Abstract
A risk probability classification model of distribution system with source-network-load-vehicle is established based on fuzzy C-means clustering and fuzzy mathematics in this paper. Monte Carlo simulation method is used to simulate various scenarios of operation and failure of lines, transformers, generators in distribution systems. The data needed for probability classification of voltage fluctuation, line overload, power loss and load loss of distribution system are obtained. For the severity of the accident, the membership functions of voltage fluctuation, line overload, power loss and load loss are constructed by using fuzzy distribution functions based on fuzzy classification method, and the corresponding risk severity classification model is constructed. Mamdani fuzzy reasoning is used to synthesize the risk probability and risk severity for determining the risk level. A risk early warning method for distribution system based on fuzzy C-means clustering is proposed. Taking IEEE-33, IEEE-39 and IEEE-118 systems as studying examples, the risk levels of voltage fluctuation, line overload, power loss and load loss are determined with the cases of normal operation and anticipated fault in distribution system.
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