A power quality prediction system

Abstract

This paper describes two hardware prototypes and estimation schemes for determining the parameters of a simple, physically based, point-of-use electric utility model using transient measurements. Parameters of the utility model are estimated using data collected by the prototypes. Frequency-dependent effects observed in previous work in this area are modeled. Performance of the techniques given is demonstrated by comparison of measured and predicted line voltage distortion during current transients created by several loads. Index Terms-Estimation, power distribution testing, prediction methods. I. BACKGROUNDF ROM A SERVICE outlet, the electrical utility can be approximated as a sinusoidal voltage source in series with an inductor and a resistor. In a commercial or industrial building, impedances seen at the "user interface" arise predominantly from an upstream transformer, protection circuitry, and cabling. Harmonic currents generated by loads flow through these impedances, creating voltage drops that result in a distorted voltage waveform at the service outlet.In [1], an interesting technique for determining the local apparent impedance of the electrical utility service is presented. The impedance is identified by briefly closing a capacitor across the electrical service at a precise point in the line voltage waveform. The shape and decay of the transient current in the resulting RLC circuit can be used to estimate the line impedance.In this paper, the technique in [1] is reformulated in two point-of-load impedance characterization and voltage distortion prediction systems. The first system (method A) uses the RLC transient excitation technique from [1], but features a digitally programmable test capacitor, a phase-programmable switch, and a data collection interface. The second system (method B) consists of a programmable current source, providing more flexibility in test transients. The two systems, and their associated estimation procedures, share a point-of-load model of the electric utility. This model, motivated by theory, accounts for the measured increase in resistance as a function of test transient frequency observed in [1] and [2]. Ultimately, the model and estimated parameters are used to predict voltage distortion from transient currents.

Comparison of modified teaching–learning-based optimization and extreme learning machine for classification of multiple power signal disturbances

“…In a multiclass classification, the number of output nodes is equal to m (m [ 1), and in such a case, the predicted class label of a given testing sample is the index number of the output node having the highest output value. Thus, the class label of x is given by…”

“…In the past decade, researchers analyzed the power quality issues with the increasing amount of measurement data from power quality monitors. The time of occurrence and the frequency of power quality disturbances [1][2][3][4] are unknown, so the monitoring is often required over an extended period. Further, the power quality disturbances can appear simultaneously as in realistic power networks there are multiple sources of different disturbing events.…”

Classification of power quality events – A review

“…Therefore, PQ events detection and classification area is having its own importance in the era of PQ. So, PQ analysis is becoming the most interesting area of research in past several years for characterization [14,15] and classification of events [16]. For the classification of PQ events, feature extraction and classification are the most important part of the generalized PQ event classification system.…”

Power quality education using a remote monitoring laboratory

“…The most important benefit of monitoring is to prevent economic damage, produced by the lack of power quality in critical process loads. Effects on equipment and process operations can include malfunction, physical damage, process disruption and other anomalies [2]- [4].…”