A Literature Review of Wind Forecasting Methods

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Journal of Power and Energy Engineering

ISSN Print: 2327-588X
ISSN Online: 2327-5901
www.scirp.org/journal/jpee
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"A Literature Review of Wind Forecasting Methods"
written by Wen-Yeau Chang,
published by Journal of Power and Energy Engineering, Vol.2 No.4, 2014

has been cited by the following article(s):

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[12]	Wind power forecasting technologies: A review
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[14]	Forecasting of Wind Power Using Hybrid Machine Learning Approach
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[15]	Integración óptima de recursos energéticos distribuidos en redes eléctricas de distribución para la mejora de sus condiciones operativas, técnicas y económicas
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[16]	Improving Predictability of Wind Power Generation
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[17]	Wind Power Prediction Using Hybrid ELM Algorithm.
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[18]	Wind Power Prediction Using Artificial Neural Network Model: A Case Study
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[19]	DEVELOPING WIND POWER FORECASTING MODEL USING DEEP LEARNING APPROACH-A CASE OF ADAMA WIND FARM
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[20]	Comparison and Enhancement of Machine Learning Algorithms for Wind Turbine Output Prediction with Insufficient Data
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[21]	Cost and energy efficiency study of an ARIMA forecast model using HOMER pro
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[22]	Synthesis of Solar Production and Energy Demand Profiles Using Markov Chains for Microgrid Design
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[23]	GCNInformer: A combined deep learning model based on GCN and Informer for wind power forecasting
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[28]	Wind power forecasting model based on linguistic fuzzy rules
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[31]	Multimodality-based Wind Speed Forecasting Method for the Wind Resistance Control of Large Radio Telescope
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[32]	Comparison of Statistical Production Models for a Solar and a Wind Power Plant
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[33]	Artificial Intelligence Methods Applied To Wind And Solar Energy Forecasting: A Comparative Study of Current Techniques
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[35]	Wind Speed Forecasting using Hybrid Model of CNN and LSTM with Wavelets
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[36]	Empirical mode decomposition of wind speed signals
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[37]	DEEP ENSEMBLES APPROACH FOR ENERGY FORECASTING
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[38]	Wind Speed Prediction Using Machine Learning Algorithms: A Case Study of Using ANFIS and KNNR
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[39]	Markov Chains Based Generation of Energy Demand and Solar Production Profiles for the Design and Operation of Microgrids
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[40]	Economic Aspects of Market-based Flexibility for Electricity Networks
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[41]	Wind Power Forecasting Model Using Deep Learning Approach
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[42]	Machine Learning Approach to Wind Speed Prediction using Soft Computing Tools
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[43]	Data Markets for Collaborative Forecasting in the Energy Sector
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[44]	Enhancing Long-Term Wind Power Forecasting by Using an Intelligent Statistical Treatment for Wind Resource Data
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[45]	Forecasting of short-term and long-term wind speed of ras gharib using time series analysis
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[46]	Pricing Wind Power Uncertainty in the Electricity Market
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[47]	Review of key technologies for offshore floating wind power generation
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[49]	A Comprehensive Review on Machine Learning Techniques for Forecasting Wind Flow Pattern
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[50]	Comprehensive review based on the impact of integrating electric vehicle and renewable energy sources to the grid
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[51]	A novel hybrid deep learning model for multi-step wind speed forecasting considering pairwise dependencies among multiple atmospheric variables
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[52]	Review of Estimating and Predicting Models of the Wind Energy Amount
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[53]	A survey of long short term memory and its associated models in sustainable wind energy predictive analytics
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[54]	A review on modeling variable renewable energy: complementarity and spatial–temporal dependence
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[55]	A novel approach to ultra-short-term wind power prediction based on feature engineering and informer
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[56]	New ridge regression, artificial neural networks and support vector machine for wind speed prediction
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[60]	Deep Learning Approach for Wind Power Forecasting
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[61]	Wind Speed Forecast based on Combined Theory, Multi-objective Optimisation, and Sub-model Selection
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[62]	Univariate and Multivariate Regression Models for Short-Term Wind Energy Forecasting
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[63]	Research Article An Approach for Demand Forecasting in Steel Industries Using Ensemble Learning
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[64]	Wind energy prediction
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[65]	Wind Speed Prediction from Site Meteorological Data Using Artificial Neural Network
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[66]	Error Evaluation of Short-Term Wind Power Forecasting Models
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[67]	Wind power forecasting in distribution networks using non-parametric models and regression trees
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[68]	A Review on Wind Power Forecasting Regarding Impacts on the System Operation, Technical Challenges, and Applications
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[69]	Wind Power Forecasting with Deep Learning: Team didadida_hualahuala
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[70]	IoT Based Real-Time Monitoring of Meteorological Data: A Review
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[71]	Development of a Multi-Hour Ahead Wind Power Forecasting System
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[72]	Advances in Wind Power Modeling: Merging Research and Market Experience
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[73]	Study on Integration of Electric Vehicle with Wind Energy
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[74]	Aplicación de modelos de difusión y de series temporales para pronóstico de demanda agregada
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[75]	Application Of Artificial Intelligence In Generation Power Forecast Of Wind And Solar Power Plant
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[76]	III. 5.3. Method to obtain adequate wind power according to its control to reduce the frequency deviation in isolated power systems with high wind power …
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[77]	A Wind Power Prediction Method Based on DE-BP Neural Network. Front
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[78]	Regression model for predicting the speed of wind flows for energy needs based on fuzzy logic
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[79]	A novel stochastic model for very short-term wind speed forecasting in the determination of wind energy potential of a region: A case study from Turkey
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[80]	A review of short‐term wind power probabilistic forecasting and a taxonomy focused on input data
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[82]	A New Framework for Assessment of Offshore Wind Farm Location
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[83]	Power Forecasting of Regional Wind Farms via Variational Auto-Encoder and Deep Hybrid Transfer Learning
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[84]	An approach for demand forecasting in steel industries using ensemble learning
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[85]	Short-term wind speed forecasting over complex terrain using linear regression models and multivariable LSTM and NARX networks in the Andes Mountains, Ecuador
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[86]	Exploiting more robust and efficacious deep learning techniques for modeling wind power with speed
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[87]	Seasonal and subseasonal wind power characterization and forecasting for the Iberian Peninsula and the Canary Islands: A systematic review
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[88]	A comprehensive review on deep learning approaches in wind forecasting applications
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[89]	A multi-strategy random weighted gray wolf optimizer-based multi-layer perceptron model for short-term wind speed forecasting
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[90]	Incorporating spatial and temporal correlations to improve aggregation of decentralized day-ahead wind power forecasts
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[91]	Expectation-Based Probabilistic Naive Approach for Forecasting Involving Optimized Parameter Estimation
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[92]	Estimation of wind turbine output power using soft computing models
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[93]	Solar radiation forecasting using random forest
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[94]	Trend triplet based data clustering for eliminating nonlinear trend components of wind time series to improve the performance of statistical forecasting models
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[95]	Trend Lines and Japanese Candlesticks Applied to the Forecasting of Wind Speed Data Series
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[96]	Spatio-Temporal Wind Speed Forecasting using Graph Networks and Novel Transformer Architectures
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[97]	A hybrid regression based forecasting model for estimating the cost of wind energy production
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[98]	Machine Intelligent Hybrid Methods Based on Kalman Filter and Wavelet Transform for Short-Term Wind Speed Prediction
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[99]	Optimal location and sizing of distributed generators and energy storage systems in microgrids: A review
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[100]	A Hybrid Forecasting Model Based on CNN and Informer for Short-Term Wind Power
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[101]	A new approach to wind turbine power generation forecasting, using weather radar data based on Hidden Markov Model
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[102]	Pronostico numérico a corto plazo de la rapidez del viento para los parques eólicos de Gibara I y II
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[104]	A wind power prediction method based on DE-BP neural network
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[105]	Short-Term Wind Energy Forecasting Using Deep Learning-Based Predictive Analytics
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[107]	From Wind to Wave energy resource: forecasting methods analysis
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[108]	Energy Reports
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[109]	Characterizing variable renewable energy generation uncertainty towards improved forecasting and operational decision making
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[110]	Sub-optimum day-ahead power dispatch for a mixed generation system considering emission and energy storage for semi-liberalized power market
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[111]	Machine Intelligent Hybrid Methods Based on Kalman Filter and Wavelet Transform for Short-Term Wind Speed Prediction. Wind 2022, 2, 37–50
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[112]	Discover Energy
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[113]	Analysis of sea waves data for the Maltese Islands
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[114]	Abordagem auto-adaptativa baseada no conceito de expectativa de vida aplicada aos métodos Particle Swarm Optimization e máquinas kernel para previsão da …
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[115]	PREDIKSI KEBUTUHAN PLTS DAN PLTB BERBASIS JARINGAN SARAF TIRUAN
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[116]	SHORT-TERM WIND SPEED FORECASTING USING MACHINE LEARNING
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[117]	Wind Energy Analysis and Forecast using Machine Learning
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[118]	Questions théoriques et applications pratiques en apprentissage statistique et statistique non paramétrique
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[119]	A Survey on ML Models of Wind Energy Forecasting
