Towards Detecting Motifs in Time Series Data of Wind Energy
نویسندگان
چکیده
The sporadic behavior of wind currently hampers electrical companies from fully utilizing wind energy as a viable resource. Observations of reported wind generation data suggest that there may be diurnal patterns in wind generation. Predicting the magnitude and graphical shape of wind generation at different times during the day would help control room operators to better direct the assignment of power resources throughout the day. We will discuss the use of different methods of pattern detection and analysis to analyze time series data of wind generation from the wind farms in the mid-Columbia River Basin which provide power to the Bonneville Power Administration.
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