ROMJIST Volume 20, No. 1, 2017, pp. 5-17
Wenping YU, Jun WANG, Hong PENG, Jun MING, Chengyu TAO, Tao WANG Fault Diagnosis of Power Systems Using Fuzzy Reasoning Spiking Neural P Systems with Interval-valued Fuzzy Numbers
ABSTRACT: Combining interval-valued fuzzy numbers with spiking neural P systems (SN P systems, in short), an extended SN P system model is developed for fault diagnosis of power systems, called fuzzy reasoning spiking neural P systems with interval-valued fuzzy numbers (ivFRSN P systems, in short). The ivFRSN P systems can better characterize uncertain alarm information in power systems. Firstly, the modeling approach and fuzzy reasoning algorithm are developed. Secondly, the corresponding fault diagnosis models are discussed. Finally, the fault diagnosis of a six-bus 69kV distribution system is used as an example, including single fault with device failure and multiple faults, to demonstrate the availability and effectiveness of the proposed fault diagnosis model based on ivFRSN P systems.KEYWORDS: Power system; Fault diagnosis; Fuzzy reasoning spiking neural P systems; Interval-valued fuzzy numbersRead full text (pdf)