Intelligent Emergency Generator Rejection Schemes Based on Knowledge Fusion and Deep Reinforcement Learning

LI Zhou**, Z Lingkang, YAO Wei… - Proceedings of the …, 2023 - epjournal.csee.org.cn
Emergency control is an important means of maintaining power system transient security
and stability following serious faults. The current popular" human-in-the-loop" offline …

Architecture of intelligent decision embedding knowledge for power grid generation-load look-ahead dispatch based on deep reinforcement learning

Y Jiahao, M Wenbo, W Ke… - 2023 IEEE 6th …, 2023 - ieeexplore.ieee.org
In the construction of new power systems with renewable energy as the mainstay, the
uncertainty of the operation modes for power systems increases obviously, and the type and …

基于全生命周期管理的离网型风光储交流微电网的双层优化调度策略

徐婷婷, 吴迪凡, 王晨杰, 王佳睿, **钰, 陈润田… - 电力大 …, 2024 - epjournal.csee.org.cn
以新能源为主体的微电网系统存在前期资本投入大, 电网刚性不足等问题, 特别是离网型微电网
由于失去大电网的支撑, 安全稳定运行面临更大的挑战. 本文针对离网型交流微电网设计了双层 …

A deep reinforcement learning grid dispatching method for disconnection fault analysis and topology optimization

W Tao, B Wang, Y Han, P Chen… - … on Renewable Power …, 2023 - ieeexplore.ieee.org
With a large number of high percentage of renewable energy resources connected to the
power grid, it is challenging to apply traditional dispatching means and analysis methods to …

基于**化学**算法的微电网优化策略

**子凯, 杨波, 周忠堂, 张健, 徐明珠 - 山东电力技术, 2024 - epjournal.csee.org.cn
分布式能源具有小规模波动和间歇性的特点, 导致微电网运行策略难以制定.
微电网有效集成多种分布式能源和外部电网, 多能源微电网管理**成为一项非常复杂的任务 …

Construction Method of Power Grid Simulation Environment for Reinforcement Learning

Y Huang, N Yang, Y **, L Song… - 2023 IEEE 11th Joint …, 2023 - ieeexplore.ieee.org
In recent years, with the construction of new power systems and the gradual maturity of the
application of deep reinforcement learning technology, researchers have applied …