Forward and backward models for fault diagnosis based on parallel genetic algorithms
- 61 Downloads
In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of fault sections is developed in the forward model and the message passing interface (MPI) approach is chosen to parallel the genetic algorithms by global single-population master-slave method (GPGAs). The proposed approach is applied to a sample system consisting of 28 sections, 84 protective relays and 40 circuit breakers. Simulation results show that the new model based on GPGAs can achieve very fast computation in online applications of large-scale power systems.
Key wordsForward and backward models Fault diagnosis Global single-population master-slave genetic algorithms (GPGAs) Parallel computation
Unable to display preview. Download preview PDF.
- Dysko, A., McDonald, J.R., Burt, G.M., Goody, J., Gwyn, B., 1999. Integrated Modelling Environment: A Platform for Dynamic Protection Modelling and Advanced Functionality. Proc. IEEE Transmission Distribution Conf., 1:406–411. [doi:10.1109/TDC.1999.755386]Google Scholar
- Ren, H., Mi, Z.Q., Zhao, H.S., 2005. Power system fault diagnosis by use of encoded Petri net models. Proc. CSEE, 25(20):44–49 (in Chinese).Google Scholar
- Wen, F.S., Chang, C.S., 1996. A New Approach to Fault Section Estimation in Power Systems Based on the Set Covering Theory and a Refined Genetic Algorithm. Proc. 12th Power Systems Computation Conf., Dresden, Germany, 1:358–365.Google Scholar