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[120]	Investigation of Advanced Machine Learning Methods for Wind Power Prediction
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[121]	Aplicação Híbrida com Redes Neurais Profundas e Algoritmo Genético para Previsão de Séries Temporais do Sistema de Energia Elétrica Brasileira
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[122]	Artificial intelligence‐based wind forecasting using variational mode decomposition.
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[123]	Mathematical Modelling of Engineering Problems
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[124]	Long term wind energy estimation using adaptive boosting ensemble learning model
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[125]	Net load forecasting model for a power system grid with wind and solar power penetration
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[126]	Short-Term Wind Power Forecasting Using Mixed Input Feature-Based Cascade-connected Artificial Neural Networks
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[127]	Wind Speed Forecasting by Conventional Statistical Methods and Machine Learning Techniques
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[128]	Modeling wind speed with a long-term horizon and high-time interval with a hybrid fourier-neural network model
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[129]	Atmospheric effects on short term wind power forecasting
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[130]	Wind Power Projection using Weather Forecasts by Novel Deep Neural Networks
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[131]	Caribbean Sea Offshore Wind Energy Assessment and Forecasting
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[132]	A combined method for wind power generation forecasting
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[149]	Wind Speed Forecasting Using Feed-Forward Artificial Neural Network
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[150]	Artificial Intelligence Techniques in Smart Grid
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[151]	The Prediction of Weather's Data for Wind, Power System Using Graph Database
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[152]	A Short Term Wind Speed Forecasting Model Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Models
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[153]	Short Time Solar Power Forecasting Using Persistence Extreme Learning Machine Approach
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[154]	Wind speed forecasting in Nepal using self-organizing map-based online sequential extreme learning machine
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[155]	Using Machine-Learning Methods to Improve Surface Wind Speed from the Outputs of a Numerical Weather Prediction Model
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[156]	A novel hybrid model based on weather variables relationships improving applied for wind speed forecasting
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[157]	Review of Wind Models at a Local Scale: Advantages and Disadvantages
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[158]	Tuulivoima ja tuulen ennustaminen
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[160]	Multi-step wind speed forecast based on sample clustering and an optimized hybrid system
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[161]	Short-Term Wind Power Prediction Using Hybrid Auto Regressive Integrated Moving Average Model and Dynamic Particle Swarm Optimization
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[162]	An empirical analysis of applications of artificial intelligence algorithms in wind power technology innovation during 1980–2017
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[163]	Wind power 24-h ahead forecast by an artificial neural network and an hybrid model: Comparison of the predictive performance
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[164]	MULTI-STEP FORWARD FORECASTING OF ELECTRICAL POWER GENERATION IN LIGNITE-FIRED THERMAL POWER PLANT
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[165]	Artificial Intelligence Based Hybrid Forecasting Approaches for Wind Power Generation: Progress, Challenges and Prospects
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[166]	A Spatio-Temporal Model for Predicting Wind Speeds in Southern California
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[167]	Predictive models for wind speed using artificial intelligence and copula
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[168]	Hybrid numerical models for wind speed forecasting
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[169]	A Review of Machine Learning Applications in Electricity Market Studies
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[170]	Learning Deep Architectures for Power Systems Operation and Analysis
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[171]	Prediction of Wind Speed Using Hybrid Techniques
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[172]	Machine learning aplicado à previsão de geração de energia eólica com diferentes modelos de previsão numérica do tempo
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[173]	A brief comparison of different learning methods for wind speed forecasting
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[174]	考虑时序波动的风速分布描述方法
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[175]	Estudo do potencial eólico offshore no estado da Bahia utilizando o modelo WRF
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[176]	Математична модель та програмне забезпечення прогнозу генерування електроенергії вітрогенератором для геолокаційних карт
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[177]	Timescale classification in wind forecasting: A review of the state‐of‐the‐art
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[178]	Impact of Battery Energy Storage System and its Converter Characteristics on Voltage Sags
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[179]	Short-term Wind Power Forecasting Based on Spatial Correlation and Artificial Neural Network
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[180]	Characterising the fractal dimension of wind speed time series under different terrain conditions
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[181]	A novel electrical net-load forecasting model based on deep neural networks and wavelet transform integration
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[182]	Improving wind speed forecasts from the Weather Research and Forecasting model at a wind farm in the semiarid Coquimbo region in central Chile
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[183]	Predictive Modelling for Energy Management and Power Systems Engineering
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[184]	Estimating the impact of uncertainty on optimum capacitor placement in wind‐integrated radial distribution system
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[185]	Uncertain wind power forecasting using LSTM-based prediction interval
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[186]	Prediction of Wind Speed Using Hybrid Techniques. Three locations: Colombia, Ecuador and Spain
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[187]	Hourly day-ahead wind power forecasting with the EEMD-CSO-LSTM-EFG deep learning technique
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[188]	Comprehensive Review of Wind Energy in Malaysia: Past, Present, and Future
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[189]	Fractal characteristics of tall tower wind speeds in Missouri
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[190]	A Derivative Tracking Model for Wind Power Forecast Error
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[191]	Industrial Ultra-Short-Term Load Forecasting With Data Completion
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[192]	A Critical Review of Wind
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[193]	Wind Generation Forecasting Using Python
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[194]	Design and operation strategy for multi-use application of battery energy storage in wind farms
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[195]	Short-term Wind Speed Forecasting based on LSSVM Optimized by Elitist QPSO
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[196]	A Comprehensive Review of Wind Energy in Malaysia: Past, Present and Future Research Trends
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[197]	Comparison of Recurrent Neural Networks for Wind Power Forecasting
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[198]	Deep learning architectures applied to wind time series multi-step forecasting
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[199]	Replacement Reserve for the Italian Power System and Electricity Market
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[202]	An Ensemble Forecasting Model of Wind Power Outputs based on Improved Statistical Approaches
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[203]	Stochastic modelling of wind speeds based on turbulence intensity
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[206]	Gated Recurrent Unit (GRU) Based Short Term Forecasting for Wind Energy Estimation
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[207]	Uncertain wind power forecasting using LSTM‐based prediction interval
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[208]	Forecasting of wind power using lstm recurrent neural network
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[209]	Sub-hourly forecasting of wind speed and wind energy
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[212]	Comprehensive review of wind energy in Malaysia: Past, present, and future research trends
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[213]	Development of methodologies supporting the sustainable and safe integration of offshore conventional and renewable energy production
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[214]	Improved prediction of wind speed using machine learning.
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[215]	Prediction of short-period energy production for wind farms
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[216]	Previsão de Geração no Médio Prazo em um Parque Eólico no Rio Grande do Sul utilizando o GFS e Redes Neurais Artificiais
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[219]	A Data-Driven Short-Term Forecasting Model for Offshore Wind Speed Prediction Based on Computational Intelligence
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[220]	Advances in Wind Power Forecasting
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[223]	Short-term electricity trading for system balancing: An empirical analysis of the role of intraday trading in balancing Germany's electricity system
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[225]	RANCANG BANGUN PENERAPAN JARINGAN SARAF TIRUAN UNTUK MEMPREDIKSI ARAH ANGINPADA PENGONTROLAN YAW PURWARUPA TURBIN ANGIN
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[226]	Técnicas de predicción escalables para big data temporales
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[227]	Probabilistic wind forecasting up to three months ahead using ensemble predictions for geopotential height
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[228]	Design and Implementation of Artificial Neural Networks to Predict Wind Directions on Controlling Yaw of Wind Turbine Prototype
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[229]	TIME SERIES MODEL APPLIED TO PREDICT THE WIND POWER ENERGY PRODUCTION
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[230]	A Comparative Study of Short-Term Wind Speed Forecasting Models
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[231]	PHƯƠNG PHÁP DỰ BÁO VẬN TỐC GIÓ CHO CÁC NHÀ MÁY ĐIỆN GIÓ CÓ
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[232]	A novel hybrid metaheuristic optimization method to estimate medium-term output power for horizontal axis wind turbine
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[233]	A New Method for Generating Short-Term Power Forecasting Based on Artificial Neural Networks and
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[234]	Repeated wavelet transform based ARIMA model for very short-term wind speed forecasting
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[235]	Robust short-term prediction of wind power generation under uncertainty via statistical interpretation of multiple forecasting models
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[236]	Improved Prediction of Wind Speed using Machine Learning
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[237]	Short-term wind speed forecasting in Uruguay using computational intelligence
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[238]	A supervisory control method of hybrid AC/DC microgrids considering uncertainty in loads and renewable energy sources
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[239]	A regime-switching recurrent neural network model applied to wind time series
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[240]	Prediction of Wind Power Density for Electricity Generation at Makambako, Tanzania Using Auto-Regression Integrated Moving Average (ARIMA) Model
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[241]	Scenario-based wind speed estimation using a new hybrid metaheuristic model: Particle swarm optimization and radial movement optimization
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[242]	A review on the selected applications of forecasting models in renewable power systems
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[243]	A hybrid forecasting system based on fuzzy time series and multi-objective optimization for wind speed forecasting
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[244]	A New Method for Generating Short-Term Power Forecasting Based on Artificial Neural Networks and Optimization Methods for Solar Photovoltaic Power Plants
	2019

