ADP-Based Decentralized Load Frequency Control Schemes to Multiarea Asynchronous Markov Jumping Power Systems With Experience Replay

This article investigates the problem of robust decentralized load frequency control (LFC) in multiarea interconnection power systems, in the presence of the external disturbances and stochastic abrupt variations, such as component failures and different load demands. To capture the different operating conditions of the load in the multiarea power systems, a Markov superposition technique is skillfully employed to model the system's component matrices. To solve the Nash equilibrium solution of the zero-sum differential game problem, an improved online adaptive dynamic programming (ADP) algorithm based on the experience replay technique (ERT) is developed, which addresses the nonlinear coupling difficulties encountered in solving the game algebraic Riccati equations (Game AREs). The proposed algorithm weakens the condition that traditional policy iteration online solutions of zero-sum games require an initial stabilizing control policy pair, and considers the fact that only the transition probability matrix is known, while the prior knowledge of the dynamics is completely unknown. The algorithm is used to obtain both a minimum LFC and maximum disturbance policy for a given disturbance rejection level. Additionally, a safer LFC controller of the power systems with the Markov jumping parameters is designed. The stability and convergence of the proposed algorithm are demonstrated. Finally, the effectiveness and good performance of the proposed design method are validated using a two-area four-mode simulation example.

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Publication Details

Journal
IEEE Transactions on Cybernetics
Published
2024-08-26
DOI
https://doi.org/10.1109/tcyb.2024.3443867
Citations
11
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
3.61

Funders

Controls
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article

ADP-Based Decentralized Load Frequency Control Schemes to Multiarea Asynchronous Markov Jumping Power Systems With Experience Replay

Xuan Qiu, Shengda Tang, Iyad Katib, Hai Wang et al.
11 citations
IEEE Transactions on Cybernetics
Microgrid Control and Optimization
3.61
article

ADP-Based Decentralized Load Frequency Control Schemes to Multiarea Asynchronous Markov Jumping Power Systems With Experience Replay

Xuan Qiu, Shengda Tang, Iyad Katib, Hai Wang, Jun Cheng
article en
11 citations

Abstract

This article investigates the problem of robust decentralized load frequency control (LFC) in multiarea interconnection power systems, in the presence of the external disturbances and stochastic abrupt variations, such as component failures and different load demands. To capture the different operating conditions of the load in the multiarea power systems, a Markov superposition technique is skillfully employed to model the system's component matrices. To solve the Nash equilibrium solution of the zero-sum differential game problem, an improved online adaptive dynamic programming (ADP) algorithm based on the experience replay technique (ERT) is developed, which addresses the nonlinear coupling difficulties encountered in solving the game algebraic Riccati equations (Game AREs). The proposed algorithm weakens the condition that traditional policy iteration online solutions of zero-sum games require an initial stabilizing control policy pair, and considers the fact that only the transition probability matrix is known, while the prior knowledge of the dynamics is completely unknown. The algorithm is used to obtain both a minimum LFC and maximum disturbance policy for a given disturbance rejection level. Additionally, a safer LFC controller of the power systems with the Markov jumping parameters is designed. The stability and convergence of the proposed algorithm are demonstrated. Finally, the effectiveness and good performance of the proposed design method are validated using a two-area four-mode simulation example.

IEEE Transactions on CyberneticsVol. 54(11)
King Abdulaziz University (SA), Guangxi Normal University (CN), Chongqing Vocational Institute of Engineering (CN)
Natural Science Foundation of Guangxi Zhuang Autonomous Region, Franchise Education and Research Foundation
Affordable and clean energy
Openalex Percentile: Top 7%
Microgrid Control and Optimization
3.61
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