期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2014
卷号：3
期号：9
页码：16169
DOI：10.15680/IJIRSET.2014.0309054
出版社：S&S Publications
摘要：This paper describes a design procedure for a Grey ANFIS based power system stabilizer (GrANFISPSS)and investigates their robustness for a multi-machine power system. Speed deviation of a machine and itsderivative are chosen as the input signals to the GrANFIS-PSS. A four-machine and a two-area power system is used asthe case study. Computer simulations for the test system subjected to transient disturbances i.e. a three phase fault, werecarried out and the results showed that the proposed controller is able to prove its effectiveness and improve the systemdamping when compared to a conventional lead-lag based power system stabilizer controller. The simulation resultshows that the GrANFIS-PSS can be designed to achieve good performance merely using the combination of Greyprediction and Adaptive Neuro-Fuzzy Inference System (ANFIS). GrANFIS-PSS is designed to damp out the lowfrequency local and inter-area oscillations of the Multi-machine power system. By applying this GrANFIS-PSS to thepower system the damping of inter-area modes of oscillations in a multi-machine power system is handled properly.The effectiveness of the proposed GrANFIS-PSS is demonstrated on two area four machine power system (Kundursystem), which has provided a comprehensive evaluation of the learning control performance. Finally, several fault andload disturbance simulation results are presented to stress the effectiveness of the proposed GrANFIS-PSS in a multimachinepower system and show that the proposed intelligent controls improve the dynamic performance of theGrANFIS-PSS and the associated power network
关键词：Grey Prediction; Power system oscillations; linear models; ANFIS
