Linear spectropolarimetry of young and other emission line stars

The aim of this article is to demonstrate the useful role that can be played by spectropolarimetric observations of young and evolved emission line stars that analyse the linearly polarized component in their spectra. At the time of writing, this demonstration has to be made on the basis of optical data since there is no common-user infrared facility, in operation, that offers the desired combination of spectral resolution and sensitivity. Here we focus on what can be learned from linear spectropolarimetry alone at reasonably high spectral resolution and at $10^3 <$S/N$< 10^4$. And we remind that the near infrared (1--2 micron) has the potential to out-perform the optical as a domain to work in because of the greatly reduced interstellar obscuration at these wavelengths. This point has been reached at a time when theory, exploiting flexible Monte Carlo methods, is fast becoming a powerful tool. In short we have the complex phenomena, and the rise of the modelling capability to match -- good data are the missing link.Comment: 11 pages, ESO Conference on High Resolution Infrared Spectroscop

Identifying and characterising large ramps in power output of offshore wind farms

Recently there has been a significant change in the distribution of wind farms in Great Britain with the construction of clusters of large offshore wind farms. These clusters can produce large ramping events (i.e. changes in power output) on temporal scales which are critical for managing the power system (30 minute, 60 minute and 4 hours). This study analyses generation data from the Thames Estuary cluster in conjunction with meteorological observations to determine the magnitude and frequency of ramping events and the meteorological mechanism. Over a 4 hour time window, the extreme ramping events of the Thames Estuary cluster were caused by the passage of a cyclone and associated weather fronts. On shorter time scales, the largest ramping events over 30 minute and 60 minute time windows are not associated with the passage of fronts. They are caused by three main meteorological mechanisms; (1) very high wind speeds associated with a cyclone causing turbine cut-out (2) gusts associated with thunderstorms and (3) organised band of convection following a front. Despite clustering offshore capacity, the addition of offshore wind farms has increased the mean separation between capacity and therefore reduced the variability in nationally aggregated generation on high frequency time scales

Observations of wind speed profiles over Greater London, UK, using a Doppler lidar

To calculate the potential wind loading on a tall building in an urban area, an accurate representation of the wind speed profile is required. However, due to a lack of observations, wind engineers typically estimate the characteristics of the urban boundary layer by translating the measurements from a nearby reference rural site. This study presents wind speed profile data obtained from a Doppler lidar in central London, UK, during an 8 month observation period. Used in conjunction with wind speed data measured at a nearby airport, the data have been used to assess the accuracy of the predictions made by the wind engineering tools currently available. When applied to multiple changes in surface roughness identified from morphological parameters, the non-equilibrium wind speed profile model developed by Deaves (1981) provides a good representation of the urban wind speed profile. For heights below 500 m, the predicted wind speed remains within the 95% confidence interval of the measured data. However, when the surface roughness is estimated using land use as a proxy, the model tends to overestimate the wind speed, particularly for very high wind speed periods. These results highlight the importance of a detailed assessment of the nature of the surface when estimating the wind speed above an urban surface

The impact of future offshore wind farms on wind power generation in Great Britain

In the coming years the geographical distribution of wind farms in Great Britain is expected to change significantly. Following the development of the “round 3” wind zones (circa 2025), most of the installed capacity will be located in large offshore wind farms. However, the impact of this change in wind-farm distribution on the characteristics of national wind generation is largely unknown. This study uses a 34-year reanalysis dataset (Modern-Era Retrospective Analysis for Research and Applications (MERRA) from National Aeronautics and Space Administration, Global Modeling and Assimilation Office (NASA-GMAO)) to produce a synthetic hourly time series of GB-aggregated wind generation based on: (1) the “current” wind farm distribution; and (2) a “future” wind farm distribution scenario. The derived data are used to estimate a climatology of extreme wind power events in Great Britain for each wind farm distribution. The impact of the changing wind farm distribution on the wind-power statistics is significant. The annual mean capacity factor increased from 32.7% for the current wind farm distribution to 39.7% for the future distribution. In addition, there are fewer periods of prolonged low generation and more periods of prolonged high generation. Finally, the frequency and magnitude of ramping in the nationally aggregated capacity factor remains largely unchanged. However, due to the increased capacity of the future distribution, in terms of power output, the magnitude of the ramping increases by a factor of 5

Resonance line-profile calculations based on hydrodynamical models of cataclysmic variable winds

We present synthetic line profiles as predicted by the models of 2-D line- driven disk winds due to Proga, Stone & Drew. We compare the model line profiles with HST observations of the cataclysmic variable IX Vel. The model wind consists of a slow outflow that is bounded on the polar side by a fast stream. We find that these two components of the wind produce distinct spectral features. The fast stream produces profiles which show features consistent with observations. These include the appearance of the P-Cygni shape for a range of inclinations, the location of the maximum depth of the absorption component at velocities less than the terminal velocity, and the transition from absorption to emission with increasing inclination. However the model profiles have too little absorption or emission equivalent width. This quantitative difference between our models and observations is not a surprise because the line-driven wind models predict a mass loss rate that is lower than the rate required by the observations. We note that the model profiles exhibit a double-humped structure near the line center which is not echoed in observations. We identify this structure with a non-negligible redshifted absorption which is formed in the slow component of the wind where the rotational velocity dominates over expansion velocity. We conclude that the next generation of disk wind models, developed for application to CVs, needs to yield stronger wind driving out to larger disk radii than do the present models.Comment: LaTeX, 19 pages, to appear in Ap

The importance of forecasting regional wind power ramping: a case study for the UK

In recent years there has been a significant change in the distribution of wind farms in Great Britain, with a trend towards very large offshore farms clustered together in zones. However, there are concerns these clusters could produce large ramping events on time scales of less than 6 hours as local meteorological phenomena simultaneously impact the production of several farms. This paper presents generation data from the wind farms in the Thames Estuary (the largest cluster in the world) for 2014 and quantifies the high frequency power ramps. Based on a case study of a ramping event which occurred on 3rd November 2014, we show that due to the large capacity of the cluster, a localised ramp can have a significant impact on the cost of balancing the power system on a national level if it is not captured by the forecast of the system operator. The planned construction of larger offshore wind zones will exacerbate this problem. Consequently, there is a need for accurate regional wind power forecasts to minimise the costs of managing the system. This study shows that state-of-the-art high resolution forecast models have capacity to provide valuable information to mitigate this impact