Abstract
The National Center for Atmospheric Research (NCAR) has configured a Wind Power Forecasting System for Xcel Energy that integrates high resolution and ensemble modeling with artificial intelligence methods. This state-of-the-science forecasting system includes specific technologies for short-term detection of wind power ramps, including a Variational Doppler Radar Analysis System and an expert system. This chapter describes this forecasting system and how wind power forecasting can significantly improve grid integration by improving reliability in a manner that can minimize costs. Errors in forecasts become opportunity costs in the energy market; thus, more accurate forecasts have the potential to save substantial amounts of money for the utilities and their ratepayers. As renewable energy expands, it becomes more important to provide high-quality forecasts so that renewable energy can carve out its place in the energy mix.
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