This study focuses on the fault diagnosis of a hydroelectric generation system with hydraulic‐mechanical‐electric structures. To achieve this analysis, a methodology combining Bayesian network approach and fault diagnosis expert system is presented, which enables the time‐based maintenance to transform to the condition‐based maintenance. First, fault types and the associated fault characteristics of the generation system are extensively analyzed to establish a precise Bayesian network. Then, the Noisy‐Or modeling approach is used to implement the fault diagnosis expert system, which not only reduces node computations without severe information loss but also eliminates the data dependency. Some typical applications are proposed to fully show the methodology capability of the fault diagnosis of the hydroelectric generation system.
This paper focuses on the transient stability of a hydro-turbine governing system with three kinds of tailrace tunnels. As the transfer coefficients change with operation conditions, the dynamic transfer coefficients which can describe the transient characteristics of the hydro-turbine governing system are introduced. Then, the transient stability of the hydro-turbine governing system is analyzed. The global bifurcation diagrams for the three kinds of tailrace tunnels are respectively presented to investigate the effects of the tailrace tunnels on the stability of the hydro-turbine governing system. Furthermore, theoretical analysis which proves the validity of simulation results is provided to explain the effects of the flow inertia and water level fluctuation. In addition, the influence of the tailrace tunnel gradient on the transient stability is also studied. More importantly, these methods and research results provide theoretical guidance for the arrangement of the tailrace tunnel and the operation of the hydropower station.
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