Abstract
Harvesting wind energy resources is a major part of the UK strategy to diversify the power supply portfolio and mitigate environmental degradation. Based on wind speed data for the period 1981–2018, collected at 38 surface observation stations, this study presents a comprehensive assessment of wind speed characteristics by means of statistical analysis using the Weibull distribution function. The estimated Weibull parameters are used to evaluate wind power density at both station and regional levels and important, turbine-specific wind energy assessment parameters. It is shown that the Weibull distribution function provides satisfactory modeling of the probability distribution of daily mean wind speeds, with the correlation coefficient generally exceeding 0.9. Site-to-site variability in wind power density and other essential parameters is apparent. The Weibull scale parameter lies in the range between 4.96 m/s and 12.06 m/s, and the shape parameter ranges from 1.63 to 2.97. The estimated wind power density ranges from 125 W/m2 to 1407 W/m2. Statistically significant long-term trends in annual mean wind speed are identified for only 15 of the 38 stations and three of the 11 geographical regions. The seasonal variability of Weibull parameters and wind power density is confirmed and discussed.
Highlights
Harvesting renewable energy resource represents one of a range of strategies to reduce carbon dioxide emission and decelerate environment degradation
Notable among the increase in the use of renewable energy technologies is the rapid increase in the use of 33 wind energy, with worldwide installation of new wind power generation exceeding 60 34 GW in 2019, a 19% increase compared to 2018, leading to a total installation capacity 35 of approximately 650 GW [2]
Accurate understanding of wind speed characteristics is imperative in different aspects of wind energy development, ranging from identification of desirable sites to prediction of the economic viability of wind farm to structural design of wind turbines
Summary
Harvesting renewable energy resource represents one of a range of strategies to reduce carbon dioxide emission and decelerate environment degradation. The accumulated installation of renewable energy was sufficient to provide an estimate of 27.3% of global electricity generation at the end of 2019 [1]. Notable among the increase in the use of renewable energy technologies is the rapid increase in the use of 33 wind energy, with worldwide installation of new wind power generation exceeding 60 34 GW in 2019, a 19% increase compared to 2018, leading to a total installation capacity 35 of approximately 650 GW [2]. The wind power resources in the UK are significant on a national scale [3][4], and wind power development in the UK has met a rapid growth, with the cumulative total installation capacity increased from 5.2GW in 2010 to 23.9GW in 2019 [5][6]. Accurate understanding of wind speed characteristics is imperative in different aspects of wind energy development, ranging from identification of desirable sites to prediction of the economic viability of wind farm to structural design of wind turbines
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