Forecasting models for wind speed using wavelet, wavelet packet, time series and Artificial Neural Networks
Applied EnergyPublished 16 March 2013
Hui Liu, Hong-qi Tian, Di-fu Pan, Yan-fei Li
Citations333
SJR quartileQ1
SJR score2.90
SNIP2.51
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
The results of three experimental cases show that the proposed three hybrid models have satisfactory performance in the wind speed predictions, and the Wavelet Packet-ANN model is the best among them.
Abstract
Wind speed forecasting is important for the security of wind power integration. Based on the theories of wavelet, wavelet packet, time series analysis and artificial neural networks, three hybrid models [Wavelet Packet-BFGS, Wavelet Packet-ARIMA-BFGS and Wavelet-BFGS] are proposed to predict the wind speed. The presented models are compared with some other classical wind speed forecasting methods including Neuro-Fuzzy, ANFIS (Adaptive Neuro-Fuzzy Inference Systems), Wavelet Packet-RBF (Radial Basis Function) and PM (Persistent Model). The results of three experimental cases show that: (1) the proposed three hybrid models have satisfactory performance in the wind speed predictions, and (2) the Wavelet Packet-ANN model is the best among them.
Keywords
EnergyEngineering
IEEE Transactions on Pattern Analysis and Machine IntelligenceA theory for multiresolution signal decomposition: the wavelet representation
21,081 Citations1989Stéphane Mallat
It is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2/Sup j/ can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
IEEE Transactions on Systems Man and CyberneticsANFIS: adaptive-network-based fuzzy inference system
16,152 Citations1993Jyh‐Shing Roger Jang
The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy inference system) is presented, which is a fuzzy inference System implemented in the framework of adaptive networks.
IEEE International Conference on Neural NetworksA direct adaptive method for faster backpropagation learning: the RPROP algorithm
3,927 Citations2002Martin Riedmiller, Heinrich Braun
A learning algorithm for multilayer feedforward networks, RPROP (resilient propagation), is proposed that performs a local adaptation of the weight-updates according to the behavior of the error function to overcome the inherent disadvantages of pure gradient-descent.
Applied EnergyARMA based approaches for forecasting the tuple of wind speed and direction
906 Citations2010Ergin Erdem, Jing Shi
A review of wind power and wind speed forecasting methods with different time horizons
858 Citations2010Saurabh S. Soman, Hamidreza Zareipour +2 more
Renewable EnergyMulti-step forecasting for wind speed using a modified EMD-based artificial neural network model
522 Citations2011Zhenhai Guo, Weigang Zhao +2 more
The developed model shows the best accuracy comparing with basic FNN and unmodified EMD-based FNN through multi-step forecasting the mean monthly and daily wind speed in Zhangye of China.
Applied EnergyWind speed and wind energy forecast through Kalman filtering of Numerical Weather Prediction model output
520 Citations2012Federico Cassola, Massimiliano Burlando
Applied EnergyComparison of two new ARIMA-ANN and ARIMA-Kalman hybrid methods for wind speed prediction
394 Citations2012Hui Liu, Hong-qi Tian +1 more
Energy Conversion and ManagementFine tuning support vector machines for short-term wind speed forecasting
390 Citations2011Junyi Zhou, Jing Shi +1 more
For the first time, a systematic study on fine tuning of LS-SVM model parameters for one-step ahead wind speed forecasting is presented and it is found that they can outperform the persistence model in the majority of cases.
IEEE Transactions on Sustainable EnergyAWNN-Assisted Wind Power Forecasting Using Feed-Forward Neural Network
378 Citations2012K. Ramakrishnan Bhaskar, S. N. Singh
The effectiveness of the proposed method is compared with persistence (PER) and new-reference (NR) benchmark models and the results show that the proposed model outperforms the benchmark models.
IEEE Transactions on Power SystemsDay-Ahead Price Forecasting of Electricity Markets by a New Fuzzy Neural Network
371 Citations2006Nima Amjady
An efficient method based on a new fuzzy neural network has inter-layer and feed-forward architecture with a new hypercubic training mechanism for short-term price forecasting of electricity markets and can provide more accurate results than other price forecasting techniques.
