Quantitative long-term prediction method of power grid icing based on discrete particle swarm optimization and least squares

Abstract

The invention discloses a power transmission line icing long-term and quantified forecasting method. The method comprises the following steps of: 1, collecting history circulation index data and icing data; 2, calculating coefficients related to circulation indexes and an average icing day number, and preliminarily selecting icing forecasting factors; 3, utilizing a discrete particle swarm algorithm to obtain the icing forecasting factors highest in forecasting performance; 4, based on the selected forecasting factors, utilizing the history data to establish a least square regression prediction model; and 5, utilizing the established model to carry out quantified forecasting on the icing degree of a power grid in winter. The method has the advantages that 1, quantified forecasting of the icing can be carried out a month in advance on the power grid in a future quarter (winter); 2, the operation performance is high; 3, the accuracy for power transmission line icing forecasting is high; and 4, the problem of power grid icing long-term and quantified forecasting is solved. According to a predicted result, the manual power and the material for handling the icing of the power grid can be scientifically and reasonably planned, related economic disposition can be performed, the icing of the power grid is handled in advance, and the loss caused by the icing of the power grid is lowered.

Description

technical field [0001] The invention belongs to the technical field of power transmission and distribution, and in particular relates to a method for long-term forecasting of grid ice. Background technique [0002] Grid icing is one of the natural disasters that seriously endanger the safe and stable operation of transmission lines. Since the first transmission line icing accident in 1954, large-scale icing accidents have occurred in the country from time to time, bringing huge losses to the national economy. . Especially at the beginning of 2008, southern China encountered a rare large-scale, long-term severe snow and ice disaster. Due to insufficient preparation of anti-icing resources, the direct economic loss of power grid enterprises reached more than 10 billion yuan, and factories, hospitals and residents The power outage in the district and the outage of the Beijing-Guangzhou electrified railway have posed a serious threat to social stability and people's production ...

AI Technical Summary

Problems solved by technology

[0003] At present, the long-term prediction method of power grid icing only predicts the degree of icing on the power grid, and the same degree of icing will also be severe or light, so it is difficult to refine the anti-icing decision-making. In addition, the degree prediction method needs to include human experience factors, which is difficult Using a computer for programmatic processing requires a large workload. Therefore, there is an urgent need for a quantitative long-term forecast method for power grid icing that can be programmatically processed.

Images