[245]	A framework for online prediction using kernel adaptive filtering
	2019

[246]	Comparison of Wind Scenarios Generation Methods-A Case Study From Ecuador
	2019

[247]	Deep Learning Method Based on Gated Recurrent Unit and Variational Mode Decomposition for Short-Term Wind Power Interval Prediction
	2019

[248]	Availability estimation of wind power forecasting and optimization of day-ahead unit commitment
	2019

[249]	Modelling and forecasting wind drought
	2019

[250]	Coordinated Voltage and Reactive Power Control for Renewable Dominant Smart Distribution Systems
	2019

[251]	Using Artificial Intelligence to Predict Wind Speed for Energy Application in Saudi Arabia
	2019

[252]	Trajectory tracking with an aggregation of domestic hot water heaters: Combining model-based and model-free control in a commercial deployment
	2019

[253]	Wind power ensemble forecasting
	2019

[254]	Forecasting the wind power generation using Box–Jenkins and hybrid artificial intelligence
	2019

[255]	Detecting the Long-Term Frequency of Large-Scale Wind Power Ramp Events Observed in ERCOT's Aggregated Wind Power Time-Series Data
	2019

[256]	Demand-Side Load Management Using Single-Phase Residential Static VAR Compensators
	2019

[257]	Error Analysis of Ultra Short Term Wind Power Prediction Model and Effect on the Power System Frequency
	2019

[258]	Integration of Micro Grid System using 3-Level Inverter
	2019

[259]	Department Of Electrical And Electronic Engineering Short-termwind-speed-to-wind-power Forecasting Using A Hybrid Of Particle Swarm Optimization And Artificial …
	2019

[260]	Оценка мощности ветроэнергетических установок на основе нечеткой модели ветрового потока и его вероятностных характеристик
	2019

[261]	Business cases for wind battery storage
	2019

[262]	Doğrusal Ve Doğrusal Olmayan Metotlarla Bir Adım İleri Rüzgar Şiddeti Öngörüsü
	2019

[263]	The impact of renewable energy forecasts on intraday electricity prices
	2019

[264]	PLANIFICACIÓN EFICIENTE DE REDES INTELIGENTES (SMART GRIDS) INCLUYENDO LA GESTIÓN ACTIVA DE LA DEMANDA: APLICACIÓN A ECUADOR
	2018

[265]	EFFECTS OF NUMERICAL WEATHER PREDICTIONS ON WIND POWER FORECASTS
	2018

[266]	Wind Power Forecasting
	2018

[267]	Generation Forecasting Models for Wind and Solar Power
	International Journal of Computer Electrical Engineering, 2018

[268]	Improved Stacked Ensemble based Model For Very Short-Term Wind Power Forecasting
	2018

[269]	Algorithms for technical integration of virtual power plants into German system operation
	2018

[270]	Estimation-Based Model Predictive Control for Automatic Crosswind Stabilization of Hybrid Aerial Vehicles
	2018

[271]	Ultra-short-term multi-step wind power prediction based on fractal scaling factor transformation
	AIP Conference Proceedings, 2018

