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In view of the complexity and low accuracy of existing fault diagnosis methods for transmission network, this paper proposes a novel transmission network fault diagnosis method combining simplified Bayesian network and fault decision table. First, using the information from Supervisory Control and Data Acquisition (SCADA) system, there develop a fault area identification method, which utilizes circuit breaker (CB) information to isolate the components to build a fault area. In fault area, there creates the simplified Bayesian network to associate components with CBs. Further, the paper proposes a calculation method to calculate the fault probability of components in fault area, which is able to determine the suspicious component set. According to the sequence of relay actions, a fault decision table for the suspicious component set can be established. Finally, the fault condition of components, CBs and protection devices are diagnosed by comparing the local fault decision table. The above method greatly simplifies the complexity of Bayesian network, and the test results show that the speed and accuracy of its fault diagnosis have been significantly improved.

The setting of traditional distance zone-II protection is very complicated, which is due to the difficulty in determining the operating mode and its branch coefficient under the cooperation of multiple lines. So this paper proposes a novel simplified setting method of distance backup protection. This method simplifies the calculation of setting value and accelerates the action time of protection device, which makes the distance zone-II protection only cooperate with the protection of zone-I of local line and only consider the sensitivity coefficient. To further ensure the selectivity of relay protection, the paper develops a fault line detection to match the above method based on random matrix spectral analysis, whose matrix formed by the measured lines current. Then the paper designs a feasible simplified setting process of distance zone-II backup protection by integrating the above methods. Finally, the example analysis shows the simplified setting method of distance backup protection can ensure the selectivity of relay protection, correctly identify the faulty line and speed up the action time.

In recent years, distributed renewable generation has become vital energy support in large-scale power systems. After the different distributed renewable generation connected to the main grid, the analysis and control of power system become more diverse and complicated. This paper proposes an improved system frequency response (SFR) model to predict the frequency dynamic of large-scale distributed hybrid power system more accurately. This paper firstly expands the constants of mechanical power gain factor within traditional SFR model into a first-order inertia link, which can accurately simulate the mechanical power gain factor. Then there extends the generator damping regarding the damping of generator, excitation system and load effect, which can accurately simulate the damping influence of the system frequency dynamics. Finally, the paper proposes a tuning method of related parameters of higher-order SFR model. The simulation results verify that the higher-order SFR model used to predict the power system frequency dynamic is accurate and effective.