Research on Testability Optimization for Measurement System of Third-generation Intelligent Substation

Testability analysis and optimization are important issues for on-site inspection of intelligent substation measurement devices. Based on the structure of measurement system, the functions of each module and fault modes of each functional module, the test information of the system is collected. Then the test selection model of the improved quantum-inspired evolutionary algorithm (IQEA) is introduced in this paper. The basic steps and process of the IQEA are analyzed and the fault- test matrix of the measurement system is calculated according to the test model. From the simulation comparison results of IQEA and other algorithms, it is proved that the IQEA outperformed the existing methods in solving the problem of test selection optimization.