A Real-time Estimation and Prediction Method of Transmission Line Icing Using Kalman Filter

Abstract

The invention relates to a real-time estimation and prediction method of transmission line icing by using Kalman filtering. The invention uses the historical data of icing and micro-meteorology at time K to establish a multivariate non-universal model based on equivalent icing thickness increments and micro-meteorological factors. The linear regression model, combined with the forecast micro-meteorological data, predicts the equivalent ice thickness increment at time K+1. Based on Kalman filtering, a Kalman filter prediction equation is established by combining the optimal estimated value of equivalent ice thickness at time K and the incremental predicted value of equivalent ice thickness at time K+1 to calculate the equivalent ice coating at time K+1. Thickness prediction value, when the equivalent ice thickness observation value at K+1 time is obtained, the Kalman filter observation equation is established, and then the optimal estimation value of the equivalent ice thickness at K+1 time is obtained. The invention can eliminate noise and gross errors in the ice-covering observation sequence, and realize the real-time estimation and optimization prediction of the ice-covering observation sequence through the mutual correction of the ice-covering model prediction value and the ice-covering observation value.

Description

technical field [0001] The invention belongs to the technical field of on-line monitoring of overhead transmission lines, in particular to a method for estimating and predicting ice coating in transmission lines in real time using Kalman filtering. Background technique [0002] National economic growth is highly dependent on electricity, and at the same time, economic growth will also promote the increase in electricity demand. With the large-scale construction and development of power grids, long-distance, high-capacity transmission lines will inevitably pass through micro-meteorological areas caused by special micro-terrains such as high cold, high altitude, high humidity, and heavy precipitation areas or basins and watersheds. The icing disasters of transmission lines are caused, and the extreme abnormal weather caused by global warming is frequent, which aggravates the icing disasters of transmission lines, and people pay more and more attention to the problem of icing o...

AI Technical Summary

Problems solved by technology

[0004] (1) Long-distance and large-capacity transmission lines inevitably pass through micro-topography, micro-meteorological regions and high-humidity, high-cold, high-altitude, heavy rainfall and snowfall areas caused by special and complex landforms such as mountains, plateaus, and basins. Therefore, The observation environment of the ice-covered online monitoring device is extremely harsh, which affects its observation accuracy

[0005] (2) The real-time estimated value of icing is the basis for line managers to understand the situation of the icing site in real time. However, the current research in this area directly uses the observed icing value as the real-time estimated value of icing to evaluate the current icing state. Due to the influence of observation noise and other factors, the icing observations cannot accurately express the current icing state

[0006] (3) The icing prediction method is usually to establish an icing prediction model, and then obtain the model coefficients through the least squares regression fitting of the observed icing and micrometeorological historical data, and then calculate the predicted icing value, while the observed icing value cannot Avoided errors will definitely affect the accuracy of icing prediction

Images