[272]	An intelligent framework for short-term multi-step wind speed forecasting based on Functional Networks
	Applied Energy, 2018

[273]	Generation Forecasting for Small Run-of-the-River Hydroelectric Systems Using Statistical Learning Models
	2018

[274]	A review of methods applied for wind power generation forecasting
	Polityka Energetyczna, 2018

[275]	Comparing different solutions for forecasting the energy production of a wind farm
	Neural Computing and Applications, 2018

[276]	A short-term wind speed forecasting model by using artificial neural networks with stochastic optimization for renewable energy systems
	Energies, 2018

[277]	Prediction of fatal accidents in Indian factories based on ARIMA
	Production Engineering Archives, 2018

[278]	Ultra-short-term Multi-step Wind Power Prediction Based on Improved EMD and Reconstruction Method Using Run-length Analysis
	2018

[279]	Innovative Hybrid Modeling of Wind Speed Prediction Involving Time-Series Models and Artificial Neural Networks
	Atmosphere, 2018

[280]	Elaboración de pronóstico energético a corto plazo para parques eólicos
	2018

[281]	Bir rüzgar çiftliğinden yapay sinir ağlarıyla kısa süreli elektrik üretim tahmini
	2018

[282]	Planificación Eficiente de Redes Inteligentes (Smartgrids) Incluyendo la Gestión Activa de la Demanda: Aplicación a Ecuador.
	2018

[283]	Optimisation of the Structure of a Wind Farm—Kinetic Energy Storage for Improving the Reliability of Electricity Supplies
	Applied Sciences, 2018

[284]	A survey of analytical methods for inclusion in a new energy-water nexus knowledge discovery framework
	Big Earth Data, 2018

[285]	Forecasting from incomplete and chaotic wind speed data
	Soft Computing, 2018

[286]	Consumption and production forecast algorithm for a smart grid
	Master project, 2018-2019, 2018

[287]	Machine learning for energy-water nexus: challenges and opportunities
	Big Earth Data, 2018

[288]	Ocena proizvodnje električne energije vetrne elektrarne z Weibullovo funkcijo
	2018

[289]	Comparison of Three Methods for Short-Term Wind Power Forecasting
	2018

[290]	A GA-PSO Hybrid Algorithm Based Neural Network Modeling Technique for Short-term Wind Power Forecasting
	Distributed Generation & Alternative Energy Journal, 2018

[291]	Positioning of operating responsibility of electrical energy storage: Case study: EES implementing in the Dutch electricity system
	2018

[292]	Novel Supervisory Control Method for Islanded Droop-Based AC/DC Microgrids
	2018

[293]	Metodologia Híbrida para a Previsão dos Preços do Mercado Elétrico com Integração Renovável
	2018

[294]	Interval deep generative neural network for wind speed forecasting
	2018

[295]	Technical Integration of Virtual Power Plants enhanced by Energy Storages into German System Operation with regard to Following the Schedule in Intra-Day
	2018

[296]	Load and RE Forecasting – Utilization and Impact on System Operation
	2018

[297]	Ultra-short Term Wind Speed Prediction under Multi-model Structure and Uncertainty Analysis
	2018

[298]	Short-term forecasting models of wind speed for airborne wind turbines: a comparative study
	2018

[299]	Two-Way Energy Flow Optimization Based on Smart Grid Concept
	2018

[300]	Short-term electricity trading for system balancing
	2018

[301]	Modeling, planning, application and management of energy systems for isolated areas: A review
	Renewable and Sustainable Energy Reviews, 2018

[302]	A New Hybrid Prediction Method of Ultra-Short-Term Wind Power Forecasting Based on EEMD-PE and LSSVM Optimized by the GSA
	Energies, 2018

[303]	Wind Power Forecasting Based on Echo State Networks and Long Short-Term Memory
	Energies, 2018

[304]	Wind Power and Ramp Forecasting for Grid Integration
	Advanced Wind Turbine Technology, 2018

[305]	Stochastic wind speed modelling for estimation of expected wind power output
	Applied Energy, 2018

[306]	Spatio-temporal Graph Deep Neural Network for Short-term Wind Speed Forecasting
	2018

[307]	Assessment of Wind Power Prediction Using Hybrid Method and Comparison with Different Models
	Journal of Electrical Engineering & Technology, 2018

[308]	Estimation of renewable energy and built environment-related variables using neural networks–A review
	Renewable and Sustainable Energy Reviews, 2018

[309]	Short‐term wind power prediction in microgrids using a hybrid approach integrating genetic algorithm, particle swarm optimization, and adaptive neuro‐fuzzy …
	IEEJ Transactions on Electrical and Electronic Engineering, 2018

[310]	24-hours wind speed forecasting and wind power generation in La Serena (Chile)
	Wind Engineering, 2018

[311]	Short-term forecasting of wind power production using machine learning and deep learning methods
	2018

[312]	Rüzgar parametrelerinin değişiminin izlenmesi ve yapay zeka algoritmaları kullanılarak tahmini
	2018

[313]	Transformer less Grid Integrated Wind Energy Conversion System Using Multilevel Inverter
	2018

[314]	Forecasting Models for Renewable Power Dispatch in Microgrids
	2017

[315]	Characterization of flexibility resources and distribution networks
	2017

[316]	An overview of forecasting techniques for load, wind and solar powers
	2017

[317]	Forecasting of wind speed using ANN, ARIMA and Hybrid models
	2017

[318]	Multi-step Ahead Wind Forecasting Using Nonlinear Autoregressive Neural Networks
	Energy Procedia, 2017

[319]	Technical integration of virtual power plants into German system operation
	2017

[320]	Comparative investigation of short-term wind speed forecasting models for airborne wind turbines
	2017

[321]	Análise da complementaridade das gerações intermitentes no planejamento da operação eletro-energética da região nordeste brasileira
	2017

[322]	Short Term Wind Speed Forecasting using Hybrid ELM Approach
	2017

[323]	Optimized hybrid wind power generation with forecasting algorithms and battery life considerations
	2017

[324]	Combinatorial double auctions for multiple microgrid trading
	Electrical Engineering, 2017

[325]	A novel method based on Weibull distribution for short-term wind speed prediction
	International Journal of Hydrogen Energy, 2017

[326]	Performance Analysis of Time Series Forecasting Models for Short Term Wind Speed Prediction
	2017

[327]	Accurate Short-Term Power Forecasting of Wind Turbines: The Case of Jeju Island's Wind Farm
	Energies, 2017

[328]	Flexible Reserve Margin Optimization for Increased Wind Generation Penetration
	ProQuest Dissertations Publishing, 2017

[329]	Smart grid integration of micro hybrid power system using 6-switched 3-level inverter
	2017

[330]	Short Term Wind Power Prediction Based on Improved Kriging Interpolation, Empirical Mode Decomposition, and Closed-Loop Forecasting Engine
	Sustainability, 2017

[331]	Rough Deep Neural Architecture for Short-Term Wind Speed Forecasting
	2017

[332]	Simulation of Wind-Battery Microgrid Based on Short-Term Wind Power Forecasting
	Applied Sciences, 2017

