Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A scalable graph reinforcement learning algorithm based stochastic dynamic dispatch of power system under high penetration of renewable energy
Junbin Chen, Tao Yu, Zhenning Pan, et al.
International Journal of Electrical Power & Energy Systems (2023) Vol. 152, pp. 109212-109212
Open Access | Times Cited: 18

Showing 18 citing articles:

Reinforcement Learning-Driven Proximal Policy Optimization-Based Voltage Control for PV and WT Integrated Power System
Anis Ur Rehman, Zia Ullah, Hasan Saeed Qazi, et al.
Renewable Energy (2024) Vol. 227, pp. 120590-120590
Closed Access | Times Cited: 9
A Review on Economic Dispatch of Power System Considering Atmospheric Pollutant Emissions
Hengzhen Wang, Ying Xu, Zhongkai Yi, et al.
Energies (2024) Vol. 17, Iss. 8, pp. 1878-1878
Open Access | Times Cited: 4
Golden eagle optimization algorithm embedded in gated Kolmogorov-Arnold network for transient stability preventive control of power systems
Linfei Yin, Wei Gao Ge, R.-W. Liu
Energy (2025), pp. 134931-134931
Closed Access
Soft Open Points Scheduling in Unbalanced Active Distribution Networks Based on Multi-agent Graph Reinforcement Learning
Liu Hong, Li Qizhe, Qiang Zhang, et al.
Sustainable Energy Grids and Networks (2025), pp. 101689-101689
Closed Access
Optimal Power Flow for High Spatial and Temporal Resolution Power Systems with High Renewable Energy Penetration Using Multi-Agent Deep Reinforcement Learning
Liangcai Zhou, Long Huo, Linlin Liu, et al.
Energies (2025) Vol. 18, Iss. 7, pp. 1809-1809
Open Access
Reward shaping-based deep reinforcement learning for look-ahead dispatch with rolling-horizon
Hongsheng Xu, Yungui Xu, Ke Wang, et al.
International Journal of Electrical Power & Energy Systems (2025) Vol. 168, pp. 110673-110673
Closed Access
A data-physical fusion method for economic dispatch considering high renewable penetration and security constraints
Yuchen Dai, Wei Xu, Xiaokang Wu, et al.
International Journal of Electrical Power & Energy Systems (2025) Vol. 168, pp. 110691-110691
Closed Access
Dynamic adaptive event detection strategy based on power change-point weighting model
Gang Wang, Zhao Li, Zhao Luo, et al.
Applied Energy (2024) Vol. 361, pp. 122850-122850
Closed Access | Times Cited: 3
Stochastic dynamic power dispatch with high generalization and few-shot adaption via contextual meta graph reinforcement learning
Zhanhong Huang, Changyuan Yu, Zhenning Pan, et al.
International Journal of Electrical Power & Energy Systems (2024) Vol. 162, pp. 110272-110272
Open Access | Times Cited: 3
Reinforcement Learning for Efficient Power Systems Planning: A Review of Operational and Expansion Strategies
Gabriel Pesántez, Wilian Guamán, José Córdova, et al.
Energies (2024) Vol. 17, Iss. 9, pp. 2167-2167
Open Access | Times Cited: 2
Mobileception-ResNet for transient stability prediction of novel power systems
Linfei Yin, Wei Gao Ge
Energy (2024), pp. 133163-133163
Closed Access | Times Cited: 1
A topology-guided high-quality solution learning framework for security-constraint unit commitment based on graph convolutional network
Liqian Gao, Lishen Wei, Shichang Cui, et al.
International Journal of Electrical Power & Energy Systems (2024) Vol. 164, pp. 110322-110322
Open Access | Times Cited: 1
Stochastic Dynamic Power Dispatch With Human Knowledge Transfer Using Graph-GAN Assisted Inverse Reinforcement Learning
Junbin Chen, Tao Yu, Zhenning Pan, et al.
IEEE Transactions on Smart Grid (2023) Vol. 15, Iss. 3, pp. 3303-3315
Closed Access | Times Cited: 3
Reward Shaping-Based Deep Reinforcement Learning for Look-Ahead Dispatch with Dynamic Horizons
Hongsheng Xu, Yungui Xu, Yaping Li, et al.
(2024)
Closed Access
A Data-Physical Fusion Method for Economic Dispatch Considering High Renewable Penetration and Security Constraints
Dai Yuchen, Wei Xu, Xiaokang Wu, et al.
(2024)
Closed Access
A novel improved harbor seal whiskers algorithm for solving hybrid dynamic economic environmental dispatch considering uncertainty of renewable energy generation
Wisam Najm Al-Din Abed
e-Prime - Advances in Electrical Engineering Electronics and Energy (2024) Vol. 9, pp. 100685-100685
Open Access
Artificial intelligence driving perception, cognition, decision‐making and deduction in energy systems: State‐of‐the‐art and potential directions
Zhaoyang Dong, Tianjing Wang
Energy internet. (2024) Vol. 1, Iss. 1, pp. 27-33
Open Access
Applications of deep reinforcement learning in nuclear energy: A review
Yong‐Chao Liu, Bo Wang, Sichao Tan, et al.
Nuclear Engineering and Design (2024) Vol. 429, pp. 113655-113655
Closed Access
Page 1

Scroll to top