Abstract
In view of the research in the existing forecast model and transformer DGA methods, this paper presents the collaborative model of intelligent concentration forecast of dissolved gases in transformer oil based on multi-Agent system, for improving the predictability of transformer fault. It presents the main function of each Agent, blackboard and JADE bus in this model, discusses the collaborative process of intelligent concentration forecast of dissolved gases in transformer oil based on multi-Agent system, and designs a combination forecasting architecture and a method of composition forecasting. Finally it indicates the feasibility and effectiveness of the intelligent concentration forecast model of dissolved gases in transformer oil based on multi-Agent system according to the application examples.
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