[333]	Short term solar insolation prediction: P-ELM approach
	Journal of Strategic Marketing, 2017

[334]	Development of an Offshore Specific Wind Power Forecasting System
	2017

[335]	Determination of Appropriate Distribution Functions for the Wind Speed Data Using the R Language
	2017

[336]	Implications of high wind penetration for the NEM
	2017

[337]	Comparison of forecasting methods for vertical axis wind turbine applications in an urban/suburban area
	AIP Conference Proceedings, 2017

[338]	WIND FORECASTING USING ARTIFICIAL NEURAL NETWORKS: A SURVEY AND TAXONOMY
	2017

[339]	A Statistical Analysis of Short-Term Wind Power Forecasting Error Distribution
	International Journal of Applied Engineering Research [IJAER], 2017

[340]	A methodology to assess home PV capacity to mitigate wind power forecasting errors
	2017

[341]	An ARIMA model for the forecasting of healthcare waste generation in the Garhwal region of Uttarakhand, India
	2017

[342]	Methodology and Precision Research of Wind Farm Power Prediction
	2017

[343]	Wind power forecasting: A case study in terrain using artificial intelligence
	International Research Journal of Engineering and Technology, 2017

[344]	Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods
	Renewable and Sustainable Energy Reviews, 2017

[345]	ADVANCED FORECASTING METHODS FOR RENEWABLE GENERATION AND LOADS IN MODERN POWER SYSTEMS
	2017

[346]	A Nonlinear Autoregressive Neural Network Model for Short-Term Wind Forecasting
	2017

[347]	Increase of the Integration Degree of Wind Power Plants into the Energy System Using Wind Forecasting and Power Consumption Predictor Models by …
	2017

[348]	Support Vector Regression 기반의 단기 풍력발전 예측시스템 개발
	Journal of the Korean Institute of Illuminating and Electrical Installation Engineers, 2017

[349]	Повышение степени интеграции ветроэнергетических станций в энергосистему путем использования у системного оператора математических …
	2017

[350]	Pronóstico a corto plazo de velocidad del viento a partir de datos incompletos
	2017

[351]	Cost minimization in multi wind farm power dispatch
	2017

[352]	Wind Speed Prediction using Back Propagation Mechanism in ANN
	2017

[353]	Wind speed time series reconstruction using a hybrid neural genetic approach
	2017

[354]	Increase of the Integration Degree of Wind Power Plants into the Energy System Using Wind Forecasting and Power Consumption Predictor Models by Transmission …
	2017

[355]	An Empirical Analysis of the Effect of Wind Power on the Level and the Volatility of the Electricity Price in the Nordic-Baltic Market
	Master’s thesis in economics, 2017

[356]	Wind Speed Prediction using Levenberg-Marqardt Back Propagation Neural Network
	International Journal for Rapid Research in Engineering Technology & Applied Science, 2017

[357]	Wind Power Prediction Using a Hybrid Approach with Correction Strategy Based on Risk Evaluation
	2017

[358]	Pronóstico a corto plazo de velocidad del viento a partir de datos incompletos.
	2017

[359]	On The Development of Solar & Wind Energy Forecasting Application Using ARIMA, ANN and WRF in MATLAB
	2017

[360]	تخمین اقتصادی رزرو مورد نیاز مزارع بادی با بکارگیری شبکه عصبی در پیش‌بینی سرعت باد‎
	2017

[361]	Forecasting wind speed of Suva (Fiji) and Abaiang (Kiribati) using artificial neural network
	2017

[362]	Повышение степени интеграции ветроэнергетических станций в энергосистему путем использования у системного оператора математических моделей …
	Problemele Energeticii …, 2017

[363]	Wind prediction modelling and validation using coherent Doppler LIDAR data
	2016

[364]	Joint optimisation of generation and storage in the presence of wind
	2016

[365]	Sistema automático de estimação do potencial de produção eólica para Portugal Continental
	2016

[366]	A new wind power model using the lightning search algorithm
	2016

[367]	LONG TERM WIND SPEED PREDICTION USING WAVELET COEFFICIENTS AND SOFT COMPUTING
	2016

[368]	DEEPSO to Predict Wind Power and Electricity Market Prices Series in the Short-Term
	2016

[369]	A GA-BP hybrid algorithm based ANN model for wind power prediction
	2016

[370]	The impact of climate change on the wind energy resource of Suriname using Regional Climate Model (RCM) simulations
	International Journal of Engineering and Applied Sciences, 2016

[371]	Intelligent energy management control for independent microgrid
	Sadhana, 2016

[372]	Metodologia Híbrida de Previsão de Preços de Eletricidade e Potência Eólica
	Dissertation, Open Repository of the University of Porto, 2016

[373]	Modelling the Variability of the Wind Energy Resource on Monthly and Seasonal Timescales
	Pré-publication, Document de travail, 2016

[374]	K-means clustering with a new initialization approach for wind power forecasting
	2016

[375]	Enhanced Forecasting Approach for Electricity Market Prices and Wind Power Data Series in the Short-Term
	Energies, 2016

[376]	Most influential parametrical and data needs for realistic wind speed prediction
	Renewable Energy, 2016

[377]	Técnicas de ajuste geográfico e dinâmico de Modelos de Previsão de Produção Eólica
	Dissertation, Open Repository of the University of Porto, 2016

[378]	Enhanced power system operational performance with anticipatory control under increased penetration of wind energy
	ProQuest Dissertations Publishing, 2016

[379]	EMoFS Tekniği Kullanılarak Rüzgar Gücü Tahmini Yapılması Wind Power Prediction Using EMoFS Technique
	2016

[380]	Wind Speed Forecasting based on Statistical Auto Regressive Integrated Moving Average (ARIMA) method
	IJCTA, 2016

[381]	Demand forecasting in residential distribution feeders in the context of smart grids
	2016

[382]	Wind power prediction using EMoFS technique
	2016

[383]	Utilização de Micro FV com Armazenamento para Compensação da Intermitência da Energia Eólica
	2016

[384]	Short term wind power prediction using ANFIS
	2016

[385]	Técnicas de ajuste geográfico e dinâmico de modelos de previsão eólica
	Dissertation, Open Repository of the University of Porto, 2016

[386]	Lissage optimal de la charge électrique en présence de sources d'énergies renouvelables via le pilotage de la consommation des chauffe-eau
	2016

[387]	Examining nominal and ordinal classifiers for forecasting wind speed
	2016

[388]	Vėjo elektrinių integracijos į elektros energetikos sistemą ir galių balansavimo tyrimai
	2016

[389]	Investigations OnWind Resource Assessment and Wind Farm Layout Using Hybrid Algorithms and Simulation Tools
	2015

[390]	Investigations on Wind Resource Assessment and Wind Farm Layout Using Hybrid Algorithms and Simulation Tools
	2015

[391]	Aplicação de Heurísticas para Otimização e Parâmetros de Modelos de Previsão Eólica
	Dissertation, Open Repository of the University of Porto, 2015

[392]	Application Layer Protocol for Network Integration of a Smart Grid Residential Load-Shifting Algorithm
	International Journal of Computer Science and Mobile Computing, 2015

