Development of a sustainable transmission structure replacement and maintenance strategy

This thesis proposes methods to both estimate optimal aggregate investment levels for a system of transmission towers by means of an integrated corrosion and failure simulation as well as a method to identify specific assets in need of investment through a statistical model of structural health. Limited tower replacements over the past decade have resulted in an overall aging of PG&E's transmission system, leading to managerial concerns about potential increased maintenance and replacement costs going forward. The utility is seeking to be able to forecast its future needs despite a minimal history of asset failure. This work establishes long-term investment scenarios by simulating asset aging due to atmospheric corrosion and integrating those simulations with maintenance, replacement, and failure cost estimates. In addition, the aggregate investment forecasts are supplemented with an asset health ranking methodology that enables more targeted resource deployment. Implementation of the simulation based forecasting provides long-term spend estimates - on the order of many decades - and enables the production of sensitivity analyses based on underlying parameters grounded in physical system properties. This advances current industry spend forecasting which relies on qualitative risk assessments and past cost trends. Asset health indices generated from structural properties and environmental data are also shown to correctly rank a structure with a historic reported structural issue as at higher risk than a structure without a reported issue at a rate of 70%.

Department dc:contributor.department

Leaders for Global Operations Program at MIT

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2018

Author dc:creator

• Tuttman, Max (Max B.)

Advisor dc:contributor.advisor

• Georgia Perakis and Konstantin Turitsyn.

• Sloan School of Management.
• Mechanical Engineering.
• Leaders for Global Operations Program.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/117959

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/117959