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Criteria algorithm for smart substation recorder starting based on BP & Elman neural network
Author(s): 
Pages: 110-115
Year: Issue:  5
Journal: Relay

Keyword:  smart substationfault recorderstarting criteriaBP neural networkElman neural networkpattern distinction;
Abstract: As to the limitation of traditional starting criteria for fault recorder algorithm, this paper proposes an algorithm based on BP neural network and Elman neural network. An example of phase A and phase B current out-of-limit is studied with the algorithm. By choosing starting criteria samples to train BP and Elman neural network, then inputting the starting criteria information to the two trained models, whether to start recording can be judged from the output results. The outcome of MATLAB simulation shows that the starting criteria for fault recorder algorithm based on BP neural network can effectively complete the recording start with minor error, but the pace is comparatively slower. The starting criteria for fault recorder algorithm based on Elman neural network can also complete the recording start, but the error is bigger. Thanks to the part of feedback, the pace is smooth and steady and easy to accomplish in engineering project. Comparing two algorithms, the suitable one can be selected according to the amount of recorded data.
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