Carl L. Benner

Analysis of high impedance faults using fractal techniques

Phase currents and voltages in a distribution power system change with a certain degree of chaos when high impedance faults (HIFs) occur. This paper describes application of the concepts of fractal geometry to analyze chaotic properties of high impedance faults. Root-mean-square rather that instantaneous values of currents are used for characterization of temporal system behavior; this results in relatively short time-series available for analysis. An algorithm is presented for pattern recognition and detection of HIFs; it is based on techniques suited for analysis of relatively small data sets. Examples are given to illustrate the ability of this approach to discriminate between faults and other transients in a power system.

Intelligent Systems for Improved Reliability and Failure Diagnosis in Distribution Systems

Certain smart grid technologies can reduce the number of customers affected by prolonged outages, and thereby increase reliability through automated switching to restore service. Such technologies are useful, but reactive in nature, performing their function only after a fault occurs and an outage has been detected. They must presume that nonfaulted feeder sections and alternative feeders are healthy and capable of carrying increased power flow. Research at Texas A&M University has demonstrated that sophisticated, automated real-time analysis of feeder electrical waveforms can be used to predict failures and assess the health of distribution lines and line apparatus. Reliability can be substantially improved by detecting, locating, and repairing incipient failures before catastrophic failure, often before an outage occurs. Requirements for data and computation are substantially greater than for devices like digital relays and power-quality meters, but feasible with modern electronics. This paper provides selected examples of failures that have been predicted by intelligent distribution fault anticipation (DFA) algorithms. The data requirements and processing analysis to detect these failures are discussed. The problems related to full-scale deployment of the proposed system in a utility-wide application are presented. The authors use experience gained from their long-term research to propose concepts for overcoming these impediments.

Improved algorithm for detecting arcing faults using random fault behavior

Abstract High impedance distribution feeder faults have been shown to generate considerable high frequency current when arcing is present. A new algorithm is presented which takes advantage of this phenomenon and its random behavior. Using recorded fault data, parametric analysis has been performed to pseudo-optimize the detection capability while maintaining a high degree of insensitivity to normal system events. A discussion of possible implementation constraints is included.

High impedance fault detection for industrial power systems

The authors describe the characteristics of high-impedance faults and the most effective techniques for detecting them. The benefits of high-impedance fault detection for industrial power systems are identified. It is shown that the most effective high-impedance-fault detection system incorporates several algorithms and monitors a number of parameters to ensure sensitivity and correct operation. Operating the detector in an alarm mode improves safety and fault location with minimal effect on service continuity. A valuable use for such a detector would be the identification of incipient faults, so that critical loads can be switched to another source before the fault becomes bolted and requires the circuit to be cleared. Using a detector in this way could save substantial down-time costs for critical processes.<<ETX>>

Electrical behavior of contaminated distribution insulators exposed to natural wetting

Working insulators begin failing as airborne contaminants and moisture from natural wetting combine on insulator surfaces to cause a drop in surface resistivity. This enables current to conduct across the insulators, thereby changing the electrical activity exhibited by the insulators when clean. If the drop in surface resistivity is severe enough, then the leakage current may escalate into a service interrupting flashover that degrades power quality. To help improve power quality, Texas A&M University developed an experimental methodology to investigate the electrical activity of contaminated insulators exposed to natural wetting. Leakage current and weather data obtained during experimentation showed that humidity and rain cause a deviation in the electrical activity of contaminated insulators from that of clean insulators. Analysis of leakage current data showed that this electrical activity was characterized by transient arcing behavior. Further, this nonsteady state activity is small, intermittent, and broad band in nature.

