Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application

The accuracy of wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. In particular, reliable short-term wind speed forecasting can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However...

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Main Authors: Mingfei Niu, Shaolong Sun, Jie Wu, Yuanlei Zhang
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2015/351354
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spelling doaj-8835ca172e9d454ba27e046119ceefb62020-11-25T00:16:49ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/351354351354Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its ApplicationMingfei Niu0Shaolong Sun1Jie Wu2Yuanlei Zhang3School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000, ChinaSchool of Mathematics and Statistics, Lanzhou University, Lanzhou 730000, ChinaSchool of Mathematics and Statistics, Lanzhou University, Lanzhou 730000, ChinaSchool of Mathematics and Statistics, Lanzhou University, Lanzhou 730000, ChinaThe accuracy of wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. In particular, reliable short-term wind speed forecasting can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, due to the strong stochastic nature and dynamic uncertainty of wind speed, the forecasting of wind speed data using different patterns is difficult. This paper proposes a novel combination bias correcting forecasting method, which includes the combination forecasting method and forecasting bias correcting model. The forecasting result shows that the combination bias correcting forecasting method can more accurately forecast the trend of wind speed and has a good robustness.http://dx.doi.org/10.1155/2015/351354
collection DOAJ
language English
format Article
sources DOAJ
author Mingfei Niu
Shaolong Sun
Jie Wu
Yuanlei Zhang
spellingShingle Mingfei Niu
Shaolong Sun
Jie Wu
Yuanlei Zhang
Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application
Mathematical Problems in Engineering
author_facet Mingfei Niu
Shaolong Sun
Jie Wu
Yuanlei Zhang
author_sort Mingfei Niu
title Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application
title_short Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application
title_full Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application
title_fullStr Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application
title_full_unstemmed Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application
title_sort short-term wind speed hybrid forecasting model based on bias correcting study and its application
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2015-01-01
description The accuracy of wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. In particular, reliable short-term wind speed forecasting can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, due to the strong stochastic nature and dynamic uncertainty of wind speed, the forecasting of wind speed data using different patterns is difficult. This paper proposes a novel combination bias correcting forecasting method, which includes the combination forecasting method and forecasting bias correcting model. The forecasting result shows that the combination bias correcting forecasting method can more accurately forecast the trend of wind speed and has a good robustness.
url http://dx.doi.org/10.1155/2015/351354
work_keys_str_mv AT mingfeiniu shorttermwindspeedhybridforecastingmodelbasedonbiascorrectingstudyanditsapplication
AT shaolongsun shorttermwindspeedhybridforecastingmodelbasedonbiascorrectingstudyanditsapplication
AT jiewu shorttermwindspeedhybridforecastingmodelbasedonbiascorrectingstudyanditsapplication
AT yuanleizhang shorttermwindspeedhybridforecastingmodelbasedonbiascorrectingstudyanditsapplication
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