کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
243226 501923 2012 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Comparison of two new ARIMA-ANN and ARIMA-Kalman hybrid methods for wind speed prediction
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی مهندسی انرژی و فناوری های برق
پیش نمایش صفحه اول مقاله
Comparison of two new ARIMA-ANN and ARIMA-Kalman hybrid methods for wind speed prediction
چکیده انگلیسی

Wind speed prediction is important to protect the security of wind power integration. The performance of hybrid methods is always better than that of single ones in wind speed prediction. Based on Time Series, Artificial Neural Networks (ANN) and Kalman Filter (KF), in the study two hybrid methods are proposed and their performance is compared. In hybrid ARIMA-ANN model, the ARIMA model is utilized to decide the structure of an ANN model. In hybrid ARIMA-Kalman model, the ARIMA model is employed to initialize the Kalman Measurement and the state equations for a Kalman model. Two cases show both of them have good performance, which can be applied to the non-stationary wind speed prediction in wind power systems.


► A new hybrid ARIMA-ANN model is proposed to forecast wind speed.
► A new hybrid ARIMA-Kalman model is proposed to predict wind speed.
► A detailed comparison of multi-step forecasting performance is provided.
► The two new hybrid models can obtain high-precision multi-step results.
► The two presented models are suitable for non-stationary wind speed.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Energy - Volume 98, October 2012, Pages 415–424
نویسندگان
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