| With the rapid development of smart grids and the increased sensitivity of electrical equipment in industrial production,the problem of voltage sag was an urgent topic that needs to be studied in depth.Its research could be started in many ways.Among them,the detection and positioning of voltage sags was the basis of the research.The research on the assessment of the severity of voltage sags was of great significance for the establishment of a governance plan for the distribution network,the reduction of the degree of harm,and assessing economic losses.And its assessment relies on the voltage sag sensitivity of sensitive equipment.Therefore,this thesis would conduct analysis and research from these three aspects:(1)A set of experimental test system for voltage sag tolerance of sensitive equipment based on multiple characteristic quantities was designed.In order to obtain the voltage tolerance capability curve efficiently and accurately,based on the laboratory test method and through the realization of software,a set of experimental test system for voltage sag tolerance of sensitive equipment was designed which could simultaneously apply multiple characteristic quantities such as voltage sag amplitude,starting point,phase jump,harmonics,the voltage sag type(single-phase Type Ⅰ,two-phase Type Ⅱ,three-phase Type Ⅲ)to the equipment under test,and the corresponding parameter value could be set and displayed through the man-machine interface.Experiments had shown the feasibility and correctness of the test system and test process,and could efficiently and accurately test the voltage tolerance capability for sensitive equipment.(2)A method for assessing the severity of voltage sags based on improved voltage tolerance curves of sensitive equipment was proposed.The assessment of the severity of voltage sags was an important means to measure the impact of voltage sag events on electrical equipment.This assessment method was proposed for the abrupt problem of voltage tolerance curve distribution of sensitive equipment in the existing assessment methods.First,based on the method of least squares,combined with the equipment voltage tolerance capability and the law of voltage sag,a continuous and monotonic characteristic of sensitive equipment voltage tolerance improvement curve was fitted.Then,according to the relationship between the voltage sag severity function and the equipment voltage tolerance capability,a voltage sag severity function model based on the improved voltage tolerance curve of sensitive equipment was established.Finally,an example was verified based on the voltage sag event data that occurred in a textile factory substation in Thrace,Turkey.The verification result showed that the assessment result of the improved severity function was more reasonable and more realistic.(3)Aiming at the problem that the existing voltage sag severity assessment method and the improved assessment method proposed in this thesis do not consider the difference in the tolerance of user-side sensitive equipment,a node voltage sag severity assessment method based on the tolerance capability of different sensitive equipment was proposed.First,perform simulation tests on each sensitive equipment to obtain its voltage tolerance capability data,and perform curve fitting according to the data to obtain a continuous and monotonic voltage tolerance curve function for each sensitive equipment.Then,based on the voltage tolerance curve functions of different sensitive devices,a voltage sag severity function model that conforms to the actual distribution and had monotonic continuous characteristics was constructed.Finally,the corresponding weights were determined based on the load proportions of different sensitive equipment at each node,and the node voltage sag severity function model was constructed.The simulation experiment results show that the proposed assessment method in this thesis could fully consider the tolerance capability of each sensitive equipment,and could accurately reflect the voltage sag level on the user side of the distribution network node. |