A scalable graph reinforcement learning algorithm based stochastic dynamic dispatch of power system under high penetration of renewable energy-Reference-Cited by-同舟云学术

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A scalable graph reinforcement learning algorithm based stochastic dynamic dispatch of power system under high penetration of renewable energy

Published:2023-10 Issue: Volume:152 Page:109212
ISSN:0142-0615
Container-title:International Journal of Electrical Power & Energy Systems
language:en
Short-container-title:International Journal of Electrical Power & Energy Systems

Author:

Chen Junbin,Yu Tao,Pan Zhenning,Zhang Mengyue,Deng Bairong

Funder

State Grid Corporation of China

National Natural Science Foundation of China - State Grid Corporation Joint Fund for Smart Grid

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference39 articles.

1. Smart energy systems for coherent 100% renewable energy and transport solutions;Mathiesen;Appl Energy,2015

2. Collaborative optimization of dynamic grid dispatch with wind power;Liu;Int J Electr Power Energy Syst,2021

3. Compressive Sensing Based Stochastic Economic Dispatch With High Penetration Renewables;Li;IEEE Trans Power Syst,2019

4. A GAN-based fully model-free learning method for short-term scheduling of large power system;Guan;IEEE Trans Power Syst,2022

5. An online optimal dispatch schedule for CCHP microgrids based model predictive control;Gu;IEEE Trans Smart Grid,2017

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