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A Combined Fuzzy GMDH Neural Network and Grey Wolf Optimization Application for Wind Turbine Power Production Forecasting Considering SCADA Data
2021
Energies
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This paper proposes a combined forecasting model that consists of empirical mode decomposition, fuzzy group method of data handling neural network, and grey wolf optimization algorithm. ...
A combined K-means and identifying density-based local outliers is applied to detect and clean the outliers of the raw supervisory control and data acquisition data in the proposed forecasting model. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/en14123459
fatcat:7te43nbhpbcirb6keez6dj7zje
A Hybrid Wind Speed Forecasting System Based on a 'Decomposition and Ensemble' Strategy and Fuzzy Time Series
2017
Energies
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Therefore, in this paper, a hybrid forecasting system, which combines the 'decomposition and ensemble' strategy and fuzzy time series forecasting algorithm, is proposed that comprises two modules-data ...
Accurate and stable wind speed forecasting is of critical importance in the wind power industry and has measurable influence on power-system management and the stability of market economics. ...
The proposed hybrid system employs the 'decomposition and ensemble' strategy to effectively reduce noise in the wind speed time series signal. ...
doi:10.3390/en10091422
fatcat:j762xwdhazh7pd557p7h5hsulm
A Review on Hybrid Empirical Mode Decomposition Models for Wind Speed and Wind Power Prediction
2019
Energies
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The present review is focused on hybrid empirical mode decomposition (EMD) or ensemble empirical mode decomposition (EEMD) models with their advantages, timely growth and possible future in wind speed ...
However, due to the highly chaotic, intermittent and stochastic behavior of wind, which means a high level of difficulty when predicting wind speed and, consequently, wind power, the evolution of models ...
Neural Networks CEEMD Complete Ensemble Empirical Mode Decomposition CEEMDAN Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Adaptive Neural Network based Fuzzy Interface System
ANN ...
doi:10.3390/en12020254
fatcat:xqzhyrb5hrffrforqeekhm2c4m
Icing Load and Risk Forecasting for Power Transmission Line Based on Multi-scale Time Series Phase-Space Reconstruction and Regression
2021
International Journal of Safety and Security Engineering
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Upon experimentally evaluating the validity of the model using related transmission lines of the Yunnan Power Grid, it is shown that this method could predict the real-time icing load on overhead power ...
Finally, according to the load prediction results, fuzzy reasoning method was used to determine the risk status of transmission line towers in this paper. ...
ACKNOWLEDGMENT This study was supported in part by the National Natural Science Foundation of China (NSFC) (61763049) and the Science and Technology plan of Applied Basic Research Programs key Foundation ...
doi:10.18280/ijsse.110109
fatcat:fbccgfi64ra7tggksidbygpn4u
Related Entropy Theories Application in Condition Monitoring of Rotating Machineries
2019
Entropy
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Rotating machinery plays an important role in various kinds of industrial engineering. How to assess their conditions is a key problem for operating safety and condition-based maintenance. ...
Among the available methods of analyzing sensors data, entropy and its variants can provide quantitative information contained in these sensing data. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/e21111061
fatcat:zz7ii3sd6faxfnc5lll34rs2j4
A Comparative Study of Groundwater Level Forecasting Using Data-Driven Models Based on Ensemble Empirical Mode Decomposition
2018
Water
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(i.e., artificial neural networks (ANN), support vector machines (SVM) and adaptive neuro fuzzy inference systems (ANFIS)), respectively. ...
Three nonlinear time-series intelligence hybrid models were proposed to predict groundwater level fluctuations through a combination of ensemble empirical mode decomposition (EEMD) and data-driven models ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/w10060730
fatcat:qkrxe46pfjg6nlqtscax56st3a
Comprehensive Overview on Computational Intelligence Techniques for Machinery Condition Monitoring and Fault Diagnosis
2017
Chinese Journal of Mechanical Engineering
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Computational intelligence is one of the most powerful data processing tools to solve complex nonlinear problems, and thus plays a significant role in intelligent fault diagnosis and prediction. ...
The characteristics of different algorithms are compared, and application situations of these methods are summarized. ...
This method is based on fuzzy mathematics theory, including the appropriate membership and fuzzy rules; then, fuzzy inference is continued to implement fuzzy prediction. ...
doi:10.1007/s10033-017-0150-0
fatcat:7e7qq3xewzhqtdvb2np6q3ftv4
Multi-Step Wind Speed Forecasting Based On Ensemble Empirical Mode Decomposition, Long Short Term Memory Network and Error Correction Strategy
2019
Energies
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The calculation outcomes reveal that: (1) the EEMD is able to boost the wind speed prediction capacity and robustness of the LSTM approach effectively; (2) the BSO based parameter optimization method is ...
It is of great significance for wind power plant to construct an accurate multi-step wind speed prediction model, especially considering its operations and grid integration. ...