Renewable EnergyA comparison of various forecasting techniques applied to mean hourly wind speed time series
365 Citations2000Athanasios Sfetsos
A comparison of various forecasting approaches, using time series analysis, on mean hourly wind speed data, including the traditional linear (ARMA) models and the commonly used feed forward and recurrent neural networks is presented.
Knowledge-Based SystemsA case study on a hybrid wind speed forecasting method using BP neural network
355 Citations2011Zhenhai Guo, Jie Wu +2 more
This paper proposes a new hybrid wind speed forecasting method based on a back-propagation (BP) neural network and the idea of eliminating seasonal effects from actual wind speed datasets using seasonal exponential adjustment that can forecast the daily average wind speed one year ahead with lower mean absolute errors.
Annual Reviews in ControlNeuro-fuzzy methods for nonlinear system identification
314 Citations2003Robert Babuška, H.B. Verbruggen
An overview of neuro-fuzzy modeling methods for nonlinear system identification is given, with an emphasis on the tradeoff between accuracy and interpretability.
Renewable and Sustainable Energy ReviewsEvaluation of hybrid forecasting approaches for wind speed and power generation time series
272 Citations2012Jing Shi, Jinmei Guo +1 more
The results show that the hybrid approaches are viable options for forecasting both wind speed and wind power generation time series, but they do not always produce superior forecasting performance for all the forecasting time horizons investigated.
European Journal of Operational ResearchForecasting wind speed with recurrent neural networks
261 Citations2012Qing Cao, Bradley T. Ewing +1 more
This research presents a comparative analysis of the wind speed forecasting accuracy of univariate and multivariate ARIMA models with their recurrent neural network counterparts and indicates that multivariate models perform better than univariate models and that the recurrent Neural network models outperform the AR IMA models.
IEEE Transactions on Sustainable EnergyWind Power Prediction by a New Forecast Engine Composed of Modified Hybrid Neural Network and Enhanced Particle Swarm Optimization
223 Citations2011Nima Amjady, Farshid Keynia +1 more
This paper proposes a wind power forecasting strategy composed of a feature selection component and a forecasting engine that applies an irrelevancy filter and a redundancy filter to the set of candidate inputs.
Renewable EnergyData mining and wind power prediction: A literature review
218 Citations2012İlhami Çolak, Şeref Sağıroğlu +1 more
It is shown that adaptive neuro-fuzzy inference systems, neural networks and multilayer perceptrons give better results in wind power predictions.
Expert Systems with ApplicationsShort term wind speed prediction based on evolutionary support vector regression algorithms
217 Citations2010Sancho Salcedo‐Sanz, Emilio G. Ortiz-Garcı ́a +3 more
This paper discusses the application of two different evolutionary computation techniques to tackle the hyper-parameters estimation problem in SVMrs and tests an Evolutionary Programming algorithm (EP) and a Particle Swarm Optimization approach (PSO).
Applied EnergyComprehensive evaluation of ARMA–GARCH(-M) approaches for modeling the mean and volatility of wind speed
209 Citations2010Heping Liu, Ergin Erdem +1 more
The results show that the ARMA-GARCH(-M) approaches can effectively catch the trend change of the mean and volatility of wind speed and confirm that for any wind speed dataset, the potential models should be evaluated to find the most appropriate one for the highest modeling sufficiency.
Applied EnergyEstimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS)
209 Citations2011Mohamed Mohandes, Shafiqur Rehman +1 more
Energy Conversion and ManagementNeural networks approach to forecast several hour ahead electricity prices and loads in deregulated market
204 Citations2006Paras Mandal, Tomonobu Senjyu +1 more
An approach for several hour ahead electricity price and load forecasting using an artificial intelligence method, such as a neural network model, which uses publicly available data from the NEMMCO web site to forecast electricity prices and loads for the Victorian electricity market is introduced.
IEEE Transactions on Sustainable EnergyApplication of Auto-Regressive Models to U.K. Wind Speed Data for Power System Impact Studies
186 Citations2011David Hill, David McMillan +2 more
Energy Conversion and ManagementVery short-term wind speed prediction: A new artificial neural network–Markov chain model
184 Citations2010S.A. Pourmousavi Kani, M.M. Ardehali
It is found that the prediction errors can be decreased, while the uncertainty of the predictions and calculation time are reduced.
