IET Renewable Power Generation · 2013 · 10 citations · 20 references
Natural SciencesEarth SciencesMeteorologyAtmospheric ScienceTime Series AnalysisWeather ForecastingOffshore Wind EnergySeasonal ForecastingTime Series ForecastingWind ForecastingDiurnal Variation CorrectionOffshore Wind StatisticsPower Output ModelingStatistical Wind ForecastingTime Series Forecasting For WindWindWind Power ForecastingWind Resource Meteorology
The authors present a four‐season model representing the aggregate output of a possible British wind fleet circa 2030, suitable for providing synthetic wind time series or a statistical characterisation of the transitional behaviour at timescales of 1 h and above. The model is fitted to an aggregated power output time series derived from historic onshore anemometry data and shown to provide a good fit to both long‐term and transitional statistics. The authors show that the use of a constant factor to extrapolate anemometer‐height wind speeds to hub height leads to an excessive diurnal variation in the implied wind power output. They adjust the model parameters to compensate for this and to account for the offshore component that is not present in the raw data. The complete parameter set is presented.
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Time Series Analysis: Forecasting and Control
Michael D. Geurts, George E. P. Box, Gwilym M. Jenkins · Journal of Marketing Research · 1977 · 19.3K citations
Computing, Data Science, Forecasting +11