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OpenAlex Citation Counts

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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:

Exploiting Battery Storages With Reinforcement Learning: A Review for Energy Professionals
Rakshith Subramanya, Seppo Sierla, Valeriy Vyatkin
IEEE Access (2022) Vol. 10, pp. 54484-54506
Open Access | Times Cited: 17

Showing 17 citing articles:

From DevOps to MLOps: Overview and Application to Electricity Market Forecasting
Rakshith Subramanya, Seppo Sierla, Valeriy Vyatkin
Applied Sciences (2022) Vol. 12, Iss. 19, pp. 9851-9851
Open Access | Times Cited: 39
Recent Progress of Deep Learning Methods for Health Monitoring of Lithium-Ion Batteries
Seyed Saeed Madani, Carlos Ziebert, Parisa Vahdatkhah, et al.
Batteries (2024) Vol. 10, Iss. 6, pp. 204-204
Open Access | Times Cited: 8
Deep Reinforcement Learning for the Joint Dispatch of Battery Energy Storage Systems and Gas Turbines in Microgrids with Renewable Energy
Manuel Sage, Khalil Al Handawi, Yaoyao Fiona Zhao
(2025)
Closed Access
Deep reinforcement learning for economic battery dispatch: A comprehensive comparison of algorithms and experiment design choices
Manuel Sage, Yaoyao Fiona Zhao
Journal of Energy Storage (2025) Vol. 115, pp. 115428-115428
Open Access
Economics of utility-scale batteries in Romania under various market conditions
Simona‐Vasilica Oprea, Adela Bârã
Utilities Policy (2025) Vol. 95, pp. 101939-101939
Open Access
A Multi-Agent Reinforcement Learning Approach for Continuous Battery Cell-Level Balancing
Yasaman Tavakol-Moghaddam, Mehrdad Boroushaki
Results in Engineering (2025), pp. 104898-104898
Open Access
Prioritized experience replay based deep distributional reinforcement learning for battery operation in microgrids
Deepak Kumar Panda, Oliver Turner, Saptarshi Das, et al.
Journal of Cleaner Production (2023) Vol. 434, pp. 139947-139947
Open Access | Times Cited: 8
Advanced Research Directions on AI for Energy
Claus Daniel, Jess C Gehin, K.F. Laurin-Kovitz, et al.
(2024)
Open Access | Times Cited: 2
Optimal scheduling strategy of electricity and thermal energy storage based on soft actor-critic reinforcement learning approach
Yingying Zheng, Hui Wang, Jinglong Wang, et al.
Journal of Energy Storage (2024) Vol. 92, pp. 112084-112084
Closed Access | Times Cited: 2
Suppressing active power fluctuations at PCC in grid-connection microgrids via multiple BESSs: A collaborative multi-agent reinforcement learning approach
Wangli He, Chengyuan Li, Chenhao Cai, et al.
Applied Energy (2024) Vol. 373, pp. 123858-123858
Closed Access | Times Cited: 2
Energy Storage Management for Microgrids Using n-Step Bootstrapping
Necati Aksoy, İstemihan Genç
Canadian Journal of Electrical and Computer Engineering (2023) Vol. 46, Iss. 2, pp. 107-116
Closed Access | Times Cited: 5
A Review of Reinforcement Learning-Based Powertrain Controllers: Effects of Agent Selection for Mixed-Continuity Control and Reward Formulation
Daniel Egan, Qilun Zhu, Robert Prucka
Energies (2023) Vol. 16, Iss. 8, pp. 3450-3450
Open Access | Times Cited: 4
A Reinforcement Learning controller optimizing costs and battery State of Health in smart grids
Marco Mussi, L. Pellegrino, Oscar Francesco Pindaro, et al.
Journal of Energy Storage (2024) Vol. 82, pp. 110572-110572
Open Access | Times Cited: 1
Economic Battery Storage Dispatch with Deep Reinforcement Learning from Rule-Based Demonstrations
Manuel Sage, Martin Staniszewski, Yaoyao Fiona Zhao
(2023), pp. 1-6
Closed Access | Times Cited: 3
Deep Reinforcement Learning for Economic Battery Dispatch: A Comprehensive Comparison of Algorithms and Experiment Design Choices
Manuel Sage, Yaoyao Fiona Zhao
(2024)
Closed Access
Deep Reinforcement Learning for Economic Battery Dispatch: A Comprehensive Comparison of Algorithms and Experiment Design Choices
Manuel Sage, Yaoyao Fiona Zhao
(2024)
Closed Access
Optimal Scheduled Control Operation of Battery Energy Storage System using Model-Free Reinforcement Learning
Alaa Selim
2021 IEEE Sustainable Power and Energy Conference (iSPEC) (2022), pp. 1-5
Closed Access | Times Cited: 2
Battery Energy Storage Control Using Reinforcement Learning
Elliott Basso, Yang Du
2021 IEEE International Future Energy Electronics Conference (IFEEC) (2023), pp. 1-5
Closed Access
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