Distributed control based on tie-set graph theory for smart grid networks

Nakayama, Kiyoshi; Shinomiya, Norihiko

doi:10.1109/icumt.2010.5676490

Cited by 10 publications

(5 citation statements)

References 8 publications

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“…Agent models are commonly used for simulations, where each agent has its own decision-making power and none of them depends on any central authority [20]. Relationships and connections between agents are usually modeled using network theory [21]. The agent decision-making process and behavior prediction can be modeled, for example, using machine learning (ML) [22].…”

Section: Network Modelingmentioning

confidence: 99%

Machine Learning-Based Node Characterization for Smart Grid Demand Response Flexibility Assessment

et al. 2021

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As energy distribution systems evolve from a traditional hierarchical load structure towards distributed smart grids, flexibility is increasingly investigated as both a key measure and core challenge of grid balancing. This paper contributes to the theoretical framework for quantifying network flexibility potential by introducing a machine learning based node characterization. In particular, artificial neural networks are considered for classification of historic demand data from several network substations. Performance of the resulting classifiers is evaluated with respect to clustering analysis and parameter space of the models considered, while the bootstrapping based statistical evaluation is reported in terms of mean confusion matrices. The resulting meta-models of individual nodes can be further utilized on a network level to mitigate the difficulties associated with identifying, implementing and actuating many small sources of energy flexibility, compared to the few large ones traditionally acknowledged.

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Section: Network Modelingmentioning

confidence: 99%

Machine Learning-Based Node Characterization for Smart Grid Demand Response Flexibility Assessment

et al. 2021

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“…However, the route switching technique in rings requires the reservation of half of the total capacity for protection purposes. Aside from failure management, ring-structured networks are getting more attention in various fields, such as genetic networks [4], smart grid networks [5], [6], etc.…”

Section: Introductionmentioning

confidence: 99%

An Autonomous Distributed Control Method for Link Failure Based on Tie-Set Graph Theory

Nakayama

Shinomiya

Watanabe

2012

IEEE Trans. Circuits Syst. I

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This study proposes an autonomous distributed control method for single link failure based on loops in a network. This method focuses on the concept of tie-sets defined by graph theory in order to divide a network into a string of logical loops. A tie-set denotes a set of links that constitutes a loop. Based on theoretical rationale of graph theory, a string of tie-sets that cover all the nodes and links can be created by using a tree, even in an intricately-intertwined mesh network. If tie-sets are used as local management units, high-speed and stable fail-over can be realized by taking full advantage of ring-based restoration. This paper first introduces the notion of tie-sets, and then describes the distributed algorithms for link failure. Experiments are conducted against Rapid Spanning Tree Protocol (RSTP), which is generally used for fault recovery in mesh topological networks. Experimental results comparing the proposed method with RSTP suggest that our method alleviates the adverse effects of link failure with a modest increase in state information of a node.

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“…This technique avoids the need to use matrices for developing general purpose equations for a specific system in order to calculate its steady-state availability and failure frequency. [19][20][21][22][23][24][25] Complexity for calculation has been reduced to great extent using graph theory as a set of generalized formulae is developed that can be applied to several configurations. Solution of general purpose equations obtained by graph theory is fast and less complex than other methods as it does not involve transition rate symbols, so its solution does not require matrix solving by Cramer's rule.…”

Section: Introductionmentioning

confidence: 99%

A graph theory approach for reliability analysis of phasor measurement units using frequency and duration technique

Ghosh

Mishra

Ghose

et al. 2014

Proceedings of the Institution of Mechanical Engineers, Part O:

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Failure frequency and steady-state availability are two key indices for reliability analysis of phasor measurement units. Phasor measurement unit is the edifice of wide area measurement system and thus reliable operation is essential. Markov model is the general basis for evaluation of reliability indices, but it involves matrices of large dimension. This article describes the general purpose graphical approach for obtaining the two key reliability indices of phasor measurement units from flow graph based on Markov model. It is concerned with the calculation of availability, frequency and outage duration of phasor measurement units by module wise reliability analysis. This method itself is sufficient for sensitivity analysis of phasor measurement unit and helps in identifying the critical module within the phasor measurement unit.

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Distributed control based on tie-set graph theory for smart grid networks

Cited by 10 publications

References 8 publications

Machine Learning-Based Node Characterization for Smart Grid Demand Response Flexibility Assessment

Machine Learning-Based Node Characterization for Smart Grid Demand Response Flexibility Assessment

An Autonomous Distributed Control Method for Link Failure Based on Tie-Set Graph Theory

A graph theory approach for reliability analysis of phasor measurement units using frequency and duration technique

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