Transgrid – Public Safety Risk Quantification

1. Executive Summary

Transgrid has automated the individual calculation of the public safety risk for each of its 38,000 transmission line poles and towers. To improve the calculation of asset risk costs, individual asset component health and human movement data has been used to better quantify the likelihood that people will be in the vicinity of our transmission line assets during various high potential incidents. This approach enables Transgrid to better prioritise and optimise its capital expenditure, design control
selection and public awareness strategies. The investment approach target’s assets with elevated probabilities of failure in combination with locations of high criticality to help prevent safety incidents.

2. Description of Project

2.1. Need for Project

Transgrid’s previous approach to public safety exposure relied on a high level ranking of safety criticality based on broad categories of land use, zoning, terrain etc. It relied on general assumptions around hazard occupancy and highly averaged exposure times over relatively large geographic areas. In addition we received feedback from the AER and consumer groups that our risk assessment methodology overstated safety risk costs and therefore the expected benefits of our proposed capex program were not fully demonstrated. There is a strong desire to continually improve our methodology to further demonstrate that we are managing safety risk to As Low As Reasonably Practicable (ALARP) for all of assets, and at lowest cost to consumers.

2.2. Project Details

In managing assets, Transgrid needs to identify and quantify (in dollars) potential risks to public safety. For a variety of asset types (eg. transmission lines, substation equipment) and a variety of hazards (e.g. conductor drop, transmission tower earthing system failure, unauthorised asset access, explosive failure) Transgrid have considered the following in determining the likelihood of consequence from an asset failure:

  • Frequency of person in near vicinity (on an annual basis as a percentage of time)
  • Effectiveness of preventative controls
  • Vicinity of asset to a publically accessible area
  • The area of effect from a high potential incident.

Figure 1 illustrates the asset risk cost calculation used by Transgrid.

Figure 1 – Risk quantification methodology

The following section briefly describes the enhanced methodology for determining public safety consequence for a transmission line conductor drop. A similar approach is used for assessing substation equipment explosions and transmission structure earthing system failures.

2.3. Conductor Drop Public Safety Modelling

This high potential incident covers the consequence of injury to person(s) resulting from a transmission line
conductor falling to the ground, including the likelihood it will lead to an injury and the type of injury.

2.3.1. Asset Health and Probability of Failure

Transmission line asset health has been upgraded to consider the following:

  • A transmission line asset consists of a number of structures/spans, each of which contributes to the health of the overall line.
  • The individual transmission line structure/span consists of a compound group of components (eg. poles, foundations, conductors, insulators, fittings), each with an underlying life expectancy and reliability.
  • The overall health of an individual structure/span is a function of the health of each component and a health score is calculated for each component.
  • The ‘current effective age’ is derived from asset information and condition data.
  • The future effective age (considering age acceleration/deceleration) is derived by ‘ageing’ and moderating ‘current effective age’ based on factors such as, external environment, expected stress events and operating conditions.
  • The forecasted likelihood of failure of an asset is a conditional probability based on its assessed remaining life using statistical failure curves, normally using Weibull analysis.

Prior to these enhancements generic assumptions were applied on a line by line basis to determine the probability of failure.

2.3.2. Public Exposure and Consequences

Human movement data (HMD from mobile phones), as illustrated in Figure 2, was used to help calculate the expected number of exposed people hours within the easement for each of Transgrid’s transmission line spans. This enabled the % likelihood that a person, on a span by span basis, could be located in close proximity to a Transgrid line should it fall to the ground.

Figure 2 – Mobile phone usage geospatial heat map

The conductor drop public safety consequence (as displayed in Figure 3) has now been calculated for each individual span location. The likelihood of consequence is calculated in consideration of the following:

  • Potential Impact Zone: Defined as the span length x easement width. The human movement data corridor used in the calculation corresponds to this area.
  • Impact Zone: Defined as the span length x potential injury width. The potential injury width is based on the safe approach distances to live electricity mains, with higher voltages having a larger impact zone.
  • Injury likelihood factor: To denote that an exposed person may escape an injury.

Figure 3 – Calculating the Likelihood of Consequence for a Transmission line span

The probability distribution of the injury consequence has been assessed based on the impact zone area, from minor injury through to fatality. Similarly a probability distribution for the value of a range of injuries ($50,000-$5,000,000) has been applied to determine the likelihood and cost of consequence. Prior to the usage of HMD, public safety exposure were based on generic assumptions applied on a line by line basis, with serious injury assumed for all high potential incidents.

