the Irish electricity system could vary by as much as 10% depending on the NAO phase within the next few years. The emissions intensity of the electricity system will vary with the NAO phase. Terms of use: Documents in
Abstract. The Northeast Atlantic possesses an energetic and variable wind and wave climate which has a large potential for renewable energy extraction; for example along the western seaboards off Ireland. The role of surface winds in the generation of ocean waves means that global atmospheric circulation patterns and wave climate characteristics are inherently connected. In quantifying how the wave and wind climate of this region may change towards the end of the century due to climate change, it is useful to investigate the influence of large scale atmospheric oscillations using indices such as the North Atlantic Oscillation (NAO), the East Atlantic pattern (EA) and the Scandinavian pattern (SCAND). In this study a statistical analysis of these teleconnections was carried out using an ensemble of EC-Earth global climate simulations run under the RCP4.5 and RCP8.5 forcing scenarios, where EC-Earth is a European-developed atmosphere ocean sea-ice coupled climate model. In addition, EC-Earth model fields were used to drive the WAVEWATCH III wave model over the North Atlantic basin to create the highest resolution wave projection dataset currently available for Ireland. Using this dataset we analysed the correlations between teleconnections and significant wave heights (Hs) with a particular focus on extreme ocean states using a range of statistical methods. The strongest, statistically significant correlations exist between the 95th percentile of significant wave height and the NAO. Correlations between extreme Hs and the EA and SCAND are weaker and not statistically significant over parts of the North Atlantic. When the NAO is in its positive phase (NAO+) and the EA and SCAND are in a negative phase (EA−, SCAND−) the strongest effects are seen on 20-year return levels of extreme ocean waves. Under RCP8.5 there are large areas around Ireland where the 20-year return level of Hs increases by the end of the century, despite an overall decreasing trend in mean wind speeds and hence mean Hs.
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