Time Series Models to Simulate and Forecast Wind Speed and Wind Power
Open Access
- 1 August 1984
- journal article
- Published by American Meteorological Society in Journal of Climate and Applied Meteorology
- Vol. 23 (8) , 1184-1195
- https://doi.org/10.1175/1520-0450(1984)023<1184:tsmtsa>2.0.co;2
Abstract
A general approach for modeling wind speed and wind power is described. Because wind power is a function of wind speed, the methodology is based on the development of a model of wind speed. Values of wind power are estimated by applying the appropriate transformations to values of wind speed. The wind speed modeling approach takes into account several basic features of wind speed data, including autocorrelation, non-Gaussian distribution, and diurnal nonstationarity. The positive correlation between consecutive wind speed observations is taken into account by fitting an autoregressive process to wind speed data transformed to make their distribution approximately Gaussian and standardized to remove diurnal nonstationarity. As an example, the modeling approach is applied to a small set of hourly wind speed data from the Pacific Northwest. Use of the methodology for simulating and forecasting wind speed and wind power is discussed and an illustration of each of these types of applications is presen... Abstract A general approach for modeling wind speed and wind power is described. Because wind power is a function of wind speed, the methodology is based on the development of a model of wind speed. Values of wind power are estimated by applying the appropriate transformations to values of wind speed. The wind speed modeling approach takes into account several basic features of wind speed data, including autocorrelation, non-Gaussian distribution, and diurnal nonstationarity. The positive correlation between consecutive wind speed observations is taken into account by fitting an autoregressive process to wind speed data transformed to make their distribution approximately Gaussian and standardized to remove diurnal nonstationarity. As an example, the modeling approach is applied to a small set of hourly wind speed data from the Pacific Northwest. Use of the methodology for simulating and forecasting wind speed and wind power is discussed and an illustration of each of these types of applications is presen...Keywords
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