Powerful analytics tool identifies priority gas mains
25/08/2020 Probit Consulting
Advanced data analytics is being used to coordinate widescale iron mains replacement, driving efficiencies in the gas sector. Probit’s director of analytics, Dr Tim Watson explains how the company’s latest asset investment planning software is supporting Cadent’s strategic and tactical plans.
The quantity of work on gas pipelines from the Health & Safety Executive mandate requiring UK distributors to replace their iron mains by 2032 is driving the implementation of technologies that can help optimise and schedule programmes of work. For the UK’s largest distributor, Cadent, which manages a network of more than 131,000km, that means renewal of around/approximately 1,700km of iron mains annually
The scale of the works means that robust optimisation and scheduling of the pipe renewals has the potential to drive major cost efficiencies while still maintaining key performance targets, such as; interruptions to supply, health and safety, and environmental targets. Probit Consulting’s AIM – Asset Investment Manager – software, was selected in a competitive process for asset investment planning (AIP) solutions that could be deployed at the scale Cadent required.
AIM deploys powerful analytical capability to interpret dynamic relationships and optimise investment for specific operational requirements and performance targets over a given time horizon. It has the capability to:
- Measure the current health of assets and how they would perform over time
- Identify which distribution mains to prioritise for renewal
- Assess the relative benefit of each pipe renewal
- Understand the likely cost
- Coordinate the work so that it can be done in the most economical and timely way
Historically, such digital tools were not available and this kind of analysis would have been labour intensive, using an array of spreadsheets and databases showing cost assessments and work schedules. Further, the scale of Cadent’s asset base renders the problem intractable at asset level for more traditional AIP and project portfolio tools, resulting in the need to aggregate assets into cohorts or split the problem into many smaller ones. Both these approaches result in unnecessary and inefficient data processing and suboptimal decisions.
Gas companies and other asset intensive utilities like Cadent have a large quantity of good quality data about the age, size, materials, pressure and locations of pipes in the network and the AIM platform is designed to take full advantage of this data and connect directly with many data sources at asset level. These include business operations and asset management software, database management systems, geographical information systems (GIS) and spreadsheets.
Where data is limited, industry accepted models or expert opinion are used and stored in a templated model library in AIM. A governance strategy adopted to identify work required to improve the data and related models over time.
Cadent’s Distribution Mains Renewal plan is focused on low, medium and intermediate pressure pipes of two to 48 inches (50-1220mm) in local transmission systems and the AIM platform is being used for five purposes:
- To assess the health of each pipe and predict how it will perform over time, including how many failures it will have and how that will change with age, depending on materials and other factors
- To assess the consequences and cost of failure in terms of repairs, customer service and community impact
- To assess risk to the environment from release of carbon dioxide into the atmosphere
- To assess health and safety risk from gas potentially trapped in buildings – gas ignition could cause explosion with risk of fatality and injury
- To assess risk of interruption of customer supply and potential penalties
The key strength of the model for this application is that it can assess one pipe against another and indicate which should be renewed first. For example, the location of a given pipe might make it more expensive to renew, but if it is failing more often, and its failure has a greater impact on customers, the model can pick this up and show the greatest total benefit.
The model is programmed to ensure completion of the iron mains work by 2032, in accordance with the regulatory mandate. In December 2019, Cadent submitted its distribution mains renewal plan for RIIO-GD2, the gas distribution price control review that runs from April 2021 to March 2026.
The programme of works comprises three elements, the most significant of which is the HSE-mandated renewal of all iron mains of 8-inch (203mm) diameter and below, situated within 30m of a building. These pipes comprise 93% of all renewal work.
The second major element of the plan is other mains that are above the safety threshold and require renewal. This is cohort mainly comprises ageing steel mains. The third lot are the cost benefit assessment mains (CBAMs), which are not necessarily a safety risk but are failing and are cheaper to renew than maintain.
Given that Cadent also wants to undertake the non-regulated safety work and the CBAM work, the model can coordinate all three programmes together. Repairs necessarily carry on during programmes of renewal and the order of works impacts on the total volume of repairs. Rigorous analysis of the network and the schedule means the whole renewal programme can be delivered at optimal efficiency according to best performance and cost and within the regulatory timeframe.
The development of a monetised risk-based methodology and framework has made it possible to make consistent and robust comparisons between potential asset investments. The framework identifies the potential impacts of decisions made on individual assets through assessment of risk, consequence and financial cost of failure.
This means risk can be projected forward to determine whole-life cost of ownership. The effect of intervention plans and the associated risk impact can also be assessed, enabling the comparison of current and future risk with and without proactive investment.
The core of AIM is a powerful simulation and optimisation engine. Optimisation is performed using the leading commercial mathematical optimiser and has been particularly chosen for large-scale and sparse infrastructure problems. Combinations of drivers can be optimised including budget, resource, risk, serviceability, asset performance, whole-life benefit and whole-life cost.
AIM can produce risk maps, graphical representations that link cause and effect. They can integrate all the components required to make investment decisions and calculate intervention benefits, such as the new failure rate following proactive replacement.
The scenario builder within AIM enables the user to ask questions in an intuitive manner to assess the trade-off between risk, service and cost. Typical questions might be:
- If I do nothing, and just react, what will happen?
- How much will it cost to maintain current performance?
- What is the best level of service and least risk I can achieve with a limited budget?
- If I want to maintain my network in the same condition what
will it cost? - If I replace assets based on age what will it cost?
AIM has a built-in model equation editor that allows for any mathematical function, such as an estimated deterioration relationship, to be input and stored. This helps produce statistical models that represent asset performance and serviceability through time and other relationships such as costs and benefits.
Equations may be as simple or complex as required and a full audit trail means they can be saved in a model library and evolve over time as new data or expert opinion becomes available. Results can be compared across simulations and optimisation scenarios; exported from within a scenario; produced spatially, at asset level; and extracted from drilldowns into the data itself.
All scenario results can be exported from AIM at asset, or any aggregated level, to give short- and long-term programmes of work, identifying cost-beneficial projects. This output is typically imported into client GIS and business intelligence software for sense checking and validation.
Sam McGauley, RIIO-GD2 mains renewal investment lead at Cadent said, “The GD2 Distribution Mains Renewal programme is a massive undertaking and the models generated by the AIM software are already providing us with a level of detail on pipe condition and costs we haven’t had previously. Building on the work we did with during the RIIO-GD1 price control, we have refined the digital tools over the last two years to help with Cadent’s RIIO-GD2 submission.
“Once the strategic plan is approved, I’m looking forward to moving on to the tactical plan, where we use the model to identify specific pipes, based on further analysis. By inputting additional data and running models we expect to be able to be able to prioritise renewals.”
“Once the model is finalised and the plan submitted to Ofgem, we will follow up further questions the regulator may have before we get the draft determination.”
At the time of writing, Ofgem was unable to say when the draft and final determinations for RIIO-GD2 would be delivered. A spokesperson said COVID-19 is having an impact on the regulator’s work and that of the industry and a review of all work is underway to ensure that protecting consumers is the priority during the crisis.
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Probit Consulting
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Web: www.probitconsulting.com
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