An Equivalent Salt Density Prediction Method Based on Fourth-Order Runge-Kutta and Simulated Annealing

Abstract

The present invention provides an equivalent salt deposit density prediction method based on fourth-order Runge-Kutta and simulated annealing, comprising the following steps that: (1) parameter dynamization processing is performed on a classical prediction mode to obtain a discrete classical prediction model expressed by a first-order Euler equation; (2) a fourth-order Runge-Kutta algorithm is introduced to perform higher order derivation iteration on the Euler equation obtained in step (1), to suppress a discrete error of an Euler model; (3) global optimal estimation is performed on model parameters by using an annealing simulation algorithm, so that an equivalent salt deposit density prediction model with high accuracy is achieved; the error that a prediction result of a classical accumulative formula of the equivalent salt deposit density is a negative value at zero time is eliminated, thereby avoiding introduction of a new error; the prediction error is effectively suppressed and a more accurate prediction result is acquired; the difficulty in fitting of a nonlinear high-order model is resolved, the fitting speed is increased, and the optimal estimation value of the parameter is quickly acquired; the defect of the fixed parameter in the classical prediction model is overcome, and dynamic parameter estimation is achieved.

Description

technical field [0001] The invention relates to the field of pollution prediction of electric insulators, in particular to an equivalent salt density prediction method based on fourth-order Runge-Kutta and simulated annealing. Background technique [0002] Insulators are an insulation control that can play an important role in overhead transmission lines. A large number of insulators are installed in transmission lines and substations in the national power system. Due to the large amount of pollutants in our country's atmospheric environment, more dirt will accumulate on the surface of insulators over time. Under unfavorable weather conditions (such as fog, dew, drizzle, melting snow, etc.), the gradually wet pollutants discharge strongly under the action of electromagnetic field, which is pollution flashover. Power grid pollution flashover accidents involve a wide range, and the power outage lasts for a long time, which directly endangers the operation safety of the power ...

AI Technical Summary

Problems solved by technology

Its limitation lies in ignoring the impact of pollution level changes on the pollution rate, which makes the model unable to dynamically modify the parameters, resulting in a sharp increase in the prediction error under natural conditions

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