Source-Load Joint Probability Prediction Based on Transformer Model-Reference-Cited by-同舟云学术

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Source-Load Joint Probability Prediction Based on Transformer Model

Published:2022-05-27 Issue: Volume: Page:
ISSN:
Container-title:2022 5th International Conference on Artificial Intelligence and Big Data (ICAIBD)
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Author:

Hu Pingzhao¹,Shan Xin²,Hu Diangang³,Fu Jiayu³,Wang Chen¹,Zhang Kaifeng¹

Affiliation:

1. Southeast University,Key Laboratory of Measurement and Control of CSE, Ministry of Education,Nanjing

2. NARI Group (State Grid Electric Power Research Institute) Co. Ltd., State Grid NARI Technology Co., Ltd., State Key Laboratory of Smart, Grid Protection and Operation Control,Nanjing,China

3. State Grid Gansu Electric Power Co. Ltd.,Gansu,China

Funder

State Grid Corporation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9819953/9819974/09820171.pdf?arnumber=9820171

Reference14 articles.

1. Prediction intervals forecasts of electricity price based on Dynamic Bayesian networks;wang;Proceedings of the CSU-EPSA,0

2. On Accuracy Estimation Using Parametric Bootstrap in small Area Prediction Problems;??d?o;Journal of Official Statistics,2020

3. A Novel Twin Support Vector Machine with Generalized Pinball Loss Function for Pattern Classification;wanida;Symmetry,2022

4. A Comparison on PSO Optimized PID Controller for Inter-Area Oscillation Control in an Interconnected Power System

5. Probabilistic Forecasting of Wind Power Generation Using Extreme Learning Machine

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