KOHONEN NEURAL NETWORK CLUSTERING FOR udVOLTAGE CONTROL IN POWER SYSTEMS

摘要

Clustering a power system is very useful for the purpose of voltage stability control. udHowever, the methods have developed usually have computational inefficiency. This paper udpresents a new cluster bus technique using Kohonen neural network for the purpose of forming udbus clusters in power systems from the voltage stability viewpoint. This cluster formation will udsimplify voltage control in power system. With this proposed Kohonen algorithm, a large bus udsystem will be partitioned into a small bus groups that have a coherence V, θ, P and Q. The udmaximum number of area clusters will be formed need for voltage stability needed. The udproposed technique was tested on IEEE 39 bus system by considering two contingency namely udload increased and line outage by using voltage collapse analysis. This formation will be udcompared with the Learning Vector Quantization (LVQ) algorithm. The results showed the udproposed technique produces four clusters on contingency load load increased and three udclusters online outage contingency on IEEE 39 bus system as shown by the LVQ. ud udKeywords: clustering, Kohonen, learning vector quantization, voltage stability ud