IDENTIFICATION OF MULTIPLE DYNAMIC NETWORK STRUCTURE CHANGES BY THE INNOVATION GRAPH APPROACH

Having a correct topology structure is one of the key problems of power system network analysis. In this paper, after proposing the modeling principle of predicting and forecasting network as well as innovation network, the superposition relationship of the operating, forecasting and innovation network is formed to establish the relation among innovation vector elements which satisfies Kirchhoff's circuit law. The link reckoning innovation vector defined in the innovation graph provides another way to obtain the innovation vector elements. The corrected vector of load flow is defined by the renewed innovation vector plus forecasting vector, the ratio of which to forecasting value is defined and used as a criterion to identify the two types of dynamic topology changes due to branchs opened and closed. Therefore the multiple collaborated network structure changes can be identified rapidly and effectively in the poor measurement condition such as existing collaborated bad data, not measured branch and even if there is not any status information. In this way, it can provide technical supports for the security supervisory and control function to acquire the important real time information.