Accelerating optimal scheduling prediction in power system: A multi-faceted GAN-assisted prediction framework-Reference-Cited by-同舟云学术

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Accelerating optimal scheduling prediction in power system: A multi-faceted GAN-assisted prediction framework

Published:2024-09 Issue: Volume:230 Page:120830
ISSN:0960-1481
Container-title:Renewable Energy
language:en
Short-container-title:Renewable Energy

Author:

Peivand Ali,Azad Farsani Ehsan^ORCID,Abdolmohammadi Hamid Reza

Publisher

Elsevier BV

Reference51 articles.

1. Small signal stability analysis and optimize control of large-scale wind power collection system;Li;IEEE Access,2022

2. Application of model predictive control for active load management in a distributed power system with high wind penetration;Zong,2012

3. A new Co-optimized hybrid model based on multi-objective optimization for probabilistic wind power forecasting in a spatiotemporal framework;Kousounadis-Knousen;IEEE Access,2023

4. Scheduling electric vehicle charging to minimise carbon emissions and wind curtailment;Dixon;Renew. Energy,2020

5. Short-term wind speed forecasting over complex terrain using linear regression models and multivariable LSTM and NARX networks in the Andes Mountains, Ecuador;López;Renew. Energy,2022

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