Synchronous condenser excitation system parameter identification based on improved artificial bee colony algorithm

2019 2nd International Conference on Composite Materials Science and Technology

Li, Nan^1 ; Meng, Lian^1 ; Geng, Bin^2

Department of Electric Engineering, School of Northeast Electric Power University, Jilin City, Jilin Province

132012, China^1

State Grid Jilin Electric Power Co. Ltd., Changchun City, Jilin Province

132021, China^2

关键词: Artificial bee colony algorithms;    Excitation controls;    Identification parameters;    Parameter identification methods;    Parameter sensitivities;    Power system stability;    Reactive power regulation;    Synchronous condensers;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/600/1/012026/pdf
DOI  :  10.1088/1757-899X/600/1/012026

来源: IOP

【 摘 要 】

The quality of excitation control of the synchronous condenser directly determines the reactive power regulation ability and control support performance of the power grid.Aiming at parameter identification of non-linear links such as limit and saturation in the synchronous condenser excitation system, a parameter identification method of the synchronous condenser excitation system based on improved artificial bee colony algorithm is proposed.Firstly, the order of the phase modulation operation is deduced, and the mathematical model of the synchronous condenser excitation system is established based on it.Then the artificial bee colony algorithm is improved and applied to the parameter identification of the synchronous condenser excitation system. A parameter identification strategy based on sensitivity analysis is proposed for the unstable and multi-solution situation of multi-parameter identification results. Analysis of parameter sensitivity and identification based on parameter sensitivity. Finally, the identification parameters and the overall identification results obtained after sensitivity analysis are compared and analyzed. The results show that the proposed method can effectively identify the parameters of the non-linear link and has strong robustness. It can provide accurate models and parameters for power system stability analysis.