Wind Power and Electric Load Forecasting
نویسندگان
چکیده
As renewable energy increasingly integrates into the electric power system, electric load forecasting and renewable energy power generation forecasting become more important. In this project, ARIMA and NARX are applied to build load forecasting model focusing on improving statistical and computational efficiency without losing accuracy. ARIMA turns out to be better for short term forecasting while NARX is more stable and efficient. Meanwhile, forecasting power generation by wind farm is implemented by using a hybrid k nearest neighbors and least square boosting algorithm. A supply shortage measured by the difference between load and generation is forecasted with a 95% confidence that the error is less than 24.73%.
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