Trend Lines and Japanese Candlesticks Applied to the Forecasting of Wind Speed Data Series

One of the most critical issues for wind energy exploitation is high variability resource, resulting in very difficult forecasting power that farms can grant. A vast literature has therefore been devoted to speed and quantitative forecasting, using different techniques. The widely used statistical learning models are based on a continuation future series’ past behaviour offer performance may be much less satisfactory when values suddenly change their trend. application data two techniques usually employed technical analysis financial series–namely support resistances identification candlestick charts–is investigated here, with main aim detect inversion points series. They applied series locations Spain Italy. proposed indicators confirm usefulness identifying peculiar behaviours system conditions where trend expected change. This additional information offered algorithms also included innovative approaches, e.g., machine learning.