Very‐short‐term load forecasting based on empirical mode decomposition and deep neural network-Reference-Cited by-同舟云学术

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Very‐short‐term load forecasting based on empirical mode decomposition and deep neural network

Published:2019-11-12 Issue:2 Volume:15 Page:252-258
ISSN:1931-4973
Container-title:IEEJ Transactions on Electrical and Electronic Engineering
language:en
Short-container-title:IEEJ Trans Elec Electron Eng

Author:

Cheng Li‐Min¹,Bao Yu‐Qing¹,Tang Lai²,Di Hui‐Fang²

Affiliation:

1. NARI School of Electrical Engineering and AutomationNanjing Normal University, No.1 Wenyuan Road 210023 Nanjing Jiangsu Province China

2. Engineering Laboratory of Gas‐Electricity Integrated Energy of Jiangsu Province, No.1 Wenyuan Road 210023 Nanjing Jiangsu Province China

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Wiley

Subject

Electrical and Electronic Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/tee.23052

Reference25 articles.

1. Long Term Probabilistic Load Forecasting and Normalization With Hourly Information

2. Medium-term electric load forecasting using singular value decomposition

3. Short-Term Load Forecasting by Separating Daily Profiles and Using a Single Fuzzy Model Across the Entire Domain

4. Very short‐term load forecasting using artificial neural networks;Charytoniuk W;IEEE Transactions on Power Systems,2002

5. Comparison of very short-term load forecasting techniques

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