Hydro-generator Excitation Winding Inter-turn Short Circuit Fault Feature Analysis And Fault Identification

In recent years,renewable energy has developed rapidly in China.Hydropower has the advantages of flexible management and mature technology,which plays an important role in renewable energy.The installed capacity and generating capacity of hydro-generator are also increasing year by year.Large hydro-generators have complex structures and take into account the tasks of power generation and power system peak regulation.With the increase of operation burden,the failure rate of units is on the rise.The excitation winding of the hydro-generator has been accompanied by high-speed rotation of the rotor for a long time,and prone to inter-turn short circuit faults.The initial fault characteristics of the inter-turn short circuit of the field winding are not obvious.If the fault is not handled in time,it may cause more serious faults such as the grounding of the rotor and affect the stable operation of the hydro-generator.At present,there is no effective online monitoring method for inter-turn short circuit faults in the field windings of hydro-generator.Therefore,it is necessary to deeply study the fault characteristics of the inter-turn short circuit of the field winding to put forward the recognition method with high accuracy.These studies have important implications for hydro-generator.In this paper,the excitation current,temperature field and thermal stress of the inter-turn short circuit fault in the field winding of the hydro-generator are studied in detail.Combined with the electrical quantity analysis,the inter-turn short circuit identification of the hydro-generator is proposed.Based on the multi-feature research,an information fusion diagnosis method is proposed.On the basis of on-line diagnosis of short circuit fault in hydro-generator,the identification accuracy of short circuit fault in field windings is improved.The main work and achievements are as follows:Calculation and analysis of inter-turn short circuit rotor current and standard current of hydro-generator windings.The excitation current of the hydro-generator after an inter-turn short circuit in the field winding is analyzed.Based on the principle of the generator,a mathematical model of electrical parameters such as voltage,active and reactive power is established.Push the relationship between the amount of conductive machine operation monitoring and the excitation electromotive force.An inverse calculation method for the no-load curve of the excitation current is proposed.By calculating the no-load characteristic curve in the reverse direction,the standard value of the excitation current for a specific operating state of the hydro-generator excitation winding under normal condition is obtained.The comparison between the inter-turn short circuit criterion and the measured excitation current can reflect the inter-turn short circuit fault and the degree of failure.Study on rotor pole temperature and thermal characteristics of excitation winding inter-turn short circuit fault.A three-dimensional finite element model of the rotor pole of the hydro-generator is established and related assumptions are proposed according to the situation of the hydro-generator.The rotor pole temperature field and thermal stress before and after the short circuit fault of the field winding are calculated.The changes of magnetic pole temperature field and thermal stress during fault are summarized.Change the relevant parameters of the model and establish models with different short circuit degrees and different short circuit locations.The influence of the degree and position of the short circuit of the exciting winding on the temperature field and thermal stress of the magnetic pole of the hydro-generator are further analyzed.A diagnosis method for inter-turn short circuit of hydro-generator based on Volterra kernel identification is proposed.This chapter establishes a non-linear system for inter-turn short circuit fault in the field windings of hydro-generator.Analyze the feasibility of stator branch voltage and branch current as input and output to identify interturn short circuit.The Volterra series model is introduced to describe the system characteristics.In order to diagnose the inter turn short circuit fault of excitation winding,the difference of Volterra kernel function is used to identify the transfer relationship of nonlinear system under normal and fault conditions of excitation winding.The correctness and validity of the method are verified by the generator inter-turn short circuit fault experiment.The proposed diagnosis method has high accuracy.The third-order kernel identification is used to identify the inter-turn short circuit fault of the excitation winding of the hydro-generator.Based on multi-source information fusion,this chapter presents a method for identifying the inter turn short circuit in the excitation winding of hydro-generator.The theory of multi-source information fusion is applied to the identification of the inter turn short circuit fault in the excitation winding of hydro-generator.According to the characteristics of generator and the condition of sensor,the characteristic value of short circuit fault is selected as the evidence body.The multiple sets of fault characteristic evidence bodies of the inter-turn short circuit of the hydro-generator are fused based on the evidence theory to reduce the influence of sensor uncertainty and improve the confidence of the conclusion of the inter-turn short circuit identification.Experiment on inter-turn short circuit fault in the field winding of the generator was carried out.The comparison of multi-feature and single-feature confidence levels validates the effectiveness of multi-source information fusion in the identification of inter-turn faults in generator windings.The results show that the fault identification method based on multi-source information fusion for the inter-turn short circuit in the field winding of the hydro-generator reduces the impact of uncertainty caused by single sensor.This method improves the accuracy of fault identification.