A Novel Hybrid Method for Short-Term Probabilistic Load Forecasting in Distribution Networks-Reference-Cited by-同舟云学术

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A Novel Hybrid Method for Short-Term Probabilistic Load Forecasting in Distribution Networks

Published:2022-09 Issue:5 Volume:13 Page:3650-3661
ISSN:1949-3053
Container-title:IEEE Transactions on Smart Grid
language:
Short-container-title:IEEE Trans. Smart Grid

Author:

Wang Bingzhi¹^ORCID,Mazhari Mahdi¹^ORCID,Chung C. Y.¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, SK, Canada

Funder

Natural Sciences and Engineering Research Council (NSERC) of Canada

Saskatoon Light and Power

Saskatchewan Power Corporation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/5165411/9865089/09765577.pdf?arnumber=9765577

Reference47 articles.

1. Probabilistic forecasts, calibration and sharpness

2. Statistical Load Forecasting Using Optimal Quantile Regression Random Forest and Risk Assessment Index

3. Effective Estimation of Posterior Probabilities: Explaining the Accuracy of Randomized Decision Tree Approaches

4. Ensemble Machine Learning

5. Conjugate Bayesian analysis of the Gaussian distribution;murphy;Def,2007

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1. Deep Reinforcement Learning-Assisted Federated Learning for Robust Short-Term Load Forecasting in Electricity Wholesale Markets;IEEE Transactions on Network Science and Engineering;2024-09

2. Day-Ahead Probabilistic Load Forecasting: A Multi-Information Fusion and Noncrossing Quantiles Method;IEEE Transactions on Industrial Informatics;2024-08

3. Short-Term Residential Load Forecasting via Pooling-Ensemble Model With Smoothing Clustering;IEEE Transactions on Artificial Intelligence;2024-07

4. A hybrid prediction interval model for short-term electric load forecast using Holt-Winters and Gate Recurrent Unit;Sustainable Energy, Grids and Networks;2024-06

5. From Time-Series to Hybrid Models: Advancements in Short-Term Load Forecasting Embracing Smart Grid Paradigm;Applied Sciences;2024-05-23

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