Wind Power Short-Term Time-Series Prediction Using an Ensemble of Neural Networks

Wind Power Short-Term Time-Series Prediction Using an Ensemble of Neural Networks

Short-term wind power forecasting has difficult problems due to the very large variety of speeds of the wind, which is a key factor in producing energy. From the point of view of the whole country, an important problem is predicting the total impact of wind power’s contribution to the country’s ener...

Full description

Bibliographic Details
Main Authors:	Tomasz Ciechulski, Stanisław Osowski
Format:	Article
Language:	English
Published:	MDPI AG 2024-01-01
Series:	Energies
Subjects:	wind power forecasting neural networks LSTM ensemble of predictors
Online Access:	https://www.mdpi.com/1996-1073/17/1/264

Similar Items

Neural Approaches to Short-Time Load Forecasting in Power Systems—A Comparative Study
by: Stanislaw Osowski, et al.
Published: (2022-04-01)

High Precision LSTM Model for Short-Time Load Forecasting in Power Systems
by: Tomasz Ciechulski, et al.
Published: (2021-05-01)

Deep Learning Approach to Power Demand Forecasting in Polish Power System
by: Tomasz Ciechulski, et al.
Published: (2020-11-01)

Time-consistent calibration of short-term regional wind power ensemble forecasts
by: Stephan Späth, et al.
Published: (2015-04-01)

Two‐stage short‐term wind power forecasting algorithm using different feature-learning models
by: Jiancheng Qin, et al.
Published: (2021-07-01)

Local dynamic integration of ensemble in prediction of time series
by: S. Osowski, et al.
Published: (2019-06-01)

A Long-Term Wind Speed Ensemble Forecasting System with Weather Adapted Correction
by: Yiqi Chu, et al.
Published: (2016-10-01)

Short-term wind power forecasting through stacked and bi directional LSTM techniques
by: Mehmood Ali Khan, et al.
Published: (2024-03-01)

An ensemble model for short-term wind power prediction based on EEMD-GRU-MC
by: Peilin Wang, et al.
Published: (2024-01-01)

Deep convolutional long short-term memory for forecasting wind speed and direction
by: Anggraini Puspita Sari, et al.
Published: (2021-06-01)

Stacking Ensemble Method with the RNN Meta-Learner for Short-Term PV Power Forecasting
by: Andi A. H. Lateko, et al.
Published: (2021-08-01)

An Adaptive, Data-Driven Stacking Ensemble Learning Framework for the Short-Term Forecasting of Renewable Energy Generation
by: Hui Huang, et al.
Published: (2023-02-01)

Wind Speed Multi-Mode Ensemble Forecasting for Wind Farms Based on Machine Learning
by: Sheng GAO, et al.
Published: (2024-01-01)

A Deep Learning Framework for Day Ahead Wind Power Short-Term Prediction
by: Peihua Xu, et al.
Published: (2023-03-01)

Physical approach to short-term wind power prediction /
by: 186201 Lange, Matthias, et al.
Published: (2005)

Enhancing wind power forecasting accuracy through LSTM with adaptive wind speed calibration (C-LSTM)
by: Ding Wang, et al.
Published: (2025-02-01)

Investigation of the Features Influencing the Accuracy of Wind Turbine Power Calculation at Short-Term Intervals
by: Pavel V. Matrenin, et al.
Published: (2024-10-01)

Evaluating ensemble post‐processing for wind power forecasts
by: Kaleb Phipps, et al.
Published: (2022-08-01)

Short-term wind power forecasting using integrated boosting approach
by: Ubaid Ahmed, et al.
Published: (2024-05-01)

Effects of wind speed and wind direction on crop yield forecasting using dynamic time warping and an ensembled learning model
by: Bright Bediako-Kyeremeh, et al.
Published: (2024-06-01)

A Fuzzy Seasonal Long Short-Term Memory Network for Wind Power Forecasting
by: Chin-Wen Liao, et al.
Published: (2021-05-01)

A Multi-View Ensemble Width-Depth Neural Network for Short-Term Wind Power Forecasting
by: Jing Wan, et al.
Published: (2022-05-01)

The Schaake Shuffle Technique to Combine Solar and Wind Power Probabilistic Forecasting
by: Stefano Alessandrini, et al.
Published: (2020-05-01)

A Novel Ensemble Wind Speed Forecasting System Based on Artificial Neural Network for Intelligent Energy Management
by: Merve Erkinay Ozdemir
Published: (2024-01-01)

Adapting Ensemble‐Calibration Techniques to Probabilistic Solar‐Wind Forecasting
by: N. O. Edward‐Inatimi, et al.
Published: (2024-12-01)

Modeling of Ultra-Short Term Offshore Wind Power Prediction Based on Condition-Assessment of Wind Turbines
by: Suo Li, et al.
Published: (2021-02-01)

Wind Power Forecasting Using Neural Network Ensembles With Feature Selection
by: Li, Song, et al.
Published: (2016)

A Short-Term Calgorithm Based on Improved LSTM Neural Network
by: Sheng GAO, et al.
Published: (2024-01-01)

Wind Power Prediction Method Based on Long Short-term Memory Neural Network
by: Xiangjun LI, et al.
Published: (2019-10-01)

Optimising the use of ensemble information in numerical weather forecasts of wind power generation
by: J Stanger, et al.
Published: (2019-01-01)

Conv‐ELSTM: An ensemble deep learning approach for predicting short‐term wind power
by: Guibin Wang, et al.
Published: (2024-12-01)

Medium- and Long-Term Wind-Power Forecasts, Considering Regional Similarities
by: Xianxun Wang, et al.
Published: (2023-02-01)

Ultra-Short-Term Wind Power Prediction Based on eEEMD-LSTM
by: Jingtao Huang, et al.
Published: (2024-01-01)

Ensemble machine learning model for forecasting wind farm generation
by: A. G. Rusina, et al.
Published: (2024-04-01)

Optimization of Feedforward Neural Networks Using an Improved Flower Pollination Algorithm for Short-Term Wind Speed Prediction
by: Yidi Ren, et al.
Published: (2019-10-01)

Short-term prediction of the power of a new wind turbine based on IAO-LSTM
by: Zheng Li, et al.
Published: (2022-11-01)

Quantile Regression Post-Processing of Weather Forecast for Short-Term Solar Power Probabilistic Forecasting
by: Luca Massidda, et al.
Published: (2018-07-01)

Ultra-Short-Term Wind Power Combined Prediction Based on Complementary Ensemble Empirical Mode Decomposition, Whale Optimisation Algorithm, and Elman Network
by: Anfeng Zhu, et al.
Published: (2022-04-01)

Deterministic and Probabilistic Prediction of Wind Power Based on a Hybrid Intelligent Model
by: Jiawei Zhang, et al.
Published: (2023-05-01)

Short-term output prediction of wind-photovoltaic power based on time-frequency decomposition
by: Yangfan Zhang, et al.
Published: (2025-01-01)