Therefore, it is imperative to propose an accurate prediction method for wind speed to reduce the instability risk of the power system and the economic losses for wind power enterprises. (3) Hybrid models ...
doi:10.3390/en12101822
fatcat:ggzsullxlvhqpheabjxf75phyy
Machine Learning Techniques for Supporting Renewable Energy Generation and Integration: A Survey
[chapter]
2014
Lecture Notes in Computer Science
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The current pace of technological development makes it commercially viable to harness energy from sun, wind, geothermal and many other renewable sources. ...
Because of the negative effects on the environment and the economy, conventional energy sources like natural gas, crude oil and coal are coming under political and economic pressure. ...
The subjective fuzzy model of the system was designed based on prior expert knowledge of the system. ...
doi:10.1007/978-3-319-13290-7_7
fatcat:ean3a774wrfq5oq7bvr5lofyiq
A review on wind turbines gearbox fault diagnosis methods
2021
Journal of Vibroengineering
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This paper reviewed some research results of faults diagnosis on wind turbines gearbox, such as time-frequency analysis method, vibration based methods, nondestructive testing methods, etc. ...
The gearbox, as the kernel component of the wind turbine system, it's robust conditions have a great influence on the whole wind turbines system. ...
BK20201463), the 333 Project of Jiangsu Province of China (2016-III-2808), the Qing-Lan Project of Jiangsu Province of China (QL2016013). Dr. Wenyi Liu is the corresponding author. ...
doi:10.21595/jve.2020.20178
fatcat:oebg5epv3reu3il7wqoqyzzfdu
Research and Application Based on Adaptive Boosting Strategy and Modified CGFPA Algorithm: A Case Study for Wind Speed Forecasting
2016
Sustainability
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Wind speed decomposition, which could decrease the non-stationary feature of the original wind speed data ...
With the development of artificial techniques, some artificial intelligent prediction methods have been mushrooming, including Artificial Neural Networks [21] [22] [23] [24] [25] [26] [27] , fuzzy logic ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/su8030235
fatcat:jl6phthqbrbjhbkax4x75atfyu
An ensemble approach based on transformation functions for natural gas price forecasting considering optimal time delays
2021
PeerJ Computer Science
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The wavelet decomposition and fuzzy transform have been integrated into the preprocessing stage. An ensemble method is used for integrating the outputs of various neural networks. ...
First, optimal time delays are identified by a new approach based on the Euclidean Distance between input and target vectors. Then, wavelet decomposition has been implemented to reduce noise. ...
Also, they examined the effects of wind direction and wind speed on the accuracy of prediction results. ...
doi:10.7717/peerj-cs.409
pmid:33954228
pmcid:PMC8049131
fatcat:vmk5aiyvxvaxhgsvefpne76hqu
A Newly Developed Integrative Bio-Inspired Artificial Intelligence Model for Wind Speed Prediction
2020
IEEE Access
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Novel WS prediction models based on the multivariate empirical mode decomposition (MEMD), random forest (RF) and Kernel Ridge Regression (KRR) were constructed in this paper better accuracy in WS prediction ...
Accurate wind speed (WS) modelling is crucial for optimal utilization of wind energy. ...
There are several versions of these intelligent models, including adaptive neural fuzzy inference system, support vector machine, artificial neural network, etc. ...
doi:10.1109/access.2020.2990439
fatcat:j4wpi32sv5bazkcr2uqjxy62tq
A Hybrid Model Based on a Two-Layer Decomposition Approach and an Optimized Neural Network for Chaotic Time Series Prediction
2019
Symmetry
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The experimental results indicate that the two-layer decomposition approach is superior to other competing approaches in terms of four evaluation indexes in one-step and multi-step ahead predictions. ...
In this paper, we put forward a novel hybrid model based on a two-layer decomposition approach and an optimized back propagation neural network (BPNN). ...
Funding: This work was supported by the National Natural Science Foundation of China (61773087).
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/sym11050610
fatcat:dlxglhyezjcbvixafzhkavzkxi
Short-Term Wind Speed Forecasting Using Decomposition-Based Neural Networks Combining Abnormal Detection Method
2014
Abstract and Applied Analysis
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This paper contributes to short-term wind speed forecasting by developing two three-stage hybrid approaches; both are combinations of the five-three-Hanning (53H) weighted average smoothing method, ensemble ...
In particular, short-term wind speed forecasting, an essential support for the regulatory actions and short-term load dispatching planning during the operation of wind farms, is currently regarded as one ...
Acknowledgments This work was supported by the R&D Special Fund for Public Welfare Industry (meteorology) (GYHY201206013) and the Gansu Provincial Meteorological Service Center Innovation Fund (2013-10 ...
doi:10.1155/2014/984268
fatcat:hqb65cjbrjgzvjpbs7ovzvorzi
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