Electrical characterization of vegetation contacts with distribution conductors - investigation of progressive fault behavior

Vegetation intrusion is a major cause of faults, outages, interruptions and other power quality problems on electric distribution feeders. Despite the problem vegetation intrusion presents, little fundamental work exists regarding the characterization of electrical signals generated from vegetation contacts. This paper discusses efforts to further characterize the physical and electrical phenomena associated with vegetation contacts on distribution feeder conductors through field experiments. Researchers used tree branches of varying types and diameters to span primary phase and neutral conductors while recording feeder currents and voltages at a remote substation. Video and still photographs detailing the physical progression of vegetation- related faults were also obtained. The results discussed in this paper enhance the understanding of the electrical and physical progression of vegetation-related events, and suggest the continued use of measured electrical signals for detection of incipient vegetation conditions.

Reliability improvement of distribution feeders through real-time, intelligent monitoring

Feeder reliability has been receiving increased attention. Substantial industry efforts have defined standardized indices for quantifying reliability. Utility commissions and municipalities are requiring utilities to use these indices to identify and make improvements to poorly performing feeders. Reliability indices generally equate to the number and length of outages, and to the number of customers affected. While some outages are unavoidable, others are the result of incipient failures or apparatus malfunction. This paper illustrates how reliability can be improved through real-time situational awareness of faults and events. Emphasis is given to providing actionable information with little or no human intervention. The paper describes how Texas A&Ms Distribution Fault Anticipation (DFA) project documented naturally occurring faults and outages on 60 feeders, and examines how those events could be avoided with intelligent monitoring. Reliability improvements are projected through condition-based maintenance and quick response to outages using previously unavailable information on faults and events.

Field experience with high-impedance fault detection relays

High-impedance, arcing faults (HiZ faults) are a perennial problem for distribution systems. They typically occur when overhead conductors break and fall, but fail to achieve a sufficiently low-impedance path to draw significant fault current. As a result, conventional protection cannot clear them, resulting in situations that are hazardous both to personnel and to property. Texas A&M researchers spent two decades characterizing HiZ faults and developing and testing algorithms for detecting them. In the mid 1990s, General Electric commercialized the algorithms in a relay for detecting a large percentage of these faults, while maintaining security against false operations. In an effort to mitigate problems associated with these faults, Potomac Electric Power Company (Pepco) installed the HiZ relays. They evaluated the performance of these relays on 280 feeders over a period of two years and gained significant operational experience with them. Being the first utility to apply high-impedance fault detection technology on such a widespread basis makes Pepcos experience valuable to other utilities that are struggling with decisions regarding their own response to the problem of high-impedance faults.

Distribution feeder caused wildfires: Mechanisms and prevention

Drought conditions in the United States in recent years bring increased attention to the age-old issue of power line-caused fires. It has long been known that power line faults and failures can cause wildfires through multiple mechanisms. Failure mechanisms of various apparatus and operational conditions that result in wildfire ignition are reviewed. Case studies of faults and failures from operating utility systems are presented, along with a discussion of how these faults and failures represent competent sources of ignition for wildfires. Methods of preventing power line-caused wildfires are discussed.

Outage avoidance through intelligent detection of incipient equipment failures on distribution feeders

The past two decades have witnessed quantum advances in the application of microprocessor-based monitoring, protection, and control of power systems. Early digital devices were designed with singular functions in mind, relaying being a prime example. Thinking and practice have evolved and it is now recognized that current and voltage waveforms necessary for a particular function, say relaying, also contain a wealth of information that can be useful for other functions. Texas A&M is collecting, analyzing, and characterizing high-fidelity current and voltage waveforms in a multi-year project, the goal of which is to discover and take advantage of information ldquohiddenrdquo in waveforms, to recognize early warning signs of incipient apparatus failures and recognize improper or suboptimal equipment operation. This Distribution Fault Anticipation (DFA) project is part of the Electric Power Research Institutepsilas distribution automation roadmap. EPRI-member utilities have instrumented 60 feeders across North America to record high-fidelity data for the project. Tennessee Valley Authority-member utility Pickwick Electric Cooperative has instrumented three feeders and has avoided multiple outages and diagnosed malfunctioning equipment.