Research On Topology Identification Method Of Power Supply Network Based On Smart Meter Data

With the development of social economy,the demand for electricity continues to increase,and the requirements for the level of power supply services are also increasing.However,the low-voltage power supply network has a low level of intelligence.It increases the workload and difficulty of the daily operation and maintenance of the grid company,and also affects the user's electricity experience.The topology of the low-voltage power supply network is the basis for application functions such as line loss analysis,fault diagnosis,state estimation,and three-phase balance.It is crucial to improve power supply reliability and power supply service capabilities.Since the low-voltage power supply network is located at the end of the power grid,it directly faces users and has many nodes.Its topology information mainly depends on the design data during the construction of the transformer district,and is entered by manually drawing.With the transformation and expansion of the substation,the frequent replacement of equipment and changes in the line lead to changes in the network topology.Through the survey of the transformer district,it was found that due to the untimely update of the topology information,the problem that the on-site installation does not correspond to the system file is common,especially in rural areas.This problem hinders the optimal economic operation of the power grid.How to identify and verify the topology,solve the blind area of the low-voltage power supply network topology management,and realize the intelligent management and control of the transformer district have begun to attract the attention of the grid company.It is inefficient to verify topological relationships through manual investigation.The development of Advanced Metering Infrastructure(AMI)provides utilities with a new method of modeling and analyzing low-voltage power supply networks.This thesis aims to solve the problem of low-voltage power supply network topology identification.Based on the investigation of the current status of smart meter measurement in China and the low-voltage power supply network topology structure,the relationship between them is analyzed.A method for identifying the power supply network topology is proposed.Firstly,a method for single-phase electric meter phase identification based on multiple linear regression is proposed.The multiple linear regression equation takes the single-phase electric meter voltage as the dependent variable.Meanwhile,it takes the gateway meter voltage,the gateway meter current and the single-phase electric meter current as the independent variables.Each single-phase electric meter forms three regression equations with the gateway meter A,B,and C phase,respectively.The determination coefficients of the three regression equations are calculated.According to the value of the coefficients,the phase of single-phase electric meter is identified.In addition,the proposed method is compared with other identification methods from the two aspects of identification accuracy and computational efficiency.The actual meter reading data is used for example analysis.The results show that the proposed method has higher reliability and accuracy without significantly increasing the time complexity.Secondly,a topology identification method for power supply network is proposed based on the identified phase of users.The proposed method is based on iterative principal component analysis(IPCA)and voltage correlation analysis(VCA).This method is based on the principle of conservation of electric energy,that is,the measurement energy of the upper-level meter is equal to the sum of the measurement energy of the lower-level meters connected to it.The topology of the power supply network is modeled as a linear model between the energy of each meter.The IPCA is used to estimate the model constraint matrix and calculate the error covariance matrix of the energy measurement value.Furthermore,the model constraint matrix is modified by the error covariance matrix.In order to reduce the computational complexity of identifying the "table box to user" topology,the users under the same branch are selected using the voltage correlation coefficient,and then the topology identification is performed branch by branch.Finally,the regression matrix is obtained according to the calculated model constraint matrix.Then the correlation matrix is obtained,and the topology of the low-voltage power supply network is identified based on this.Finally,on the basis of identifying the topology,a line parameter identification method based on multiple linear regression is proposed.According to the topological radial characteristics of China's low-voltage power supply network,combined with the measurement data of the electric energy meters at both ends of the line,a mathematical model of parameter identification is established based on the line voltage drop equation.Then the parameter identification problem of the line is converted into a problem of solving the regression coefficient of the regression equation.The regression coefficients of the equation are solved by the least square method.Then the estimated values of the line parameters are obtained.This thesis identifies the exact location of the energy meter in the topology from the perspective of data analysis by mining smart meter data.It is of great significance to accurately load model and power supply network line loss calculation,comprehensively improve the informatization and automation level of the power supply network.Meanwhile,it helps to realize the perception and meticulous control of the power supply network operating status.