Digital Twin-oriented Multi-physics Field Modeling And Simulation Of High-voltage Circuit Breakers

Digital twin is an emerging digital technology capable of perceiving,simulating and predicting the physical world with high accuracy,integrating multi-physical quantities,multi-scales and multi-disciplinary attributes,featuring real-time interaction and closed-loop feedback,and enabling the interactive integration of the physical world and the information world.Digital twin combined with technologies such as IoT,big data,artificial intelligence,cloud computing,fog computing,edge computing,and blockchain is of great significance for solving the increasingly complex monitoring and prediction problems of power systems.As an extremely important device for opening and breaking circuits in the power system,the operation status and safety performance of circuit breakers deserve attention.For the problems of condition assessment,online monitoring,decision optimization and offline inefficiency of operation management of circuit breakers,multi-physical field modeling and simulation of high-voltage circuit breakers based on digital twin,by establishing a digital twin model of circuit breakers,analyzing the change of multi-physical field parameters of digital twin model in different opening distance cases,and mastering the operation status of circuit breakers and other situations,the main research contents are as follows.(1)A digital twin-based circuit breaker condition monitoring method is proposed.The physical field of circuit breaker is a multi-scale,non-linear system with complex coupling relationship.Based on electrostatic field equation,hydrodynamic equation and turbulence model to establish a mathematical model of circuit breaker multi-physical field coupling,considering the media characteristics inside the interrupter chamber,establishing a digital model of circuit breaker in virtual space with the help of open source software FreeFem++ and OpenFOAM,data acquisition to obtain static data of circuit breaker and Data acquisition to obtain static data and real-time operation data of the circuit breaker,in the virtual space of the circuit breaker internal multi-physics field simulation,simulation results and the actual situation to assist the circuit breaker state monitoring.(2)Digital twin circuit breaker temperature field,airflow field and other multi-physical field coupling calculation.Firstly,the digital model of high-voltage SF6 circuit breaker entity is established.Secondly,the finite element method and finite volume method are used to simulate the electric field and airflow field of the circuit breaker,and the distribution of electric field strength,density,temperature,etc.at different opening distances is obtained based on the compilation and execution of open source software to obtain the dynamic distribution of each physical field opening and closing process.Finally,the density,temperature,velocity and pressure characteristics of feature points are obtained by setting probes,and the physical characteristics of each feature point and time node are extracted as the digital twin history data set,which provides the basis for subsequent circuit breaker state identification.(3)A circuit breaker digital twin framework is constructed and the digital twin technology is applied to circuit breaker condition monitoring.The field strength,velocity,pressure,temperature,and density of the characteristic points are selected as the identification parameters,and the models with different numbers of input variables are selected for training and prediction respectively,considering the different identification effects of single physical field and multi-physical field parameters,and the results show the feasibility and effectiveness of the circuit breaker identification model based on digital twin data.In addition,according to the four evaluation indexes constructed,the genetic algorithm has better adaptability,the smallest error and good fit when density is used as a feature quantity in a single physical quantity,and better discrimination effect than single physical field when multi-physical fields are used together as discrimination indexes.