EnergyAssessment of the benefits of numerical weather predictions in wind power forecasting based on statistical methods
158 Citations2011Maria Grazia De Giorgi, Antonio Ficarella +1 more
Several forecast systems have been developed to predict power production of a wind farm located in a complex terrain, where geographical effects make wind speed predictions difficult) in different time horizons: 1,3,6,12 and 24 h.
Renewable EnergyVery short-term wind speed forecasting with Bayesian structural break model
151 Citations2012Yu Jiang, Zhe Song +1 more
Electric Power Systems ResearchShort-term wind power forecasting using ridgelet neural network
128 Citations2011Nima Amjady, Farshid Keynia +1 more
A new prediction strategy is proposed for forecasting of both wind power output of wind farms and aggregated wind generation of power systems using a ridgelet neural network (RNN) owning ridge functions as the activation functions of its hidden nodes.
EnergyPrediction of wind speed time series using modified Taylor Kriging method
109 Citations2010Heping Liu, Jing Shi +1 more
Applied EnergyMultiple architecture system for wind speed prediction
108 Citations2011Hassen Bouzgou, Nabil Benoudjit
The experimental results point out that the proposed MAS approach is capable of improving the precision of the wind speed prediction compared to the traditional prediction methods.
Renewable and Sustainable Energy ReviewsA new strategy for predicting short-term wind speed using soft computing models
91 Citations2012Ashraf Ul Haque, Paras Mandal +4 more
A performance analysis of short-term wind speed prediction techniques based on soft computing models formulated on a backpropagation neural network, a radial basis function neural network (RBFNN), and an adaptive neuro-fuzzy inference system (ANFIS) shows that all evaluated SCMs incur some level of performance improvement with the addition of SD pre-processing.
Renewable and Sustainable Energy ReviewsDevelopment of offshore wind power in China
88 Citations2011Jinjin Chen
International Journal of Green EnergyShort-Term Wind Power Generation Forecasting: Direct Versus Indirect Arima-Based Approaches
88 Citations2011Jing Shi, Xiuli Qu +1 more
Applied EnergyPerformance analysis of four modified approaches for wind speed forecasting
53 Citations2012Wenyu Zhang, Jie Wu +3 more
IEEE Transactions on Industry ApplicationsAn Effort to Optimize Similar Days Parameters for ANN-Based Electricity Price Forecasting
50 Citations2009Paras Mandal, Anurag K. Srivastava +1 more
Applied EnergyAn integrated control method for a wind farm to reduce frequency deviations in a small power system
49 Citations2010Toshiaki Kaneko, Akie Uehara +3 more
Digital Signal ProcessingConvolution wavelet packet transform and its applications to signal processing
46 Citations2010Xuezhi Zhao, YE Bang-yan
Based on the length invariance property of convolution WPT, a noise reduction algorithm is proposed, and signal processing example shows that its denoising performance is better than that of traditional W PT, and also much betterthan that of wavelet transform.
European Transactions on Electrical PowerA new hybrid iterative method for short-term wind speed forecasting
43 Citations2010Nima Amjady, Farshid Keynia +1 more
IEEE Transactions on Plasma ScienceFeedforward Neural Network Trained by BFGS Algorithm for Modeling Plasma Etching of Silicon Carbide
36 Citations2010Jinghua Xia, Rusli Rusli +1 more
The silicon carbide ECR process modeling results demonstrate that the FNN trained by the BFGS algorithm are fast, reliable, and accurate.
International Journal of Sustainable EnergyAdaptive neuro-fuzzy short-term wind-speed forecasting for Egypt's East-Coast
13 Citations2011Omar M. Salim, Mohammed Zohdy +2 more
Five different adaptive neuro-fuzzy wind predictors are proposed and compared to forecast the speed of wind blowing in the East Coast of Egypt, a very promising location to generate more than 20 GW of wind power.
Convergence analysis of the Quickprop method
12 Citations2003Michael N. Vrahatis, George D. Magoulas +1 more
Modifications of the algorithm are presented that exhibit improved convergence speed and stability and at the same time, alleviate the use of heuristic learning parameters.