Abstract
AbstractCommunication quality is a key factor affecting the effectiveness of distribution network operation status management. Therefore, it is required that the communication performance of the distribution network management system be good, and the communication signal can directly reflect the communication quality. Therefore, a genetic algorithm (GA) based HPLC communication signal feature extraction method is proposed. The process of constructing reference samples, training recognition models, constructing noise samples, self‐coding denoising processing, and denoising sample recognition has completed the identification of power line channel transmission characteristics. The state feature quantity of the topological line is based on the positioning results of the diagnostic function, and the calculated value of the reflection coefficient calculation model at the head end of the topological line is compared with the measured value. By optimizing the feature quantities containing topological line states through GAs, abnormal feature quantities close to the true state of topological lines are obtained. Experimental analysis shows that this method can correctly identify the position of reactive power compensation in the transmission line, and can also correctly identify the extraction of topological anomaly features. Therefore, the research method is of great significance in improving the safe operation of power systems and extending the service life of topology lines.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.