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.