Affiliations: [a] School of Computer and Software Engineering, Xihua University, Chengdu, Sichuan, China | [b] School of Electrical Engineering and Electronic Information, Xihua University, Chengdu, Sichuan, China | [c] School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, Australia | [d] Research Group of Natural Computing, Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain
Correspondence:
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Corresponding author: Jun Wang, School of Electrical Engineering and Electronic Information, Xihua University, Chengdu 610039, Sichuan, China. E-mail: [email protected].
Abstract: Fuzzy tissue-like P systems (FTPS), as a new variant of tissue-like P systems (TPS), is proposed in this paper. FTPS inherits the advantages of TPS and has the ability of dealing with incomplete and uncertain information. FTPS is very suitable to model the causal relationship between a fault and its protective devices in power systems. A forward reasoning algorithm based on FTPS is developed, and then the corresponding fault diagnosis model is discussed. In order to evaluate the availability and effectiveness of the proposed fault diagnosis model, three case studies of fault diagnosis of a transmission system are discussed and analyzed, including simple fault, complex faults and multiple faults with uncertain status information. The results of case studies demonstrate that FTPS can be used to diagnose faulty sections in power systems accurately and effectively.
Keywords: Power systems, fault diagnosis, tissue-like P systems, fuzzy tissue-like P systems
