Synchronous generator excitation system model parameter identification optimization method

Abstract

The invention relates to a synchronous generator excitation system model parameter identification optimization method. The method comprises the following steps: 1) carrying out no-load step response test on a synchronous generator excitation system to obtain a test output signal; 2) constructing an excitation system simulation model, and determining per-unit guide rule constraints; 3) modifying system model parameters of the simulation model; 4) applying an excitation signal same with that of the test to the simulation model to obtain a simulation output signal; 5) calculating per-unit error of each performance index of the test output signal and the simulation output signal, and judging whether the per-unit error of each performance index meets the per-unit guide rule constraints respectively, and if so, carrying out the step 6), or otherwise, returning to the step 3); and 6)carrying out optimization on the system model parameters according to the per-unit error of each performance index to obtain optimized optimal model parameters and outputting the model parameters. Compared with the prior art, the method facilities obtaining the optimum model parameters of the excitation system.

Description

technical field [0001] The invention relates to a model parameter identification method, in particular to a synchronous generator excitation system model parameter identification and optimization method. Background technique [0002] With the increasing scale of the power grid and the integration of a large number of fluctuating renewable energy into the grid, higher requirements are placed on the accuracy of power system simulation calculations. At present, standardized excitation system models are generally used in power system simulation calculations. It has become a consensus to ensure the accuracy of power system simulation calculations by improving the accuracy of excitation system model parameters. [0003] The survey results show that the current excitation system model parameter identification method uses the similarity between the simulated waveform and the actual waveform as the judgment standard, and continuously adjusts the excitation system model parameters to ...

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Problems solved by technology

The general method is to use the sum of the three error indicators as the judgment criterion. However, it can be seen from Table 1 that there is a certain gap in the dimension and magnitude of the three error indicators, and there is a difference between positive and negative values ​​in the value, so it is impossible to directly Performing a summation operation is not conducive to obtaining the optimal solution of the excitation system model parameters

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