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《AUTOMATION OF ELECTRIC POWER SYSTEMS》 2000-02
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COMBINATION OF HEURISTIC REASONING AND ANN TO REALIZE ON-LINETRANSIENT STABILITY ASSESSMENT IN LARGE SCALE POWER SYSTEMS

Guan Linl, S. K. Tso2(l. South China University of Technology, Guangzhou 510640. China)(2. City University of Hong Kong. Hong Kong, China)  
With the comparison of multiple power system transient stability assessment (TSA) methods, a new hierarchicalTSA scheme based on artificial intelligence (Al) techniques is proposed. Realization of the scheme with the application ofboth rule-based reasoning and artificial neural networks, and digital simulation test results are presented with an example of7--machine 24--bus power system. The sample--based input features screening is also discussed in detail. The new schemeavoids time--consuming digital simulation and can provide multi-level stability information, including the stability levels, theleading instability generator or generator group and the fault critical clearing time (CCT) for dangerous cases.This project is jointly supported by "artificial intelligence based power system stability margin on-line assessment andpreventive control' (Guangdong Ph. D Foundation, No. 974112) and "intelligent power system stability assessment andenhancement' (Croucher Foundation).
【Fund】: 广东省博士启动基金! (9741 1 2 );; 香港 Croucher基金
【CateGory Index】: TM71
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