Micro grid fault diagnosis based on redundant embedding Petri net

On account of the variable topology and multi-terminal power supply in micro-grid, the fault diagnosis faces more and more challenges. Traditional fault location criteria are unsuitable and fault diagnosis modelling is complex or poor versatility. Further on, the fault reasoning operation is time-co...

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Bibliographic Details
Main Authors: Xiangmin Chen, Xingzhen Bai, Qingqing Zhang
Format: Article
Language:English
Published: Taylor & Francis Group 2018-09-01
Series:Systems Science & Control Engineering
Subjects:
Online Access:http://dx.doi.org/10.1080/21642583.2018.1554801
Description
Summary:On account of the variable topology and multi-terminal power supply in micro-grid, the fault diagnosis faces more and more challenges. Traditional fault location criteria are unsuitable and fault diagnosis modelling is complex or poor versatility. Further on, the fault reasoning operation is time-consuming. A high transplantable fault diagnosis model aiming at the fault features in micro-grid is established in this paper, and a simple inference algorithm with good error-detecting capability is proposed. Firstly, the fault location criterion based on current magnitude, current phase and Distributed Generation’s current direction information is proposed, and the fault transient component is adopted as a supplementary criterion. Secondly, a hierarchical Petri net model utilizing the electrical information, relays’ and circuit breakers’ state information is accomplished. The model consists of fault location layer and fault clearance layer. In order to increase the portability of the model, the collective processing for the breakers is implemented. Moreover, ‘bidirectional arrowhead arc’ is introduced to reduce the number of places to optimize the Petri net model well. An improved redundant coding Petri net reasoning algorithm is proposed based on the fault clearance layer of the Petri net model. Finally, the validity of the method is verified through case analysis and comparison.
ISSN:2164-2583