Fault Information Processing of Power Dispatching Communication System Combining MMSE Algorithm and LMS

• Published in: IEEE access Vol. 12; pp. 184529 - 184540
• Main Authors: Pan, Lianrong, Yang, Xiao, Fu, Yuan, Hu, Yuyang, Yuan, Shangbin
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Algorithms; Communication systems; Communications systems; Data processing; Detection algorithms; Detectors; Error analysis; Error correction & detection; Error detection; Fault detection; Fault location; faults; Filtration; Information processing; Interference; least mean square; Localization; Mathematical models; Mean square error methods; Mean square errors; Mean square values; Minimum mean square error; Noise; Noise prediction; Orthogonal Frequency Division Multiplexing; power dispatching communication; Power grids; programmable logic controller; Programmable logic controllers
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2024.3510807

As the scale of power dispatching communication system expands day by day, it becomes more and more difficult for operators to deal with fault information. Therefore, it is imperative to develop an excellent fault information processing method for power dispatching communication system. Aiming at the defects of the existing power dispatching communication system, such as difficult to locate the fault information, low efficiency and poor accuracy, the research first introduces the minimum mean square error detection algorithm, and improves this algorithm. Then, the study utilizes the programmable logic controller communication system to complete the processing and analysis of the noise signal information. Second, the study also selects orthogonal frequency division multiplexing to improve the least mean square filtering algorithm in order to improve the accuracy of prediction. Finally, the study establishes a novel fault information processing model for the power dispatching communication system by combining the least mean square error detection algorithm and the least mean square filtering algorithm. The outcomes indicated that the relative errors of this model in predicting electrical and mechanical faults and environmental faults were only 0.41% and 0.21%, respectively. In addition, compared with the rest of the commonly used models, the fault localization accuracy of this model reached 99.08%. It not only effectively improved the fault localization accuracy by more than 13.77%, but also reduced the average number of iterations by more than 47.23. It can be concluded that the fault information processing model by combining the two improved algorithms can effectively improve the accuracy of fault localization and provide an efficient and feasible solution for the fault information processing of power dispatching communication system.