Wind Power Forecasting Using Historical Data for Future Time Periods
This project utilizes historical wind power data to forecast future power values through MATLAB programming and Excel data processing. It implements neural network simulation prediction, gray prediction, and time series forecasting methods to identify patterns in historical data for wind power prediction. The forecasted results undergo error analysis and benchmarking against established standards to evaluate prediction reliability, with detailed algorithmic implementations in MATLAB for each method.