Novel methodology for assessing environmental exposure of OHL routes

Completed

Other Power and Storage Technologies(Electricity transmission and distribution)

Applied Research and Development

ENVIRONMENTAL SCIENCES (Earth Systems and Environmental Sciences)

Sociological economical and environmental impact of energy (Environmental dimensions)

Project Contact
National Grid Electricity Transmission

Network Innovation Allowance

Ofgem

01 May 2017

01 November 2018

18 months

£990,000

Power

London

Network Innovation Allowance

Project Contact, National Grid Electricity Transmission

To produce a novel methodology for the classification of total environmental input to OHL Systems in order to better understand the environment as a modifier to OHL conductor and fittings degradation. This project will provide a new methodology for classifying environmental risk for OHL conductors and fittings base on environmental exposure. The project will be successful if the classification system developed proves to be accurate when verified against asset condition data.

One of the key factors that affect deterioration of OHL (Over Head Line) routes is the environmental conditions which they are exposed to. The two primary environmental factors which lead to OHL degradation are: 1. Conductor wear caused by motion of conductors due to wind input2. Corrosion resulting from deposition of chlorides and other aerosols National Grid’s current method of environment exposure classification is based heavily on distance and elevation. Geographical and climatic variability in the UK poses significant challenges for asset management of OHL routes because deterioration of OHL systems is highly dependent on localized environmental conditions. This project proposes to trial a new approach to modelling overhead line deterioration by developing a robust environmental classification system using advanced weather data and pollution data combined with mechanical wear models and recognised international standards, to understand the environment as a modifier to degradation of OHL conductor and fittings systems. The accuracy of the model will be tested against existing condition data to establish whether it represents a reliable improvement to our existing approach. If proven successful, this would improve OHL asset management by enabling optimization of asset investment through targeting the right assets at the right time and providing a clearer understanding of asset deterioration and likelihood of failure over time. This project will develop a novel weather based methodology to predict environmental risks by combining advanced weather data, pollution data and mechanical wear models. This project will develop and further verify the methodology created in project NIA_NGETO181. The project will be delivered by undertaking the following steps: ; Creation of corrosion classification based on advanced weather and pollution modelling in line with ISO standards; Creation of mechanical wear classification using advanced weather data and mechanical response models for OHLs; Development of a combined risk classification system for the environmental input on OHL systems The model will estimate wear in terms of number of vibration cycles and corrosion in terms of estimated material loss per year. The outputs of the wear and corrosion model will be validated against asset condition information including repairs and defects data in order to create the environmental risk classification system and to understand the effect of the environment as a modifier on OHL ageing. Project NIA _ETO181 has provided an initial proof of concept for modelling mechanical wear of OHL conductors in a variety of wind exposed environments using advanced weather data. However, to understand the total environment input over time a combined model of corrosion and wind induced motion needs to be developed. To verify the model effectively, a larger sample of routes is required across the full range of OHL operating environments. The model will be route specific because it relies on localised weather and historic corrosion data for each area. To provide a sufficient sample size and enable delivery of the project objectives, the project will be trialled on National Grid’s ACSR (Aluminium Conductor Steel Reinforced) routes. The method has been selected as it provides a more accurate and repeatable determination of environment input to OHL systems. The proposed method of classification allows relationships to be drawn across all spans/towers between defect, failure rate and asset life. It will then be possible to more confidently infer future condition states of younger assets where there are fewer historic defects, failures and condition assessments.Note : Project Documents may be available via the ENA Smarter Networks Portal using the Website link above

17/09/18