[393]	Modelling and fitting of the wind data using different time series models and investigating the relared applications of fitted data. Urla and RisØ cases
	2015

[394]	수치 예측 알고리즘 기반의 풍속 예보 모델 학습
	Journal of the Korea Society of Computer and Information, 2015

[395]	Optimizing Local Least Squares Regression for Short Term Wind Prediction
	2015

[396]	Short Term Wind Power Generation Forecasting Using Adaptive Network-Based Fuzzy Inference System
	2015

[397]	Artificial Intelligence Techniques for Wind Power Prediction: A Case Study
	Indian Journal of Science and Technology, 2015

[398]	Comparison of BPN and RBF Neural Networks for Prediction of Wind Speed
	International Journal of Computer & Modern Technology, 2015

[399]	Wind speed prediction in the mountainous region of India using an artificial neural network model
	Renewable Energy, 2015

[400]	Short-term wind power prediction based on Hybrid Neural Network and chaotic shark smell optimization
	International Journal of Precision Engineering and Manufacturing-Green Technology, 2015

[401]	MODELOS DE SIMULAÇÃO DE CENÁRIOS DE PRODUÇÃO DE ENERGIA EÓLICA A PARTR DO MÉTODO DE HOLT-WINTERS E SUAS VARIAÇÕES
	2015

[402]	Aplicação de Heurísticas para Otimização de Parâmetros de Modelos de Previsão Eólica
	Dissertation, Open Repository of the University of Porto, 2015

[403]	A Review of EV Load Scheduling with Wind Power Integration
	IFAC-PapersOnLine, 2015

[404]	Learning Wind Speed Forecast Model based on Numeric Prediction Algorithm
	2015

[405]	Wind power potential assessment of 12 locations in western Himalayan region of India
	Renewable and Sustainable Energy Reviews, 2014

[406]	MODELING AND FITTING OF THE WIND DATA USING DIFFERENT TIME SERIES MODELS AND INVESTIGATING THE RELATED APPLICATIONS OF FITTED …
	2014

[407]	MODELING AND FITTING OF THE WIND DATA USING DIFFERENT TIME SERIES MODELS AND INVESTIGATING THE RELATED APPLICATIONS OF …
	2014

[408]	İslam hukukunda hasta hakları
	2014

[409]	Modeling and fitting of the wind data using different time series models and investigating the related applications of fitted data. Urla and Risø cases
	2014

[410]	A REVIEW ON GLOBAL WIND POWER FORECASTING APPROACHES
	Журнал “Internationalе politik, 2001

[411]	PREDIKSI KEBUTUHAN PLTS DAN PLTB BERBASIS


[412]	SWIRL: Statistical downscaling for Wind Pattern Reconstruction using Machine Learning


[413]	Optimal Scheduling of Renewable Energy Microgrids: A Robust Multi-Objective Approach with Machine Learning-Based Probabilistic Forecasting


[414]	Rüzgar hızının farklı yöntemlerle tahminlenmesi ile ilgili örnek bir uygulama


[415]	Weather prediction using random forest machine learning model


[416]	REVIEW ON VARIOUS FORECASTING METHODS ON RENEWABLE ENERGY SOURCES

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[2]	Forecasting Wind Farm Production in the Short, Medium, and Long Terms Using Various Machine Learning Algorithms Energies, 2025 DOI:10.3390/en18051125

[3]	Evaluating Temporal and Spatial Characteristics of Wind Energy for Enhanced Synthetic Inertia Provision in Power Systems 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), 2024 DOI:10.1109/ISGTEUROPE62998.2024.10863593

[4]	Forecasting of wind farm power output based on dynamic loading of power transformer at the substation Electric Power Systems Research, 2024 DOI:10.1016/j.epsr.2024.110527

[5]	Improving the Forecasts of Coastal Wind Speeds in Tianjin, China Based on the WRF Model with Machine Learning Algorithms Journal of Meteorological Research, 2024 DOI:10.1007/s13351-024-3096-z

[6]	DWT-BILSTM-based models for day-ahead hourly global horizontal solar irradiance forecasting Neural Computing and Applications, 2024 DOI:10.1007/s00521-024-09701-2

[7]	Optimal scheduling of renewable energy microgrids: A robust multi-objective approach with machine learning-based probabilistic forecasting Applied Energy, 2024 DOI:10.1016/j.apenergy.2024.123548

[8]	Wind speed forecasting in Aceh using ARIMA and neural network model PROCEEDINGS OF THE 38TH INTERNATIONAL CONFERENCE OF THE POLYMER PROCESSING SOCIETY (PPS-38), 2024 DOI:10.1063/5.0225267

[9]	Advances in Energy Recovery and Efficiency Technologies [Working Title] 2024 DOI:10.5772/intechopen.1007556

[10]	Improving the Forecasts of Coastal Wind Speeds in Tianjin, China Based on the WRF Model with Machine Learning Algorithms Journal of Meteorological Research, 2024 DOI:10.1007/s13351-024-3096-z

[11]	Accelerating Discoveries in Data Science and Artificial Intelligence I Springer Proceedings in Mathematics & Statistics, 2024 DOI:10.1007/978-3-031-51167-7_16

[12]	Wind power forecasting technologies: A review Energy Storage and Conversion, 2024 DOI:10.59400/esc.v2i3.538

[13]	STGPT2UGAN: Spatio-Temporal GPT-2 United Generative Adversarial Network for Wind Speed Prediction in Turbine Network Applied Sciences, 2024 DOI:10.3390/app142311217

[14]	Machine Learning and Fuzzy PID for the Control of the Pitch Angle of Wind Turbine Blade 2024 IEEE International Conference on Artificial Intelligence & Green Energy (ICAIGE), 2024 DOI:10.1109/ICAIGE62696.2024.10776619

[15]	A Review of Uncertainties in Power Systems—Modeling, Impact, and Mitigation Designs, 2024 DOI:10.3390/designs8010010

[16]	Wavelet decomposition and neural networks: a potent combination for short term wind speed and power forecasting Frontiers in Energy Research, 2024 DOI:10.3389/fenrg.2024.1277464

[17]	Solar and Wind Data Recognition: Fourier Regression for Robust Recovery Big Data and Cognitive Computing, 2024 DOI:10.3390/bdcc8030023

[18]	Wind speed prediction for site selection and reliable operation of wind power plants in coastal regions using machine learning algorithm variants Sustainable Energy Research, 2024 DOI:10.1186/s40807-024-00098-z

[19]	Review of Wind Flow Modelling in Urban Environments to Support the Development of Urban Air Mobility Drones, 2024 DOI:10.3390/drones8040147

[20]	Review of Wind Flow Modelling in Urban Environments to Support the Development of Urban Air Mobility Drones, 2024 DOI:10.3390/drones8040147

[21]	Wind Speed Downscaling of the WRF Model at Subkilometer Scale in Complex Terrain for Wind Power Applications IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024 DOI:10.1109/JSTARS.2024.3386629

[22]	Wind Energy Storage and Conversion 2024 DOI:10.1002/9781394204564.ch3

[23]	Accelerating Discoveries in Data Science and Artificial Intelligence I Springer Proceedings in Mathematics & Statistics, 2024 DOI:10.1007/978-3-031-51167-7_16

