Abstract
Currently, the quality of available wind energy at a site is assessed using wind power density (WPD). This paper proposes to use a more comprehensive metric: the wind power potential (WPP). While the former accounts for only wind speed information, the latter exploits the joint distribution of wind speed and wind direction and yields more credible estimates. The WPP investigates the effect of wind velocity distribution on the optimal net power generation of a farm. A joint distribution of wind speed and direction is used to characterize the stochastic variation of wind conditions. Two joint distribution methods are adopted in this paper: bivariate normal distribution and anisotropic lognormal method. The net power generation for a particular farmland size and installed capacity is maximized for different distributions of wind speed and wind direction, using the Unrestricted Wind Farm Layout Optimization (UWFLO) framework. A response surface is constructed to represent the computed maximum wind farm capacity factor as a function of the parameters of the wind distribution. Two different response surface methods are adopted in this paper: (i) the adaptive hybrid functions (AHF), and (ii) the quadratic response surface method (QRSM). Toward this end, for any farm site, we can (i) estimate the parameters of the joint distribution using recorded wind data (for bivariate normal or anisotropic lognormal distributions) and (ii) predict the maximum capacity factor for a specified farm size and capacity using this response surface. The WPP metric is illustrated using recorded wind data at four differing stations in the state of North Dakota. The results illustrate the variation of wind conditions and, subsequently, its influence on the quality of wind resources. A comparison of four sites in North Dakota shows that WPD and WPP follow different trends, and the ranking of candidate sites in terms of a realistic resource potential measure is not captured by WPD.
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