R.A. Alammari

Frequency and harmonics evaluation in power networks using fuzzy regression technique

Abstract A new technique for frequency and harmonic evaluation in power networks is proposed in this paper. This technique is based on fuzzy linear regression and uses the digitized voltage samples, which are fuzzy numbers, to estimate the frequency and harmonic contents of the voltage signal. In this technique we formulate a linear optimization problem, where the objective is to minimize the spread of the voltage samples at the relay location subject to satisfying two inequality constraints on each voltage sample. Effects of sampling frequency, data window size, and the degree of fuzziness on the estimated parameters are investigated. The performance of the proposed technique is illustrated using simulated data.

Effects of harmonic distortion on the active and reactive power measurements in the time domain: a single phase system

A new application of the least error squares (LES) estimation algorithm is given for identifying, in the time domain, the active and reactive power from available samples of voltage and current waveforms. The digital available instruments used to monitor active, reactive and apparent power use such samples. A new definition for the active reactive and apparent power for sinusoidal and nonsinusoidal waveforms is discussed in this paper. It is shown that misleading reactive power compensation could be obtained if the circuit power factor is not well defined. Simulated results are presented for different waveforms, where the authors compare the results obtained with other available techniques.

On-line estimation of transformer model parameters

The conventional method for determining the parameters of the transformer is to performing the open and short-circuited tests. The method is only suitable for off-line application. This paper presents an alternative approach to conventional open and short-circuit test for determining the parameters of N-windings transformer operating at power frequency on an on-line mode. This approach is based on linear least errors square (LES) algorithm and uses the digitized samples of the input current and voltage as well as the output current and voltage of the transformer windings. The proposed algorithm estimates the winding parameters in two steps; while in the first step the algorithm identifying the winding parameters, in the second step, the algorithm identifying the core parameters. The proposed algorithm is applied to a two-windings transformer and simulated results are reported in this paper.

Digital measurements of symmetrical components of a multiphase power system

The paper presents a digital algorithm method for measurements of symmetrical components of a multiphase power system, four phases. The models for symmetrical components of the multiphase system are first developed, and the algorithm of solution is introduced. The proposed algorithm uses the samples of the phase voltages; the least error squares algorithm is the estimation algorithm to identify the magnitude and phase angle of each component. In this paper, the voltage signals are assumed to be polluted with noise and/or harmonics. Identifying the symmetrical components can be used to analyzing the fault in the system. Effects of critical parameters on the estimated components are discussed.

Two digital filtering algorithms for fast estimation of symmetrical components in a power system: a static estimation approach

Abstract This paper presents the application of two digital filters working together for fast estimation of power systems symmetrical components. The three-phase unbalanced system is transformed to two phases using α–β-transformation. Using such a transformation, harmonics of order 3 and their multiples, in the input signal, are suppressed. Having identified the two-phase voltages, the positive and negative sequence phase voltage can be calculated using a constant transformation matrix. The zero sequence component is easily estimated by averaging the unbalanced three-phase voltage at every sample instant. Least error square algorithm is used to identify the magnitude and phase angle of sequence components from the available samples of the specified component.

Fuzzy linear parameter estimation algorithms: a new formulation

In this paper, we present a new formulation of a fuzzy linear estimation problem as one of the linear programming where the objective is to minimize the spread of the data points, subject to constraints on each measurement point to guarantee that the original membership is included in the estimated membership. Different models are developed based on fuzzy triangular membership as well as fuzzy numbers of LR-type, and applied to different examples in fuzzy linear regression and finally we apply these models for estimating the electrical load on a substation busbar. It is demonstrated that since the nature of the load is characterized by uncertainty, the proposed technique is well suited to apply for electrical load estimation.

On the application of /spl alpha//spl beta/-transformation for power systems frequency relaying

This paper presents a new and very accurate algorithm for power system frequency measurement. The proposed algorithm is based on /spl alpha//spl beta/-transformation of the three phase voltages or current waveforms in the relay location, where digital samples are available for the three phase waveforms. Having obtained the digital samples of one of the components, /spl alpha/-/spl beta/ components, the finite divided difference formulae are used to calculate the parameters of one of these components; the magnitude, the frequency and phase angle. The necessary formulae are derived within the text and effects of imbalance and harmonics contamination on the waveforms are discussed within the text.