相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。Probabilistic spatiotemporal wind speed forecasting based on a variational Bayesian deep learning model
Yongqi Liu et al.
APPLIED ENERGY (2020)
Probabilistic Forecasting of Battery Energy Storage State-of-Charge under Primary Frequency Control
Aleksei Mashlakov et al.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (2020)
Using Bayesian Deep Learning to Capture Uncertainty for Residential Net Load Forecasting
Mingyang Sun et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2020)
Learning Temporal and Spatial Correlations Jointly: A Unified Framework for Wind Speed Prediction
Qiaomu Zhu et al.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2020)
Convolutional Graph Autoencoder: A Generative Deep Neural Network for Probabilistic Spatio-Temporal Solar Irradiance Forecasting
Mandi Khodayar et al.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2020)
Short-term global horizontal irradiance forecasting based on a hybrid CNN-LSTM model with spatiotemporal correlations
Haixiang Zang et al.
RENEWABLE ENERGY (2020)
Spatio-Temporal Graph Deep Neural Network for Short-Term Wind Speed Forecasting
Mahdi Khodayar et al.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2019)
Deep Learning-Based Multivariate Probabilistic Forecasting for Short-Term Scheduling in Power Markets
Jean-Francois Toubeau et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2019)
Open Power System Data - Frictionless data for electricity system modelling
Frauke Wiese et al.
APPLIED ENERGY (2019)
Multifactor spatio-temporal correlation model based on a combination of convolutional neural network and long short-term memory neural network for wind speed forecasting
Yong Chen et al.
ENERGY CONVERSION AND MANAGEMENT (2019)
Temporal pattern attention for multivariate time series forecasting
Shun-Yao Shih et al.
MACHINE LEARNING (2019)
Renewable generation forecast studies - Review and good practice guidance
Carsten Croonenbroeck et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2019)
Bayesian deep learning based method for probabilistic forecast of day-ahead electricity prices
Alessandro Brusaferri et al.
APPLIED ENERGY (2019)
A comparison of day-ahead photovoltaic power forecasting models based on deep learning neural network
Kejun Wang et al.
APPLIED ENERGY (2019)
A review of deep learning for renewable energy forecasting
Huaizhi Wang et al.
ENERGY CONVERSION AND MANAGEMENT (2019)
Deep ensemble learning based probabilistic load forecasting in smart grids
Yandong Yang et al.
ENERGY (2019)
Benefits of spatiotemporal modeling for short-term wind power forecasting at both individual and aggregated levels
Amanda Lenzi et al.
ENVIRONMETRICS (2018)
Recent advances in electricity price forecasting: A review of probabilistic forecasting
Jakub Nowotarski et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2018)
Review on probabilistic forecasting of photovoltaic power production and electricity consumption
D. W. van der Meer et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2018)
Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry
Ricardo J. Bessa et al.
ENERGIES (2017)
Deep learning based ensemble approach for probabilistic wind power forecasting
Huai-zhi Wang et al.
APPLIED ENERGY (2017)
Generation and evaluation of space-time trajectories of photovoltaic power
Faranak Golestaneh et al.
APPLIED ENERGY (2016)
Probabilistic electric load forecasting: A tutorial review
Tao Hong et al.
INTERNATIONAL JOURNAL OF FORECASTING (2016)
Gaussian processes for time-series modelling
S. Roberts et al.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES (2013)
Probabilistic forecasts, calibration and sharpness
Tilmann Gneiting et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2007)
25 years of time series forecasting
Jan G. De Gooijer et al.
INTERNATIONAL JOURNAL OF FORECASTING (2006)
Multivariate GARCH models: A survey
L Bauwens et al.
JOURNAL OF APPLIED ECONOMETRICS (2006)
Support vector machine with adaptive parameters in financial time series forecasting
LJ Cao et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2003)
分享论文
