A Finite State Machine Model for Business Flow in Active Distribution Networks Considering the Multi-flow Fusion Process
NOPR - NISCAIR Online Periodicals Repository
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Title |
A Finite State Machine Model for Business Flow in Active Distribution Networks Considering the Multi-flow Fusion Process
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Creator |
Liu, Keyan
Li, Zhao Cui, Zhenyu Jia, Dongli Ye, Xueshun Su, Juan |
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Subject |
Business scheduling
Cyber-physical systems Discrete state transition Distribution network fault recovery Event-level model |
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Description |
517-524
The continuous development of informatization and digitization in active distribution networks has endowed them with the characteristic of multi-flow convergence, incorporating energy flow, information flow, control flow, and business flow. The combination of multi-flow fusion and business flow modeling in active distribution networks are examined in this work, and a method for constructing business flow model that considers the process of multi-flow convergence is described. The viability of modeling business flow that incorporates the fusion process is examined by studying the interactive process of multi-flow fusion. The operating states of the network and the characteristics of business events are defined by using the finite state machine approach to create the business flow model of active distribution networks. The experimental findings show that the suggested strategy successfully captures the business flow process in active distribution networks and satisfies the requirements for practical use. This study serves as a reference for business flow modeling and the use of finite-state machine models, and it offers useful insights for optimizing and managing the functioning of active distribution networks. |
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Date |
2024-05-06T11:14:12Z
2024-05-06T11:14:12Z 2024-05 |
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Type |
Article
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Identifier |
0022-4456 (Print); 0975-1084 (Online)
http://nopr.niscpr.res.in/handle/123456789/63855 https://doi.org/10.56042/jsir.v83i5.4167 |
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Language |
en
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Publisher |
NIScPR-CSIR, India
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Source |
JSIR Vol.83(5) [May 2024]
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