P Yu, Z Wang, H Zhang, Y Song - arXiv preprint arXiv:2407.00681, 2024 - arxiv.org
The large-scale integration of intermittent renewable energy resources introduces increased uncertainty and volatility to the supply side of power systems, thereby complicating system …
With the rise in electricity, gas and oil prices and the persistently high levels of carbon emissions, there is an increasing demand for effective energy management in energy …
Y Zhou, L Zhou, Z Yi, D Shi, M Guo - IEEE Access, 2024 - ieeexplore.ieee.org
The power grids nowadays are facing increasing complexity and uncertainty due to the continuously growing penetration of renewable energy sources, such as photovoltaic (PV) …
Y Wei, M Tian, X Huang, Z Ding - 2022 IEEE/IAS Industrial and …, 2022 - ieeexplore.ieee.org
With the widespread use of reinforcement learning (RL) in the energy system, the damage to the system caused by the agents' stochastic exploration is beginning to be appreciated. We …
Renewable generation is leading to rapidly shifting power flows and it is anticipated that traditional power system control may soon be inadequate to cope with these fluctuations …
X Chen, G Qu, Y Tang, S Low… - arXiv preprint arXiv …, 2021 - authors.library.caltech.edu
With large-scale integration of renewable generation and distributed energy resources (DERs), modern power systems are confronted with new operational challenges, such as …
With large-scale integration of renewable generation and distributed energy resources, modern power systems are confronted with new operational challenges, such as growing …
M Eichelbeck, H Markgraf, M Althoff - arXiv preprint arXiv:2406.03231, 2024 - arxiv.org
The growing complexity of power system management has led to an increased interest in the use of reinforcement learning (RL). However, no tool for comprehensive and realistic …
The climate crisis necessitates a global shift to achieve a secure, sustainable, and affordable energy system toward a green energy transition reaching climate neutrality by 2050 …