Auto-steered Information-Decision Processes for Electric System Asset Management

James D. McCalley1, Vasant G. Honavar1, Sarah M. Ryan1, William Q. Meeker1, Ronald A. Roberts1, Daji Qiao1, and Yuan Li1

1 Iowa State University, Ames, IA 50011, US
jdm@iastate.edu
honavar@iastate.edu
smryan@iastate.edu
wqmeeker@iastate.edu
rroberts@iastate.edu
daji@iastate.edu
tua@iastate.edu

Abstract. The total replacement value of the US transmission lines alone (excluding land) is conservatively estimated at over $100 billion dollars and triples when including transformers and circuit breakers. Investment in new transmission equipment has significantly declined over the past 15 years. Some of the equipment is well beyond intended life, yet is operated under increasing stress, as load growth, new generation, and economically motivated transmission flows push equipment beyond nameplate limits. Maintaining acceptable electric transmission system reliability and delivering electric energy at low energy prices requires innovations in sensing, diagnostics, communications, data management, processing, algorithms, risk assessment, decision-making (for operations, maintenance, and planning), and process coordination. This paper overviews a comprehensive approach to develop methods and processes in these areas, driven by the ultimate objective to develop a hardware-software prototype capable of auto-steering the information-decision cycles inherent to managing operations, maintenance, and planning of the high-voltage electric power transmission systems.

LNCS 3993, pp. 440-447.

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