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Probabilistic Wind Power Forecasting Resilient to Missing Values: An Adaptive Quantile Regression Approach

https://doi.org/10.2139/ssrn.4667787
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Data processing and quality verification for improved photovoltaic performance and reliability analytics
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LASSO vector autoregression structures for very short‐term wind power forecasting
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The future of forecasting for renewable energy
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The Wind Integration National Dataset (WIND) Toolkit
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Wind power prediction with missing data using Gaussian process regression and multiple imputation
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On-line quantile regression in the RKHS (Reproducing Kernel Hilbert Space) for operational probabilistic forecasting of wind power
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Probabilistic wind power forecasting based on spiking neural network
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Multi-objective wind power scenario forecasting based on PG-GAN
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Imputation of missing data from offshore wind farms using spatio-temporal correlation and feature correlation
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Regional Wind Power Probabilistic Forecasting Based on an Improved Kernel Density Estimation, Regular Vine Copulas, and Ensemble Learning
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Probabilistic load forecasting with a non-crossing sparse-group Lasso-quantile regression deep neural network
inferredcites →https://doi.org/10.1016/j.energy.2022.126420openalex-extracted
Fluctuation pattern recognition based ultra-short-term wind power probabilistic forecasting method
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Transferable wind power probabilistic forecasting based on multi-domain adversarial networks
inferredcites →https://doi.org/10.1016/j.epsr.2020.106640openalex-extracted
Missing data in wind farm time series: Properties and effect on forecasts
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Probabilistic gradient boosting machines for GEFCom2014 wind forecasting
inferredcites →https://doi.org/10.1016/j.ijforecast.2019.07.001openalex-extracted
DeepAR: Probabilistic forecasting with autoregressive recurrent networks
inferredcites →https://doi.org/10.1016/j.ijforecast.2020.04.004openalex-extracted
Online distributed learning in wind power forecasting
inferredcites →https://doi.org/10.1016/j.ijforecast.2022.12.006openalex-extracted
Wind energy forecasting with missing values within a fully conditional specification framework
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-extracted
Random Forests
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Maximum Likelihood Fitting of ARMA Models to Time Series With Missing Observations
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Reducing Bias in Observational Studies Using Subclassification on the Propensity Score
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Estimation, Prediction, and Interpolation for ARIMA Models with Missing Data
inferredcites →https://doi.org/10.1080/10629360600810434openalex-extracted
Fully conditional specification in multivariate imputation
inferredcites →https://doi.org/10.1093/bioinformatics/btr597openalex-extracted
MissForest—non-parametric missing value imputation for mixed-type data
inferredcites →https://doi.org/10.1109/jsen.2021.3061109openalex-extracted
A Two-Stage Deep Autoencoder-Based Missing Data Imputation Method for Wind Farm SCADA Data
inferredcites →https://doi.org/10.1109/mpe.2019.2932639openalex-extracted
The Use of Probabilistic Forecasts: Applying Them in Theory and Practice
inferredcites →https://doi.org/10.1109/powertech55446.2023.10202786openalex-extracted
Availability Adversarial Attack and Countermeasures for Deep Learning-based Load Forecasting
inferredcites →https://doi.org/10.1109/tpwrs.2007.901117openalex-extracted
Trading Wind Generation From Short-Term Probabilistic Forecasts of Wind Power
inferredcites →https://doi.org/10.1109/tpwrs.2010.2065818openalex-extracted
Setting the Operating Reserve Using Probabilistic Wind Power Forecasts
inferredcites →https://doi.org/10.1109/tpwrs.2013.2288100openalex-extracted
Optimal Prediction Intervals of Wind Power Generation
inferredcites →https://doi.org/10.1109/tpwrs.2020.2971607openalex-extracted
Improved Deep Mixture Density Network for Regional Wind Power Probabilistic Forecasting
inferredcites →https://doi.org/10.1109/tpwrs.2022.3146982openalex-extracted
An Integrated Missing-Data Tolerant Model for Probabilistic PV Power Generation Forecasting
inferredcites →https://doi.org/10.1109/tsg.2018.2817387openalex-extracted
Cyber Risk Analysis of Combined Data Attacks Against Power System State Estimation
inferredcites →https://doi.org/10.1109/tsg.2023.3272379openalex-extracted
Towards Resilient Energy Forecasting: A Robust Optimization Approach
inferredcites →https://doi.org/10.1109/tste.2020.3009615openalex-extracted
Towards Data Markets in Renewable Energy Forecasting
inferredcites →https://doi.org/10.1109/tste.2020.3029731openalex-extracted
PV Generation Forecasting With Missing Input Data: A Super-Resolution Perception Approach
inferredcites →https://doi.org/10.1109/tste.2021.3065117openalex-extracted
Privacy-Preserving Distributed Learning for Renewable Energy Forecasting
inferredcites →https://doi.org/10.1109/tste.2022.3141549openalex-extracted
Sparse Variational Gaussian Process Based Day-Ahead Probabilistic Wind Power Forecasting
inferredcites →https://doi.org/10.1109/tste.2022.3173147openalex-extracted
Missing-Data Tolerant Hybrid Learning Method for Solar Power Forecasting
inferredcites →https://doi.org/10.1109/tste.2022.3191330openalex-extracted
Continuous and Distribution-Free Probabilistic Wind Power Forecasting: A Conditional Normalizing Flow Approach
inferredcites →https://doi.org/10.1111/j.2517-6161.1977.tb01600.xopenalex-extracted
Maximum Likelihood from Incomplete Data Via the EM Algorithm
inferredcites →https://doi.org/10.1145/3399579.3399869openalex-extracted
Resilient Neural Forecasting Systems
inferredcites →https://doi.org/10.1146/annurev-statistics-062713-085831openalex-extracted
Probabilistic Forecasting
inferredcites →https://doi.org/10.1257/jep.15.4.143openalex-extracted
Quantile Regression
inferredcites →https://doi.org/10.2307/1533221openalex-extracted
Statistical Analysis with Missing Data
inferredcites →https://doi.org/10.2307/2288398openalex-extracted
Reducing Bias in Observational Studies Using Subclassification on the Propensity Score
inferredcites →https://doi.org/10.35833/mpce.2020.000894openalex-extracted
Data-driven Missing Data Imputation for Wind Farms Using Context Encoder
inferredcites →https://doi.org/10.48550/arxiv.1708.08349openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.1805.10572openalex-extracted
BRITS: Bidirectional Recurrent Imputation for Time Series
inferredcites →https://doi.org/10.48550/arxiv.2007.01627openalex-extracted
NeuMiss networks: differentiable programming for supervised learning with missing values
inferredcites →https://doi.org/10.48550/arxiv.2111.06581openalex-extracted
Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting
inferredcites →https://doi.org/10.48550/arxiv.2309.00803openalex-extracted
inferredcites →https://doi.org/10.1109/tsg.2024.3503554openalex-snapshot
Toward Value-Oriented Renewable Energy Forecasting: An Iterative Learning Approach
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