2.4. Best Practice Asset Engineering

Our modified approach is best practice as:

  • It involves the analysis and evaluation of network asset risks in a systematic and consistent manner
  • The quantification of asset risk is based on data driven decision making, is aligned to the Transgrid asset management objectives and to the Transgrid risk management framework.
  • It caters for the huge range of public exposures across our assets (which vary from busy road and rail corridors in metropolitan areas to large outback property holdings or wilderness areas)
  • Aligns with contemporary risk management approaches and regulatory requirements
  • The investment approach helps ensure funds are allocated efficiently by targeting assets with elevated probabilities of failure in combination with locations of high criticality.

2.5. Project Originality / ingenuity

The key aspects which make this project special are the combination of these three components:

  • Calculating the probability of failure for each transmission line asset component as well determining the consequences of asset failure, considering its individual geospatial characteristics.
  • Utilising human movement data (HMD) to determine the likelihood that members of the public would be in the vicinity of Transgrid’s assets. HMD is not new, but applying it to accurately determine public expose to power system assets was a novel approach.
  • Automating the individual calculation of the risk cost for each of Transgrid’s 38,000 transmission line poles and towers, and the several individual asset components which make up a transmission line.

2.6. Program and project management

The key milestones for the project were:

  • Starting with the identification of need for the project during 2018/2019, based on feedback from the AER and other consumer groups.
  • During 2020, Transgrid subject matter experts surveyed the industry for best practice, and developed enhancements to our decision making frameworks and analytic systems.
  • From June 2020 to July 2021, determined how to obtain and use human movement data to calculate human exposure hours near Transgrid assets.
  • During 2021, Transgrid consolidated its asset information, modelled asset health and calculated public safety risk for all assets in alignment with its decision making frameworks. In addition, Transgrid refined its capital portfolio optimisation processes.
  • In 2021, Transgrid engaged a technical expert to undertake a technical assurance of its project scoping and estimation processes, and its repex program inputs. The outcomes of this independent review were that these elements are in line with good industry practice.
  • Finalised the development of the public safety modelling for input into the investment framework – November 2021
  • Finalised our capital portfolio – December 2021.
  • Initiated a number of improvements to public safety awareness, climbing control measures and design practices based on the new modelling– February 2022.

3. Benefit of the project to the community and organisation

The enhanced investment approach target’s assets with elevated probabilities of failure that can lead to hazardous events (e.g. transmission line conductor drops) in combination with locations of high criticality (e.g. people often near our assets, based on human movement data). The system enhancements undertaken to align with Transgrid’s enhanced risk assessment methodology provide significant secondary benefits to Transgrid. It provides an efficient, replicate-able and maintainable
tool to update risk costs across the entire asset base. Traditionally it has taken hundreds of man hours, and as a consequence, such updates were rarely undertaken to calculate Transgrid’s asset risks. Now asset health indexes can be re-calculated within a few minutes and refreshing asset risk costs in a few hours. The enhanced risk methodology also identified transmission towers which are more at risk to be illegally climbed, placing the climber at significant risk of serious injury. This information will then trigger the upgrading of designs, upgrading climbing deterrents at high risk locations and changes to Transgrid’s, public awareness strategies. The exposure data is also used as input into earthing system design which previously relied on assumptions around public proximity as part of the design process.

4. Specific contribution

To ensure Transgrid’s approach was best practice, the Asset Management team considered guidance from the Australian Energy Regulator, sought advice through industry working groups and from subject matter experts from across the industry. The Transgrid Advisory Council (TAC) is the main forum used by Transgrid for engagement with a range of external stakeholders including AEMO, local councils, Clean Energy Council and consumer advocacy groups. The TAC met monthly from June 2021 to December 2021. Most of our TAC members agreed or strongly agreed that our approach reflects our customers’ priorities and preferences. Transgrid worked with AMCL and mapdata (a geospatial data provider) over a 12 month period to develop a methodology to determine human exposure hours within close proximity to its assets, such as transmission line structures, lines and substations.

Transgrid’s Asset Analytics and Insights team developed a consolidated asset data source, the associated calculations and SQL scripting over a 6 months period. This challenge required intimate knowledge of the various systems, the databases, the structure of the data contained within, the logical linkages, the data
itself and scripting ability. Enhancing the asset health indexes took 10 weeks to develop, with the Asset Insights and Analytics team working closely with the asset strategists. Whilst developing the asset risk costs required 3 months to develop including subject matter expert review and assurance. To accurately calculate and quantify each asset’s public safety risk, based on the all the principles set out in the Network Asset Risk Assessment Methodology, Network Asset Criticality Framework and Network Asset Health Framework required 3 months effort. Effectively bringing together all the inputs, models and other various facets to arrive at public asset risk $. It was a large and challenging task to bring it all together, and was only achieved by a collaborative effort from across the organisation.

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