Fault Section Estimation of Power Systems with Optimization Spiking Neural P Systems
An optimization spiking neural P system (OSNPS) provides a novel way to directly use a P system to solve optimization problems. This paper discusses the practical application of OSNPS for the first time and uses it to solve the power system fault section estimation problem formulated by an optimizat...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/107802 |
| Acceso en línea: | https://hdl.handle.net/11441/107802 |
| Access Level: | acceso abierto |
| Palabra clave: | Membrane Computing Optimization spiking neural P system Fault section estimation Power systems Fault diagnosis |
| Sumario: | An optimization spiking neural P system (OSNPS) provides a novel way to directly use a P system to solve optimization problems. This paper discusses the practical application of OSNPS for the first time and uses it to solve the power system fault section estimation problem formulated by an optimization problem. When the status information of protective relays and circuit breakers read from a supervisory control and data acquisition system is input, the OSNPS can automatically search and output fault sections. Case studies show that an OSNPS is effective in fault sections estimation of power systems in different types of fault cases: including a single fault, multiple faults and multiple faults with incomplete and uncertain information. |
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