[24]	MSTL-NNAR: a new hybrid model of machine learning and time series decomposition for wind speed forecasting Stochastic Environmental Research and Risk Assessment, 2024 DOI:10.1007/s00477-024-02701-7

[25]	New ridge regression, artificial neural networks and support vector machine for wind speed prediction Advances in Engineering Software, 2023 DOI:10.1016/j.advengsoft.2023.103426

[26]	Wind Speed Forecasting using Hybrid Model of CNN and LSTM with Wavelets 2023 International Conference in Advances in Power, Signal, and Information Technology (APSIT), 2023 DOI:10.1109/APSIT58554.2023.10201713

[27]	A Brief Review on Estimation and Forecasting of Grid System in Sustainable Micro Grid System Integration 2023 International Conference on Power Energy, Environment & Intelligent Control (PEEIC), 2023 DOI:10.1109/PEEIC59336.2023.10450944

[28]	A Deep Learning Approach for Climate Parameter Estimations and Renewable Energy Sources 2023 IEEE International Conference on Big Data (BigData), 2023 DOI:10.1109/BigData59044.2023.10386617

[29]	Review of Estimating and Predicting Models of the Wind Energy Amount Energies, 2023 DOI:10.3390/en16165926

[30]	Wind Speed Forecasting using Hybrid Model of CNN and LSTM with Wavelets 2023 International Conference in Advances in Power, Signal, and Information Technology (APSIT), 2023 DOI:10.1109/APSIT58554.2023.10201713

[31]	A Review on Modeling Variable Renewable Energy: Complementarity and Spatial–Temporal Dependence Energies, 2023 DOI:10.3390/en16031013

[32]	A novel approach to ultra-short-term wind power prediction based on feature engineering and informer Energy Reports, 2023 DOI:10.1016/j.egyr.2022.12.062

[33]	Spatio-temporal wind speed forecasting using graph networks and novel Transformer architectures Applied Energy, 2023 DOI:10.1016/j.apenergy.2022.120565

[34]	Review of Key Technologies for Offshore Floating Wind Power Generation Energies, 2023 DOI:10.3390/en16020710

[35]	Expectation-Based Probabilistic Naive Approach for Forecasting Involving Optimized Parameter Estimation Arabian Journal for Science and Engineering, 2023 DOI:10.1007/s13369-022-06819-0

[36]	Comparison of Statistical Production Models for a Solar and a Wind Power Plant Mathematics, 2023 DOI:10.3390/math11051115

[37]	New ridge regression, artificial neural networks and support vector machine for wind speed prediction Advances in Engineering Software, 2023 DOI:10.1016/j.advengsoft.2023.103426

[38]	Comprehensive Review Based on the Impact of Integrating Electric Vehicle and Renewable Energy Sources to the Grid Energies, 2023 DOI:10.3390/en16062924

[39]	A CNN encoder decoder LSTM model for sustainable wind power predictive analytics Sustainable Computing: Informatics and Systems, 2023 DOI:10.1016/j.suscom.2023.100869

[40]	Pricing Wind Power Uncertainty in the Electricity Market IEEE Access, 2023 DOI:10.1109/ACCESS.2023.3282575

[41]	Multimodality-based Wind Speed Forecasting Method for the Wind Resistance Control of Large Radio Telescope Research in Astronomy and Astrophysics, 2023 DOI:10.1088/1674-4527/acdfa6

[42]	A survey of long short term memory and its associated models in sustainable wind energy predictive analytics Artificial Intelligence Review, 2023 DOI:10.1007/s10462-023-10554-9

[43]	Spatio-temporal wind speed forecasting using graph networks and novel Transformer architectures Applied Energy, 2023 DOI:10.1016/j.apenergy.2022.120565

[44]	A hybrid model for online short-term tidal energy forecasting Applied Ocean Research, 2023 DOI:10.1016/j.apor.2023.103596

[45]	Comparison and Enhancement of Machine Learning Algorithms for Wind Turbine Output Prediction with Insufficient Data Energies, 2023 DOI:10.3390/en16155810

[46]	Neural Network based wind energy model developed over Anantapur, Andhra Pradesh, India Journal of Physics: Conference Series, 2023 DOI:10.1088/1742-6596/2471/1/012029

[47]	GCNInformer: A combined deep learning model based on GCN and Informer for wind power forecasting Energy Science & Engineering, 2023 DOI:10.1002/ese3.1562

[48]	A survey of long short term memory and its associated models in sustainable wind energy predictive analytics Artificial Intelligence Review, 2023 DOI:10.1007/s10462-023-10554-9

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[225]	Ultra-short-term multi-step wind power prediction based on fractal scaling factor transformation Journal of Renewable and Sustainable Energy, 2018 DOI:10.1063/1.5042795

[226]	A Short-Term Wind Speed Forecasting Model by Using Artificial Neural Networks with Stochastic Optimization for Renewable Energy Systems Energies, 2018 DOI:10.3390/en11102777

[227]	Optimisation of the Structure of a Wind Farm—Kinetic Energy Storage for Improving the Reliability of Electricity Supplies Applied Sciences, 2018 DOI:10.3390/app8091439

[228]	Innovative Hybrid Modeling of Wind Speed Prediction Involving Time-Series Models and Artificial Neural Networks Atmosphere, 2018 DOI:10.3390/atmos9020077

[229]	A New Hybrid Prediction Method of Ultra-Short-Term Wind Power Forecasting Based on EEMD-PE and LSSVM Optimized by the GSA Energies, 2018 DOI:10.3390/en11040697

[230]	Short‐term wind power prediction in microgrids using a hybrid approach integrating genetic algorithm, particle swarm optimization, and adaptive neuro‐fuzzy inference systems IEEJ Transactions on Electrical and Electronic Engineering, 2018 DOI:10.1002/tee.22720

[231]	Prediction of fatal accidents in Indian factories based on ARIMA Production Engineering Archives, 2018 DOI:10.30657/pea.2018.18.04

[232]	Prediction of fatal accidents in Indian factories based on ARIMA Production Engineering Archives, 2018 DOI:10.30657/pea.2018.18.04

[233]	Comparison of forecasting methods for vertical axis wind turbine applications in an urban/suburban area Journal of Renewable and Sustainable Energy, 2017 DOI:10.1063/1.4978304

[234]	Short Term Wind Power Prediction Based on Improved Kriging Interpolation, Empirical Mode Decomposition, and Closed-Loop Forecasting Engine Sustainability, 2017 DOI:10.3390/su9112104

[235]	Simulation of Wind-Battery Microgrid Based on Short-Term Wind Power Forecasting Applied Sciences, 2017 DOI:10.3390/app7111142

[236]	Accurate Short-Term Power Forecasting of Wind Turbines: The Case of Jeju Island’s Wind Farm Energies, 2017 DOI:10.3390/en10060812

[237]	Different Models for Forecasting Wind Power Generation: Case Study Energies, 2017 DOI:10.3390/en10121976

[238]	Rough Deep Neural Architecture for Short-Term Wind Speed Forecasting IEEE Transactions on Industrial Informatics, 2017 DOI:10.1109/TII.2017.2730846

