To address the issue of high error rates in fault identification of the state grid of China,a power grid fault identification and alarm scheme based on multi data source fusion was designed.The method combined with maximum overlap discrete wavelet transform(MODWT)technology and long short-term memory(LSTM)network algorithm to improve the power grid fault identification and alarm capabilities;MODWT technology was used with expanded redundancy and self-orthogonal characteristics to classify fault types;transforming the LSTM network algorithm from a unidirectional to a bi-directional network avoided the situation where the network layer can not obtain appropriate partial derivatives and other gradients during feedback transmission.The experimental results show that the accuracy of data quality verification through the proposed algorithm is over 90％,indicating that the research system has strong practicality and superiority in improving the accuracy of fault discrimination.
维普
万方数据