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An Investigation of Wind Direction and Speed in a Featured Wind Farm Using Joint Probability Distribution Methods
Open AccessArticle

Artificial Combined Model Based on Hybrid Nonlinear Neural Network Models and Statistics Linear Models—Research and Application for Wind Speed Forecasting

1
School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000, China
2
Gansu Meteorogical Service Centre, Lanzhou 730020, China
3
School of Statistics, Dongbei University of Finance and Economics, Dalian 116025, China
*
Author to whom correspondence should be addressed.
Sustainability 2018, 10(12), 4601; https://doi.org/10.3390/su10124601
Received: 14 November 2018 / Revised: 29 November 2018 / Accepted: 1 December 2018 / Published: 5 December 2018
(This article belongs to the Special Issue Wind Energy, Load and Price Forecasting towards Sustainability 2019)
The use of wind power is rapidly increasing as an important part of power systems, but because of the intermittent and random nature of wind speed, system operators and researchers urgently need to find more reliable methods to forecast wind speed. Through research, it is found that the time series of wind speed demonstrate not only linear features but also nonlinear features. Hence, a combined forecasting model based on an improved cuckoo search algorithm optimizes weight, and several single models—linear model, hybrid nonlinear neural network, and fuzzy forecasting model—are developed in this paper to provide more trend change for time series of wind speed forecasting besides improving the forecasting accuracy. Furthermore, the effectiveness of the proposed model is proved by wind speed data from four wind farm sites and the results are more reliable and accurate than comparison models. View Full-Text
Keywords: modified cuckoo search algorithm; combined model; hybrid nonlinear models; wind speed forecasting modified cuckoo search algorithm; combined model; hybrid nonlinear models; wind speed forecasting
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Liu, Y.; Zhang, S.; Chen, X.; Wang, J. Artificial Combined Model Based on Hybrid Nonlinear Neural Network Models and Statistics Linear Models—Research and Application for Wind Speed Forecasting. Sustainability 2018, 10, 4601.

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