A hybrid WFA approach for Short-Term Wind Power Forecasting
نویسنده
چکیده
Wind generation is hectic by nature, making wind power forecasting highly challenging, particularly for short time frames. Forecasting of wind power is becoming progressively more important to power system operators and electricity market.Wind power is variable and irregular over various timescales as it is weather dependent. Thus precise forecasting of wind power is acknowledged as a major contribution for reliable large-scale wind power assimilation. This proposed hybrid model is developed by combining techniques such as Wavelet Transformation (WT), Fireflies (FF) and Adaptive Network-based Fuzzy Inference System (or) Adaptive Neuro Fuzzy Inference System (ANFIS) to calculate wind power. Wind power forecasting is improved by taking advantage of each independent forecasting model.
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