Power grid rainstorm disaster prediction correction method based on probability matching series-parallel connection coupling multiple models

Abstract

The invention relates to the technical field of power grid disaster prediction, and discloses a power grid rainstorm disaster prediction correction method based on a probability matching series-parallel connection coupling multi-model, so as to improve the accuracy of power grid rainstorm disaster prediction. The method comprises the following steps: selecting a forecast area, and obtaining actually measured precipitation and power grid rainstorm disaster information of the area in a historical period so as to establish at least two power grid rainstorm forecast models for forecasting the precipitation of the area; correspondingly correcting the precipitation of each power grid rainstorm forecasting model by using a probability matching correction method; predicting an error sequence et ofeach power grid rainstorm prediction model at the moment t by adopting an error autoregression model, and obtaining a precipitation sequence through series correction of each model; s4, carrying outparallel correction on the plurality of models in the step S4 by utilizing a least square method; and respectively solving parameters of series correction and parallel correction by adopting a particle swarm intelligent optimization algorithm, establishing an integrated coupling power grid rainstorm forecast correction model, and calculating a corrected result.

Description

technical field [0001] The invention relates to the technical field of power grid disaster forecasting, in particular to a method for forecasting and correcting power grid rainstorm disasters with probability matching series-parallel coupling multi-models, in other words, a method for probabilistic matching and correction for forecasting power grid rainstorm disasters with series-parallel coupling multi-models. Background technique [0002] In recent years, torrential rain natural disasters have caused great harm to domestic and foreign power grids and brought huge losses to the society. In July 2012, Beijing ushered in the once-in-500-year heavy rainfall weather, with an average rainfall of 215mm in the urban area and 460mm in Hebei Town, Fangshan District, which resulted in a power outage of all 110kV magnetic household substations in the area. According to statistics, the "7.21" heavy rain disaster caused an impact on the Beijing power grid. Both 220kV and 110kV had insta...

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Problems solved by technology

However, due to the uncertainty of the initial field of the rainstorm numerical forecast model, the imperfection of the parameterization method, and the chaotic characteristics of the atmosphere, some small phase errors in the model may lead to large forecast deviations, and the statistical method of rainstorm forecasting fails to fully consider the Influencing mechanism factors lead to large differences in the magnitude of rainstorm forecasts in local areas. The methods proposed in the above-mentioned patents do not fully consider the relationship between the characteristics of the rainstorm forecast itself, the rainstorm level, and the rainstorm occurrence area, resulting in the accuracy of the grid rainstorm forecast not meeting the requirements.

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