Distributed economic dispatch control in smart grid based on fixed-time dynamic event-triggered algorithm

This paper proposes a distributed fixed-time consensus algorithm to solve the economic dispatch problem (EDP) in smart grid. By applying this algorithm, the total generation cost can be minimized while ensuring the equation and inequality constraint. Even with unknown and bounded disturbances affect...

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Veröffentlicht in:Electric power systems research Jg. 236; S. 110933
Hauptverfasser: Ji, Lianghao, Xu, Zhenxiang, Yang, Shasha, Guo, Xing, Li, Huaqing
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.11.2024
Schlagworte:
Dynamic event-triggered scheme
Economic dispatch
Fixed-time consensus
Smart grid
Fixed-time consensus
Dynamic event-triggered scheme
Economic dispatch
Smart grid
ISSN:0378-7796
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Zusammenfassung:This paper proposes a distributed fixed-time consensus algorithm to solve the economic dispatch problem (EDP) in smart grid. By applying this algorithm, the total generation cost can be minimized while ensuring the equation and inequality constraint. Even with unknown and bounded disturbances affecting the generator system, the algorithm can achieve optimal dispatch within a fixed time and has an estimated stabilization time that is dependent of the generator’s initial conditions. Meanwhile, a static trigger function was designed to reduce the computational effort of the generators and the frequency of communication with their neighbors. Since a static threshold may result in frequent triggering, we introduced an auxiliary valuable to the static triggering condition. This allows for dynamic adjustment of the static threshold and extends the static triggering to dynamic event-triggered. Finally, the algorithm’s effectiveness is demonstrated through several examples. •We propose a distributed fixed-time dynamic event-triggered algorithm that can satisfy the inequality and equality constraints of generators. Compared with other fixed-time algorithms, the fixed-time algorithm in this paper converges faster and performs better.•When generator units face unknown and bounded disturbances, the algorithm proposed in this paper is still capable of converging within a fixed time, thereby enhancing the robustness of the algorithm.•The dynamic event-triggered method in this article, based on the static one, ensures infrequent activation of triggering conditions even as the threshold decreases, significantly reducing trigger times while maintaining convergence. Comparative experiments confirm these conclusions.
ISSN:0378-7796
DOI:10.1016/j.epsr.2024.110933