Investigation of characteristic parameters for condition evaluation of transformer oil-paper insulation using frequency domain spectroscopy

Abstract

SUMMARYFrequency domain spectroscopy (FDS) is employed to evaluate the moisture content and aging state of oil-paper insulation in power transformers. Oil-paper insulation samples with different moisture content and aging states were primarily prepared in the laboratory. A method was proposed based on a study of the influence of the aging state and moisture content on the frequency domain dielectric property of oil-paper insulation. This method distinguishes the influence of moisture content and aging state on FDS through the imaginary part of complex relative permittivity (ε r ″). Relevant characteristic parameters that characterize the moisture content and aging state of oil-impregnated pressboards were also extracted. Results reveal that the extracted characteristic parameters are sensitive to moisture content in the range of 10 À1 Hz to 10 1 Hz and in the range of 10 À3 Hz to 10 À1 Hz for the aging state. An obvious exponential relationship exists between the maximum values of the characteristic parameters in the given frequency ranges and degree of polymerization and moisture content. The new method can be utilized for a non-destructive condition assessment of oil-paper insulation of transformers.

Theoretical considerations while applying sweep frequency response analysis method in determining the interwinding capacitance of power transformers at higher frequencies

“…In all, there are several literatures that report that the status of the winding insulation could be determined faster at higher frequencies . It is even experimentally proven that the status of oil‐paper insulation of the transformer could be determined at higher frequencies with reasonable accuracy . Therefore, it appears possible to exercise high‐frequency methods to gather quickly atleast an apparent information regarding the winding insulation of transformers.…”

“…7,8 It is even experimentally proven that the status of oil-paper insulation of the transformer could be determined at higher frequencies with reasonable accuracy. 11,18,19 Therefore, it appears possible to exercise high-frequency methods to gather quickly atleast an apparent information regarding the winding insulation of transformers. Later, depending on the information obtained, the requirement of a detailed FDS analysis could be decided.…”

Detecting the location and severity of transformer winding deformation by a novel adaptive particle swarm optimization algorithm

“…Various electrical and mechanical defects may happen for power transformers during their life span. Winding deformations that may pledge to severe costly faults are detectable by various methods such as partial discharge measurement, dissolved gas analysis, impedance and capacitance measuring, and lately FRA method that attracted attention of researchers . Therefore, locating the occurred faults and determining their severity in a transformer winding are valuable tasks for enhancing their future designs and repairing procedure.…”

“…Winding deformations that may pledge to severe costly faults are detectable by various methods such as partial discharge measurement, 1 dissolved gas analysis, 2 impedance and capacitance measuring, and lately FRA method that attracted attention of researchers. [3][4][5][6] Therefore, locating the occurred faults and determining their severity in a transformer winding are Abbreviations: AOF, Augmented objective function; APDM, Acquiring parameters of the detailed model; FR, Frequency response; FRA, Frequency response analysis; HV, High voltage; LV, Low voltage; MLAPSO, Multi-level adaptive PSO; PSO, Particle swarm optimization Symbols: A n , B n , Fourier series coefficients; c, The weighting factor; g, The total number of extrema; Gbest, The best found AOF of all particles; h, The number of the i th extremum; i, The frequency point's indicator; M mes,i , The magnitude of ith measured frequency response point; M mod,i , The magnitude of ith calculated frequency response point; N, The total number of frequency points; N f , The number of Fourier coefficients; Pbest, The best found AOF of each particle; phase mes,i , The phase of ith FR point of the reference; phase mod,i , The phase of ith FR point of the obtained model; r, A uniformly distributed random number between 0 and 1; V, The velocity of each particle; w, The weighting function; X, The position of each particle; α, An arbitrary number in a defined feasible range of [0. 5 1.5] valuable tasks for enhancing their future designs and repairing procedure.…”

Retreatment of aged mineral oil using semiconductive nanocomposites for power transformer application

“…Insulating oils are the one of the petroleum by‐product; it can be refined from crude oil by means of various process‐like hydrogenation, solvent extraction, and acid and clay treatment . In power transformer, the paper‐oil complex is the main component of the insulation, playing the role of dielectric barrier, mechanical support, and cooling purpose . The degradation of transformer life is mainly depending on liquid insulation.…”