The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
A Multi-Agent Deep Reinforcement Learning Method for Cooperative Load Frequency Control of a Multi-Area Power System
Abstract
This paper proposes a data-driven cooperative method for load frequency control (LFC) of the multi-area power system based on multi-agent deep reinforcement learning (MA-DRL) in continuous action domain. The proposed method can nonlinearly and adaptively derive the optimal coordinated control strategies for multiple LFC controllers through centralized learning and decentralized implementation. The centralized learning is achieved by MA-DRL based on a global action-value function to quantify overall LFC performance of the power system. To solve the MA-DRL problem, multi-agent deep deterministic policy gradient (DDPG) is derived to adjust control agents' parameters considering the nonlinear generator behaviors. For implementation, each individual controller only needs local information in its control area to deliver optimal control signals. Numerical simulations on a three-area power system and the fully-modeled New-England 39-bus system demonstrate that the proposed method can effectively minimize control errors against stochastic frequency variations caused by load and renewable power fluctuations.
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Cites
Continuous control with deep reinforcement learning
Lillicrap, T. P., Hunt, J. J., Pritzel, A., Heess, N., Erez, T., Tassa, Y., Silver, D., & Wierstra, D. (2015) · arXiv · doi:10.48550/arxiv.1509.02971 · Cited by 10,782
(2010) · Journal of Machine Learning Research · doi:10.5555/1756006.1953039 · Cited by 4,051
Transfer Learning for Reinforcement Learning Domains: A Survey
Taylor, M. E., & Stone, P. (2009) · doi:10.5555/1577069.1755839 · Cited by 1,488
Robust Power System Frequency Control
Bevrani, H. (2009) · Springer eBooks · doi:10.1007/978-0-387-84878-5 · Cited by 1,164
Robust Power System Frequency Control
Bevrani, H. (2014) · Power Electronics and Power Systems · doi:10.1007/978-3-319-07278-4 · Cited by 571
Unified Tuning of PID Load Frequency Controller for Power Systems via IMC
Tan, W. (2010) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2009.2036463 · Cited by 526
Yan, Z., & Xu, Y. (2019) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2018.2881359 · Cited by 387
Self-citationLoad Frequency Control of a Multi-Area Power System: An Adaptive Fuzzy Logic Approach
Yousef, H. A., AL-Kharusi, K., Albadi, M. H., & Hosseinzadeh, N. (2014) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2013.2297432 · Cited by 314
Model Predictive Load-Frequency Control
Ersdal, A. M., Imsland, L., & Uhlen, K. (2015) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2015.2412614 · Cited by 285
Vachirasricirikul, S., & Ngamroo, I. (2014) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2013.2264921 · Cited by 254
Cited by
A review of control techniques for inverter-based distributed energy resources applications
Hasheminasab, S., Alzayed, M., & Chaoui, H. (2024) · Energies · doi:10.3390/en17122940 · Cited by 56
Zeng, Y., Bu, X., & Yin, Y. (2025) · Asian Journal of Control · doi:10.1002/asjc.3481 · Cited by 7
Metadata
- Authors
- Yan, Z., & Xu, Y.
- Venue
- IEEE Transactions on Power Systems
- Published
- 2020-11
- Volume
- 35
- Issue
- 6
- Pages
- 4599-4608
- ISSN
- 0885-8950 (ISSN-L)
- 1558-0679
- OpenAlex
- W3033672499
- Cited by
- 398
- References
- 18
- FWCI
- 14.60
- Type
- journal article
- Language
- en
- Open access
- closed
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