| An accurate system model is one of the prerequisites for the control system to achieve optimal control.The traditional control scheme has been unable to meet the control index of the power system,and the advanced control strategy often relies on the system model with high accuracy to a certain extent.Due to the requirements of the control system for control quality,system identification,system characteristics,and controller optimization have become the core content of system control.In the face of increasingly complex test data of the power system,the existing software cannot connect the latest algorithms and design applications in series,and the functions appear relatively fragmented.This paper designs a power system test data analysis and evaluation software that is easy to use,simple in interface,clear in concept,rich in identification methods,and higher in visualization according to the needs of actual engineering projects.And it solves many problems in other similar software such as too many setting parameters,single identification method,cumbersome data selection,and unadjustable sampling period.The specific research content is reflected in the following aspects:1.Studied the algorithm of model identification using particle swarm optimization and genetic algorithm for test data,developed the function module of model identification using test data of power system;2.Studied the performance evaluation and optimization methods of the control system,developed the function module that analyzed the performance of the power system from the time domain and frequency domain by using the test data,and optimized the parameters according to the industrial performance index;3.The human-machine interface is designed and developed,which integrates data acquisition,data processing,model identification,control system performance evaluation and parameter optimization together,forming a set of power system test data analysis and evaluation software. |
PDF Full Text Request