Journal Article10.1109/TPWRS.2020.2999890
A Multi-Agent Deep Reinforcement Learning Method for Cooperative Load Frequency Control of a Multi-Area Power System
Ziming Yan,Yan Xu +1 more
277
TL;DR: 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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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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Review on deep learning applications in frequency analysis and control of modern power system
TL;DR: In this article, the authors reviewed the history, state-of-the-art and the future of the DL's application in power system frequency analysis and control, and the application status of DL in frequency situation awareness, frequency security and stability assessment, and frequency regulation and control were summarized.
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Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challenges
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TL;DR: In this paper , a comprehensive review of various RL techniques and how they can be applied to decision-making and control in power systems is presented, including frequency regulation, voltage control, and energy management.
Delay-dependent robust load frequency control for time delay power systems
Chuan-Ke Zhang,Lin Jiang,Qinghua Wu,Yong He,Min Wu +4 more
- 21 Jul 2013
TL;DR: In this paper, a delay-dependent robust method is proposed for analysis/synthesis of a PID-type load frequency control (LFC) scheme considering time delays, where the effect of the disturbance on the controlled output is defined as a robust performance index (RPI) of the closed-loop system.
171
An Optimized Hybrid Fractional Order Controller for Frequency Regulation in Multi-Area Power Systems
Emad A. Mohamed,Emad M. Ahmed,Ahmed Elmelegi,Mokhtar Aly,Osama Elbaksawi,Al-Attar Ali Mohamed +5 more
TL;DR: A new frequency regulation method based on employing the hybrid fractional order controller for the LFC side in coordination with the fractionalOrder proportional integral derivative (FOPID) controllers for the superconducting energy storage system (SMES) side is proposed.
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