[239]	A novel method based on Weibull distribution for short-term wind speed prediction International Journal of Hydrogen Energy, 2017 DOI:10.1016/j.ijhydene.2017.03.006

[240]	Comparison of forecasting methods for vertical axis wind turbine applications in an urban/suburban area Journal of Renewable and Sustainable Energy, 2017 DOI:10.1063/1.4978304

[241]	Short Term Wind Speed Forecasting using Hybrid ELM Approach Indian Journal of Science and Technology, 2017 DOI:10.17485/ijst/2017/v10i8/104479

[242]	Ultra-Short-Term Wind Power Prediction Using a Hybrid Model IOP Conference Series: Earth and Environmental Science, 2017 DOI:10.1088/1755-1315/63/1/012005

[243]	Combinatorial double auctions for multiple microgrid trading Electrical Engineering, 2017 DOI:10.1007/s00202-017-0570-y

[244]	Smart grid integration of micro hybrid power system using 6-switched 3-level inverter 2017 5th International Istanbul Smart Grid and Cities Congress and Fair (ICSG), 2017 DOI:10.1109/SGCF.2017.7947625

[245]	Accurate Short-Term Power Forecasting of Wind Turbines: The Case of Jeju Island’s Wind Farm Energies, 2017 DOI:10.3390/en10060812

[246]	Optimized hybrid wind power generation with forecasting algorithms and battery life considerations 2017 IEEE Power and Energy Conference at Illinois (PECI), 2017 DOI:10.1109/PECI.2017.7935735

[247]	Modelling the variability of the wind energy resource on monthly and seasonal timescales Renewable Energy, 2017 DOI:10.1016/j.renene.2017.07.019

[248]	A methodology to assess home PV capacity to mitigate wind power forecasting errors 2017 International Young Engineers Forum (YEF-ECE), 2017 DOI:10.1109/YEF-ECE.2017.7935639

[249]	Comparative investigation of short-term wind speed forecasting models for airborne wind turbines 2017 8th International Conference on Mechanical and Aerospace Engineering (ICMAE), 2017 DOI:10.1109/ICMAE.2017.8038688

[250]	Short term solar insolation prediction: P-ELM approach International Journal of Parallel, Emergent and Distributed Systems, 2017 DOI:10.1080/17445760.2017.1404601

[251]	Wind speed time series reconstruction using a hybrid neural genetic approach IOP Conference Series: Earth and Environmental Science, 2017 DOI:10.1088/1755-1315/93/1/012020

[252]	Multi-step Ahead Wind Forecasting Using Nonlinear Autoregressive Neural Networks Energy Procedia, 2017 DOI:10.1016/j.egypro.2017.09.609

[253]	Short Term Wind Power Prediction Based on Improved Kriging Interpolation, Empirical Mode Decomposition, and Closed-Loop Forecasting Engine Sustainability, 2017 DOI:10.3390/su9112104

[254]	Simulation of Wind-Battery Microgrid Based on Short-Term Wind Power Forecasting Applied Sciences, 2017 DOI:10.3390/app7111142

[255]	Different Models for Forecasting Wind Power Generation: Case Study Energies, 2017 DOI:10.3390/en10121976

[256]	Forecasting of wind speed using ANN, ARIMA and Hybrid models 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), 2017 DOI:10.1109/ICICICT1.2017.8342555

[257]	Cost minimization in multi wind farm power dispatch 2017 6th International Conference on Computer Applications In Electrical Engineering-Recent Advances (CERA), 2017 DOI:10.1109/CERA.2017.8343325

[258]	A Nonlinear Autoregressive Neural Network Model for Short-Term Wind Forecasting 2017 9th IEEE-GCC Conference and Exhibition (GCCCE), 2017 DOI:10.1109/IEEEGCC.2017.8447983

[259]	Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods Renewable and Sustainable Energy Reviews, 2017 DOI:10.1016/j.rser.2016.09.063

[260]	DEEPSO to predict wind power and electricity market prices series in the short-term 2016 51st International Universities Power Engineering Conference (UPEC), 2016 DOI:10.1109/UPEC.2016.8114070

[261]	Intelligent energy management control for independent microgrid Sādhanā, 2016 DOI:10.1007/s12046-016-0515-6

[262]	K-means clustering with a new initialization approach for wind power forecasting 2016 IEEE/PES Transmission and Distribution Conference and Exposition (T&D), 2016 DOI:10.1109/TDC.2016.7519931

[263]	Enhanced Forecasting Approach for Electricity Market Prices and Wind Power Data Series in the Short-Term Energies, 2016 DOI:10.3390/en9090693

[264]	A new wind power model using the lightning search algorithm 2016 HONET-ICT, 2016 DOI:10.1109/HONET.2016.7753427

[265]	Examining nominal and ordinal classifiers for forecasting wind speed 2016 IEEE 8th International Conference on Intelligent Systems (IS), 2016 DOI:10.1109/IS.2016.7737469

[266]	Demand forecasting in residential distribution feeders in the context of smart grids 2016 12th IEEE International Conference on Industry Applications (INDUSCON), 2016 DOI:10.1109/INDUSCON.2016.7874464

[267]	Short term wind power prediction using ANFIS 2016 IEEE International Conference on Power and Renewable Energy (ICPRE), 2016 DOI:10.1109/ICPRE.2016.7871238

[268]	Most influential parametrical and data needs for realistic wind speed prediction Renewable Energy, 2016 DOI:10.1016/j.renene.2016.03.011

[269]	Enhanced Forecasting Approach for Electricity Market Prices and Wind Power Data Series in the Short-Term Energies, 2016 DOI:10.3390/en9090693

[270]	Short Term Wind Power Generation Forecasting Using Adaptive Network-Based Fuzzy Inference System 2015 International Conference on Computational Intelligence and Communication Networks (CICN), 2015 DOI:10.1109/CICN.2015.249

[271]	Wind speed prediction in the mountainous region of India using an artificial neural network model Renewable Energy, 2015 DOI:10.1016/j.renene.2015.02.034

[272]	Short-term wind power prediction based on Hybrid Neural Network and chaotic shark smell optimization International Journal of Precision Engineering and Manufacturing-Green Technology, 2015 DOI:10.1007/s40684-015-0029-4

[273]	Learning Wind Speed Forecast Model based on Numeric Prediction Algorithm Journal of the Korea Society of Computer and Information, 2015 DOI:10.9708/jksci.2015.20.3.019

[274]	A Review of EV Load Scheduling with Wind Power Integration*This work is supported in part by NSFC (61222302, 61174072, 61221063, 91224008, and U1301254), 111 International Collaboration Program of China (B06002), the National Key Technology R&D Program (2013BAG18B00), TNList Funding for Cross Disciplinary Research, TNList Funding for Excellent Young Scholar, and the Program for New Star of Science and Technology in Beijing (No. xx2014B056). Q.-S. Jia is the corresponding author. IFAC-PapersOnLine*, 2015 DOI:10.1016/j.ifacol.2015.12.129

[275]	Wind power potential assessment of 12 locations in western Himalayan region of India Renewable and Sustainable Energy Reviews, 2014 DOI:10.1016/j.rser.2014.07.050

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