An optimized fuzzy controller for a synchronous generator in a multi-machine environment

✍ Scribed by Wael A. Farag; Victor H. Quintana; G. Lambert-Torres

• Publisher: Elsevier Science
• Year: 1999
• Tongue: English
• Weight: 771 KB
• Volume: 102
• Category: Article
• ISSN: 0165-0114
• DOI: 10.1016/s0165-0114(98)00204-8

✦ Synopsis

In this paper, an optimized neuro-fuzzy power-system stabilizer (NF PSS) is proposed to improve the transient and dynamic stability of synchronous machines. The NF PSS employs a five-layer fuzzy-neural network (FNN). The learning scheme of this FNN is composed of three phases. The first phase uses a clustering algorithm for coarse identification of the initial membership functions of the fuzzy controller (FC). The second phase extracts the linguistic-fuzzy rules from the available training data. In the third phase, a multi-resolutional dynamic genetic algorithm (MRD-GA) is used to fine-tune and optimize the membership functions of the FC. Extensive simulation studies have been carried out to show the performance of the NF PSS and to compare it with a Conventional PSS (CPSS) in a multi-machine power-system environment. ~