Picture offshore wind farm

Open Access research that is improving renewable energy technology...

Strathprints makes available scholarly Open Access content by researchers across the departments of Mechanical & Aerospace Engineering (MAE), Electronic & Electrical Engineering (EEE), and Naval Architecture, Ocean & Marine Engineering (NAOME), all of which are leading research into aspects of wind energy, the control of wind turbines and wind farms.

Researchers at EEE are examining the dynamic analysis of turbines, their modelling and simulation, control system design and their optimisation, along with resource assessment and condition monitoring issues. The Energy Systems Research Unit (ESRU) within MAE is producing research to achieve significant levels of energy efficiency using new and renewable energy systems. Meanwhile, researchers at NAOME are supporting the development of offshore wind, wave and tidal-current energy to assist in the provision of diverse energy sources and economic growth in the renewable energy sector.

Explore Open Access research by EEE, MAE and NAOME on renewable energy technologies. Or explore all of Strathclyde's Open Access research...

Predicting remaining life of transmission tower steelwork components

Segovia, M. and Catterson, V. M. and Stuart, A. and Johnston, L. and Bain, H. and McPhaden, R. and Wylie, R. and Hernandez, A. (2016) Predicting remaining life of transmission tower steelwork components. In: Risk, Reliability and Safety. CRC Press, London, UK. ISBN 9781138029972

[img]
Preview
Text (Segovia-etal-ESREL2016-Predicting-remaining-life-of-transmission-tower-steelwork-components)
Segovia_etal_ESREL2016_Predicting_remaining_life_of_transmission_tower_steelwork_components.pdf
Accepted Author Manuscript

Download (311kB) | Preview

Abstract

Failures in transmission tower’s components usually result in extended disruption of power supply. Repair is very costly as it involves replacement of the transmission lines’ sections affected. Additionally, it might also entail litigation cost associated with power disruption. Maintenance decisions have to be taken in time to prevent a failure. At present, maintenance decisions are mainly based on expert’s judgement, who perform inspections every 10 to 12 years. On specific sites, tower’s components degrade much faster due to aggressive atmospheric conditions, with corrosion being the primary cause of deterioration. In this context, data indicating health state from an UK utility were used to create a Cox model that relates the time before a failure occurs to climatic and atmospheric conditions highly correlated with corrosion. The paper demonstrates the use of the model for predicting remaining tower life, and highlights how this can feed into maintenance planning.