Classification optimization method used for equivalent model parameters of electrical power system and based on trace sensitivity

Abstract

The invention discloses a classification optimization method used for equivalent model parameters of electrical power system and based on trace sensitivity. Firstly, electrical power systems considering load dynamics are divided into groups and gathered, and a system dynamic equivalent model structure and a parameter initial value are determined; dynamic responses of an original system and an equivalent system are calculated under a presupposed fault with an implicit trapezoidal integration method; trace sensitivity of active power, reactive power and boundary node voltage of all call wires to an equivalent model parameter are calculated according to a jacobian matrix output in a calculation process; the trace sensitivity is subjected to normalization processing, average values of the sensitivity are sorted by size, and a static parameter and a dynamic parameter are divided; the static parameter is subjected to least squares optimization according to a steady state time interval response curve and the trace sensitivity, and then a dynamic response time interval response curve is subjected to predicting correction according to the static parameter correction quantity and the trace sensitivity, and the dynamic parameter is optimized; and an equivalent model optimal parameter which meets the requirement of the accuracy can be obtained after a little optimization iteration.

Description

technical field [0001] The invention relates to a method for optimizing parameters of an equivalent model of a power system, in particular to a method for classifying and optimizing parameters of an equivalent model of a power system based on trajectory sensitivity, and belongs to the technical field of power system control. Background technique [0002] The power system is a nonlinear time-varying system, and its equivalent model must be approximate. Various approximations in the equivalent process and continuous changes in system operating status will lead to and increase the equivalent error. How to optimize the parameters of the dynamic equivalent model to make its external characteristics more consistent with the actual system is a key issue for power systems, etc. important question of value. The application of existing equivalent model optimization methods to trajectory sensitivity is mostly limited to selecting the dominant parameters of the equivalent system accord...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to overcome the defects of too many parameters to be optimized and a large number of constraint equations in the optimization of the existing power system dynamic equivalent model, and the artificial intelligence method has the defects of excessive calculation amount and slow algorithm convergence, and provides a A method for classifying and optimizing parameters of an equivalent model of a power system based on trajectory sensitivity, using the difference in trajectory sensitivity characteristics of different parameters in different periods, divides the dominant parameters into dynamic and static parameters, and coordinates and optimizes the two types of parameters respectively, thereby comprehensively improving Optimize algorithm efficiency and equivalent model accuracy

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