Artificial intelligence-based methods for renewable power system operation

Y Li, Y Ding, S He, F Hu, J Duan, G Wen… - Nature Reviews …, 2024 - nature.com
Carbon neutrality goals are driving the increased use of renewable energy (RE). Large-
scale use of RE requires accurate energy generation forecasts; optimized power dispatch …

Safe Reinforcement Learning for Power System Control: A Review

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 …

Online Multi-Objective Optimization for Electric Vehicle Charging Station Operation

Y Li, J Duan, L Pan, T Ishizaki, L Gao… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
With the increasing development of electric vehicles (EVs), their demand for charging has
increased. To satisfy their demand with limited public charging posts while minimizing their …

Knowledge-network-embedded deep reinforcement learning: An innovative way to high-efficiently develop an energy management strategy for the integrated energy …

B Jia, F Li, B Sun - Energy, 2024 - Elsevier
To achieve efficient energy management in complex integrated energy systems (IESs) with
renewable energy sources (RESs) and multiple energy storage systems (ESSs), the study …

[HTML][HTML] Reinforcement learning for an enhanced energy flexibility controller incorporating predictive safety filter and adaptive policy updates

S Paesschesoone, N Kayedpour, C Manna… - Applied Energy, 2024 - Elsevier
This paper presents a novel data-driven approach that leverages reinforcement learning to
enhance the efficiency and safety of existing energy flexibility controllers, addressing …

FRMNet: A Feasibility Restoration Mapping Deep Neural Network for AC Optimal Power Flow

J Han, W Wang, C Yang, M Niu, C Yang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Increasing renewable energy resources introduces uncertainties into utility grids, calling for
more frequent use of alternative current optimal power flow (AC-OPF) than before …

Multi-objective explainable smart dispatch for integrated energy system based on an explainable MO-RL method

J Dou, X Wang, Z Liu, Z Jiao, Y Han, Q Sun… - Computers and Electrical …, 2024 - Elsevier
With the rapid development of renewable energy penetration and the transition to high-
efficiency, low-carbon-footprint energy systems, renewable-based heat-electricity integrated …

Distributed Remote Secure ADP-Based Control for Interconnected Power Systems Under Cyber-Attacks

L Zhang, Y Chen… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
The interconnected power systems (IPSs) generally with complex communication topology
are sensitive to cyber-attacks. In this article, the problem of cyber-attacks on the IPSs is …

A computational efficient approach for distributionally robust unit commitment with enhanced disjointed layered ambiguity set

Y Lian, Y Li, Y Zhao, Y Li, Z Liu… - IET Renewable Power …, 2024 - Wiley Online Library
To achieve the sustainable development of the society, renewable energy dominated power
systems are gradually formed. However, the uncertainty of renewable power poses …

Towards intelligent emergency control for large-scale power systems: Convergence of learning, physics, computing and control

Q Huang, R Huang, T Yin, S Datta, X Sun, J Hou… - Electric Power Systems …, 2024 - Elsevier
This paper has delved into the pressing need for intelligent emergency control in large-scale
power systems, which are experiencing significant transformations and are operating closer …