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Research On Real-time Correction Method Of Comprehensive Load Model Parameters

Posted on:2019-01-18Degree:MasterType:Thesis
Country:ChinaCandidate:C Y PengFull Text:PDF
GTID:2382330545957401Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
In recent years,the economic and social development has led to an ever-increasing scale of the power grid,Advances in science and technology have also led to rapid development of power system engineering technology,there has also been continuous promotion of market-oriented operations,the issue of safety and stability of power grid has become more prominent.The main decisions in the security and stability control for Grid dispatch also need to be based on online,real-time simulation results.At present,the grid usually uses the existing and constant load models and parameters when performing simulation calculations,which obviously cannot meet the accuracy requirements of real-time simulation calculations.Therefore,it is very important to establish a real-time and accurate load model that adapts to changes in load characteristics.This paper proposes a real-time correction method for substation comprehensive load model parameters based on the principle of Component-based approach,based on user surveys and field measurements.The main research focus of the real-time correction method for substation comprehensive load model parameters is discussed,and the method and results analysis are carried out on the first research focus of the load investigation of the typical electricity industry.It shows that through the user survey of the load characteristics of the typical electricity industry,the dynamic load ratio of the industry and the ratio of the composition and composition of the power equipment can be obtained.The rationality of the survey results proves the rationality and effectiveness of the user-research on load characteristics of a typical electricity industry.The field measurement of static characteristics of the typical electricity industry is another focus of the real-time correction method for substation comprehensive load model parameters.After a lot of research work,it shows that the field measurement of static characteristics of the typical electricity industry can obtain static model parameters and real-time composition ratios of various industries.Introduce the actual implementation method and give an example of the actual measurement results.According to the proposed method of parameter identification,the parameter identification results of the measured users are obtained,and the static model parameters of the typical electricity industry are obtained according to the static model parameters of the measured users.A method for Composition analysis of industries based on static model parameters and PMU(Phasor Measurement Unit) data is described.It reflects the practical value of the actual field study of the static characteristics of a typical electricity industry.For the proposed real-time correction method of substation comprehensive load model parameters,it is difficult to apply to substations with negative load values.It is no longer applicable that the original analysis method for the Composition analysis of industries based on daily load curves is for substations with negative load values.This has been the focus of this study.A method for the Composition analysis of typical electricity industries in substations with negative load values is proposed.Using the Component-based approach and the principle of fuzzy clustering,the mapping relationship between the load characteristics of the typical electricity industry and the daily load curve of the substation is established to form a power balance equation group.The comprehensive improved genetic algorithm is used to analyze composition of typical electricity industry of substations with negative load values.The application example analysis proves the correctness and effectiveness of this method.
Keywords/Search Tags:Load Modeling, Component-based approach, Load Characteristics Investigation, static characteristics measured, Composition analysis of electricity industries, Comprehensive Improved Genetic Algorithm, Parameters Real-time correction
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