Detection and Location of Stator Winding Interturn Fault at Different Slots of DFIG

Abstract

Generators are critical components for the wind power generation system and process industries. Generating units or production lines may be shut down by generator failure. Most of the methods used in previous research have analyzed the rotor winding interturn fault in the slot location or the stator winding interturn fault in the phase location, but the doubly fed induction generator (DFIG) stator fault in the slot location still needs to be studied further because of the special topological structure and the real factors of the generator model. To solve this problem, this paper determines the pulsating magnetomotive force (MMF) expressions mapped to the shorted position in two forms. Based on 2D discretization and piecewise interpolation, by taking the short-circuit number and the position of short-circuit slot as model parameters, the modified fault model is developed. The simulations show that as an interturn short-circuit fault occurs, the stator's three-phase current is no longer symmetric, where the fault-phase current is bigger than that in healthy operation. In addition, the results show that the interturn short-circuit faults induce negative sequence current that increases with the gravity of fault in the DFIG stator and that the phase difference of the fault-phase and its lagging phase is more than 120 • . Moreover, commonality and heterogeneity existing in the current amplitude and negative sequence features for detecting stator interturn faults at different slots of the DFIG are proposed and analyzed. The results obtained in this paper are important complements to the stator interturn short-circuit analysis and help the practical monitoring and diagnosis of this fault.

Performance Analysis of Fault Tolerant Operation of PMSM using Direct Torque Control and Fuzzy Logic Control

“…𝑇 = 3 2 p (ᴪ 𝛼 𝑖 𝛽 − ᴪ 𝛽 𝑖 𝛼 ) (25) Here, p be number of pole pairs. Equation (24) gives flux-linkages, ᴪd and ᴪq.…”

“…(30), where theta represents the actual input of the fuzzy controller and 'θ' be its real stator flux angle[24][25].…”

Incipient detection of stator inter‐turn short‐circuit faults in a Doubly‐Fed Induction Generator using deep learning

“…Some mathematical models derived for ITF in DFIGs can be found in refs. [7][8][9][10][11][12]. Modelbased methods are susceptible to the problem characteristics and even the parameter variation and suffer from the lack of flexibility.…”

Bulletin of the Polish Academy of Sciences: Technical Sciences

“…It can be used effectively for different generator operating conditions, except that rotor faults cannot be detected in the vicinity of the synchronous speed. In [7], the doubly-fed induction generator (DFIG) stator fault in the slot location is studied because of the special topological structure and the real factors of the generator model. It determines the pulsating magnetomotive force (MMF) expressions mapped to the shorted position in two forms.…”