Showing papers by "Alexander Mamishev published in 2001"

Moisture solubility for differently conditioned transformer oils

Abstract: It is important to monitor the moisture content of transformer oil in a transformer. One parameter of particular interest is the moisture solubility of transformer oil. It has been reported that transformer oils under different conditions have different solubility. Measurements of solubility for four different types of conditioned oil are presented in this paper: fresh Shell Diala AX oil, lab-aged Shell Diala A oil, Texas Utility used transformer oil, and Ramapo Substation used transformer oil. To avoid the difficulty of achieving full saturation, this paper proposes an alternative method of measuring the moisture solubility in transformer oil using a relative humidity sensor. It utilizes the linearity between the relative humidity of the oil and the moisture content of the oil, to measure the solubility indirectly. The measured results of fresh oil, lab-aged oil, and the Texas Utility oil are very close, and only Ramapo oil shows different sensor response characteristics and solubility.

Evaluation of diffusion-driven material property profiles using three-wavelength interdigital sensor

Abstract: The response of a three-wavelength interdigital dielectrometry sensor to the moisture diffusion process in oil-impregnated transformer pressboard has been simulated using an empirical relationship between the moisture concentration and the dielectric properties of the pressboard. A benchmark test of the moisture diffusion process has been developed with the purpose of comparing alternative parameter estimation algorithms used in /spl omega/-/spl kappa/ (frequency wavenumber) dielectrometry. The results of simulations highlight characteristic features of the multi-wavelength sensor response, such as the sensor response delay from the start of the transient moisture diffusion process as a function of sensor wavelength, the influence of moisture boundary conditions, and the relation between the signal magnitude and variations of dielectric properties. One of the parameter estimation algorithms, linear calibrated admittance-based estimation (LCABE), has been applied to both simulated and measured data. Adequate performance of the LCABE approach in the absence of strong discontinuities of dielectric properties in the electric field penetration region is demonstrated and contrasted to an electrically shielded region case, in which the signal response becomes nonlinear. The proposed approach offers significant potential for the measurement of diffusion processes in various dielectrics, especially for cases with highly irregular geometry or material structure. Measurement results from moisture diffusion process monitoring are included. Parameter estimation of measurement results with LCABE confirm its applicability to the monitoring of moisture dynamics in transformer pressboard.

Classification of power quality disturbances using time-frequency ambiguity plane and neural networks

Abstract: Identification and classification of voltage and current disturbances in power systems is an important task in power system monitoring and protection. This paper presents a new approach for classifying the events that represent or lead to the degradation of power quality. The concept of ambiguity plane together with modified Fisher's Discriminant Ratio Kernel is used for feature extraction. A neural network with feedforward structure is chosen as the classifier. The results of extensive simulations confirm the feasibility of the proposed algorithm. This novel combination of methods shows promise for further development of a fully automated power quality monitoring system. The potential of developing a more powerful fuzzy classification method based on this algorithm is also discussed.

Forward and inverse parameter estimation algorithms of interdigital dielectrometry sensors

Abstract: In this paper we extend the continuum model for interdigital dielectrometry sensors and propose a new, direct technique for estimating material electrical properties from measurements. Interdigital sensors consist of alternating pairs of long, thin electrodes on a plane. An ideal model assumes that the periodic structure extends to infinity and the electrodes have no thickness. We extend this ideal analysis to account for the physical thickness of the electrodes. We also present the model in a matrix form which is amenable to linear algebraic analysis techniques. In particular, the 'inverse problem' of estimating material properties is formulated as a generalized Eigenvalue problem, which avoids the convergence problems of previous iterative algorithms.

Numerical optimization methodology for the design of power equipment

Abstract: Numerical optimization using recurrent finite-element simulations is a promising direction in design of power equipment. Previously, the speed and memory limitations of computers made such an approach unfeasible in comparison with analytical techniques. Recently, exponential improvements in the computer industry induced shifts toward numerical algorithms. The methodology presented here allows an entry-level engineer with the basic knowledge of electromagnetism to design electric power equipment for maximum energy efficiency and several other optimization goals. The search for an optimal set of key design criteria is demonstrated for the case when the number of possible variations of design far exceeds computational capabilities of modern computers.