Mladen Kezunovic

Smart Fault Location for Smart Grids

Fault location is an important application among intelligent monitoring and outage management tasks used for realization of self healing networks, one of the most attractive features of smart grids. The data gathered from various intelligent electronic devices (IEDs) installed throughout the power system could be utilized for smart approaches to locating faults in both transmission and distribution systems. This paper discusses issues associated with improving accuracy of fault location methods in smart grids using an abundance of IED data. Two examples of how the gathered data from different IEDs is used to improve fault location accuracy in transmission and distribution systems are discussed in detail.

Synchronized sampling and phasor measurements for relaying and control

This paper describes the concept of utilizing time synchronized sampling over an entire power system to simultaneously obtain the phasor values of voltages and currents at particular instants of time. Uses of the phasors are reviewed and the necessary accuracy of synchronization for several applications is established for magnitude and angle of the phasors. Various methods of providing synchronizing signals are examined, and a possible format for transmitting the phasor measurements to remote locations is described. Finally, some possibilities for applications of this technique in protection and control tasks of the future are explored. >

Mathematical models for current, voltage, and coupling capacitor voltage transformers

This paper reviews a number of mathematical models used to represent the nonlinear behavior of the magnetic core of instrument transformers. Models of instrument transformers using these core representations are presented. The transient response of the instrument transformer is compared to actual test results recorded in the laboratory. The paper provides practical guidelines as to which of the physical elements of instrument transformers are important to model during transient studies and which elements could be ignored without sacrificing the accuracy of the simulation results. The electromagnetic transients program (EMTP) data files used to generate the models are also provided in the appendix to help new EMTP users model instrument transformers for evaluation of high-speed protective relaying systems.

BEVs/PHEVs as Dispersed Energy Storage for V2B Uses in the Smart Grid

Numerous recent studies have assessed the feasibility of vehicle-to-grid (V2G) mode of discharging, which provides an option to use the energy stored in a battery in electric vehicles to support the power grid. This paper aims at demonstrating the potential benefits of battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) as dynamically configurable dispersed energy storage acting in a vehicle-to-building (V2B) operating mode. V2B is a concept that is practically viable today being far simpler than V2G, and it may be implemented on a 3-5 year time horizon while V2G may take 10-15 years to gain wider acceptance. Based on the battery characteristics, the benefits of using BEVs/PHEVs as energy storage for demand side management (DSM) and outage management (OM) are discussed in detail. This paper is also focused on the implementation issues of DSM and OM in the smart distribution grid. A strategy for adopting BEVs/PHEV uses in the V2B mode under the peak load and during outage condition is proposed and demonstrated with test cases and numerical results.

Automated transmission line fault analysis using synchronized sampling at two ends

This paper introduces a new approach to power system fault analysis using synchronized sampling. A digital fault recorder with a Global Positioning System (GPS) satellite receiver is the source of data for this approach. Fault analysis functions, such as fault detection, classification and location are implemented for a power transmission line using synchronized samples from two ends of a line. This technique can be extremely fast, selective and accurate, providing fault analysis performance that can not easily be matched by other known techniques.

Experimental evaluation of EMTP-based current transformer models for protective relay transient study

This paper describes an EPRI study of current transformer (CT) digital models intended for protective relay transient performance analysis. Experimental evaluation of CT models implemented using the Electromagnetic Transient Program (EMTP) was carried out. Two relaying CTs with 600/5 and 2000/5 ratios were used in the study. Experiments in a high power laboratory were performed to obtain transient responses. Simulation of the CT response to the same transient events was set up using three different CT models. They were implemented based on the saturable transformer and nonlinear reactor models available in an EMTP. Comparison of laboratory and simulation results indicates that CT models developed based on the EMTP program give satisfactory results for most of the cases. It has also been discovered that in some instances EMTP models need further improvements. >

Fault location using the distributed parameter transmission line model

Earlier work at Texas A&M University led to the development of transmission line fault location algorithms that were based on synchronized sampling of the voltage and current data from the two ends of the line. The line models used in the algorithms were based on lumped parameter models for electrically short lines, or lossless distributed parameter models for electrically long lines. In this paper, the lossless line model is modified to account for the series losses in the line. The line model equations are then solved in the time domain to accurately locate the fault. Testing of the modified algorithm is performed on a power system belonging to the Western Area Power Administration. Extensive EMTP based simulations are used to generate data that are supplied as inputs to the fault location algorithm. To make the testing as realistic as possible, detailed models of instrument transformers are used in the simulation of the various fault cases.

Fuzzy ART neural network algorithm for classifying the power system faults

This paper introduces advanced pattern recognition algorithm for classifying the transmission line faults, based on combined use of neural network and fuzzy logic. The approach utilizes self-organized, supervised Adaptive Resonance Theory (ART) neural network with fuzzy decision rule applied on neural network outputs to improve algorithm selectivity for a variety of real events not necessarily anticipated during training. Tuning of input signal preprocessing steps and enhanced supervised learning are implemented, and their influence on the algorithm classification capability is investigated. Simulation results show improved algorithm recognition capabilities when compared to a previous version of ART algorithm for each of the implemented scenarios.

Transmission Line Boundary Protection Using Wavelet Transform and Neural Network

Two of the most expected objectives of transmission line protection are: 1) differentiating precisely the internal faults from external and 2) indicating exactly the fault type using one end data only. This paper proposes an improved solution based on wavelet transform and self-organized neural network. The measured voltage and current signals are preprocessed first and then decomposed using wavelet multiresolution analysis to obtain the high frequency details and low frequency approximations. The patterns formed based on high frequency signal components are arranged as inputs of neural network #1, whose task is to indicate whether the fault is internal or external. The patterns formed using low frequency approximations are arranged as inputs of neural network #2, whose task is to indicate the exact fault type. The new method uses both low and high frequency information of the fault signal to achieve an advanced line protection scheme. The proposed approach is verified using frequency-dependent transmission line model and the test results prove its enhanced performance. A discussion of the application issues for the proposed approach is provided at the end where the generality of the proposed approach and guidance for future study are pointed out

Detect and classify faults using neural nets

The analysis of transmission line faults is essential to the proper performance of a power system. It is required if protective relays are to take appropriate action and in monitoring the performance of relays, circuit breakers and other protective and control elements. The detection and classification of transmission line faults is a fundamental component of such fault analysis. Here, the authors describe how a neural network, trained to recognize patterns of transmission line faults, has been incorporated in a PC-based system that analyzes data files from substation digital fault recorders.