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ABSTRACT A probabilistic framework for evaluating changes in offshore wind potential under a changing climate is presented considering three general circulation models ( GCMs), two representative concentration pathways and two statistical downscaling techniques. The analysis was done with respect to three specific locations along the Indian coastline, identified earlier for future offshore energy extraction. The uncertainty among the GCMs was addressed and the choice of an appropriate GCM was made by combining analysis of GCM uncertainty and model reliability. The regional scale wind was derived from the selected GCM using one hard computing method, namely bilinear interpolation and quantile mapping, and one soft method, an artificial neural network. The efficiency of these methods was assessed using certain performance criteria for the historical period and a convergence criterion over the future period. To evaluate wind potential, the GCM output was downscaled from daily to hourly, taking into account the removal of gusts because of long interval averaging. The wind potential for past (1979-2005) and future (2006-2032) time slices was determined using both hard and soft methods as well as two representative concentration pathways. The resulting four outcomes at annual and seasonal scale were compared with the extrapolated trend of past wind potential derived from both GCM and reanalysis data. Finally, the most efficient strategy was evaluated and the actual extractable power was estimated considering a standard power curve. It is concluded that at all the three locations the annual average wind potential will substantially increase, benefitting the offshore industry. [ABSTRACT FROM AUTHOR]

The offshore wind energy is slated to meet world's energy demand significantlyin future. In India three offshore regions along the eastern, southern and western parts of the coastline, namely, Rameshwaram, Kanyakumari and Jakhau, have been identified by the Government of India for offshore wind energy extraction. This is based on the wind power potential assessed with the help of historical data. One of the wind parameters that plays an important role in evaluating the energy resource is the persistence of mean wind, often known through the positive serial correlation in a given wind time series. The persistence observed through historical data however may not remain same in future due to the effect of climate change induced by global warming.In this paper, the wind speed persistence at the above mentioned three locations has been analyzed in the light of climate change. The daily wind speeds for the future time slice of 2006-2032 are derived from the Canadian General Circulation Model: CGCM4run with RCP 4.5 warming scenario. Such projected wind information is compared with the historical wind over the time slice of 1979-2005 and belonging to the ‘CGCM: 20C3M’ model. The GCM data suffer from bias and this is removed using the quantile mapping method. The stationarity test of ‘unit-root’ indicates that the daily wind speed for each stationis stationarity. In order to quantify the persistence at the turbine cut-in speed of 4 m/s, the wind speed duration curve (WSDC) isdrawn. The results demonstrate a decrease in the persistence in future of the order of 3% and 8% at Rameshwaram and Jakhau, respectively and an increase in it by around 3% at Kanyakumari. These trends are further confirmed by the alternate autocorrelation function approach. From the wind persistence point of view alone therefore the power extraction at Kanyakumari may go up in future, which may not be the case with the two other sites.The variances across the three datasets are analyzed using the Levene's test, which showed that the cross-variance across the three locations might decrease in future, but the individual variance at Jakhau might increase and the same at Rameshwaram and Kanyakumari might remain the same in future, not much affecting the energy extraction over the latter two sites. [ABSTRACT FROM AUTHOR]

Abstract: The increasing global warming is most likely to affect the magnitude and pattern of wind at a regional level and such an effect may or not follow the trend predicted at the global scale. Regional level exercises are therefore necessary while making decisions related to engineering infrastructure. In this paper an attempt is made to know the extent of change in design as well as operational wind conditions at two offshore locations along the west coast of India. The design wind speeds with return periods of 10, 50 and 100 years derived for two 30-year time slices in the past and future are compared. In two separate exercises the past and future wind at the local level is simulated by empirical downscaling as well as by interpolation of the general circulation model (GCM) output. Both sets of past and future data are fitted to the Generalized Pareto as well as Weibull distributions using the peak over threshold method to extract long term wind speeds with a specified return. It is noticed that at the given locations the operational and design wind may undergo an increase of around 11%–14% when no downscaling is adopted and 14%–17% when the GCM data are downscaled. Although these figures may suffer from a certain level of statistical uncertainty the study points out to take a relook into the safety margins kept in the design and operation of ocean structures in the light of global warming. [Copyright &y& Elsevier]