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less controllable and predictable – and the sheer number of them can become overwhelming. "This means that asset manage - ment needs to become much, much smarter: using big data to identify trends and patterns from millions of assets and using machine learning and artificial intelligence (AI) to respond quickly to changes," says Barnfather. "We need to ensure that our networks are fit for the future and improving our asset management will be a key part of that." Embracing innovation New technologies offer a raƒ of opportunities for networks to improve the collection of asset condition data and trigger maintenance tasks when they are required. AI and analysis of condition points is increasingly used to give asset managers early indication of potential faults on the network. An example of this is the work WPD is doing with Dynamic Rat - ings to fit condition monitoring equipment to some of its 132kV tap- changers. The equipment measures the operation of the tapchangers in real time and also collects more long-term data to help assess the duty that has been placed on the asset. The condition monitoring equipment records operational data on the unit but also checks for signals which could help identify a failure developing, such as an unexpected change to the tempera - ture of the unit or a change to the operation of ancillary items. "Some changes are within toler- ance but others may fall outside and the system will use AI to work out the difference and prompt us so that we can take action and avoid the units deteriorating," explains Ketley-Lowe. As energy networks transition to a smarter, more flexible system, the availability of data that can confirm the condition and performance of assets is crucial. But the use of big data and innovation to improve asset management plans and pinpoint vital areas for investment is not the preserve of electricity networks. Northern Gas Networks (NGN) is utilising new technologies and new ways of working to capture asset in - formation that informs key decision making and allows the business to accurately plan asset management activities. NGN owns and maintains around 1,700km of large diam - eter gas mains, stretching across Cumbria, Yorkshire and the North East – all of which require regular maintenance and assessment. Traditionally, asset assessment and repairs typically require an excavation at each point of enquiry which can be expensive, disruptive and presents safety and environ - mental risks. The development of robotic platforms, camera systems and pipe access technologies are creating opportunities for networks to undertake complex activities with minimal disruption. "While CCTV camera systems and robotic platforms have been increasingly available over recent years, these are typically expensive to deploy, and cost benefit assess - ments do not always make this a viable option," admits Richard Hynes-Cooper, head of innovation at NGN. Mitigating cost concerns, NGN is involved with an NIA-funded in - novation project called System Two Access and Seal (Stass) that has allowed the company to embrace robotics to deliver speedier repairs and maintenance across its under- ground network. New technologies The company's "robo-engineer" NETWORK / 21 / SEPTEMBER 2019 can travel up to 250m along the length of an underground gas pipe to carry out a repair. It is equipped with a camera that transmits live footage of a pipe's condition and it can treat imper- fections in a pipe by applying a "flexspray". Nicknamed Stan, the robot is being used on large diameter pipe projects, which can be particularly disruptive to motorists, and ex- pensive to carry out. The company says it is currently using robotics on an average of two jobs every week, saving time and money, and reducing disruption for customers, by limiting the number and size of holes that need to be excavated. Hynes-Cooper added: "By using the robot, we can reduce the number of holes we need to dig to carry out routine repairs and main - tenance on our larger pipes. This is good news for motorists, as it means fewer roadworks, and good news for the environment, as we don't need to dig as many holes. "Stan will also help us keep customers' bills affordable. Early indications are that we can save £2,000 per job, by getting the work done more quickly and efficiently." The robotic platform is delivered as an in-house service by NGN operators and allows the capture of asset data at a more economical rate – an increasingly useful tool as the network seeks to become more resilient to future demand. "As we move to a smarter, more flexible energy system, the avail - ability of data that can confirm the condition and performance of as- sets is crucial," says Hynes-Cooper. Indeed, any change on network de- mand, transportation requirements and whole-system solutions must be underpinned by accurate data and a comprehensive understand - ing of asset condition. As the industry looks to the smarter, more flexible energy system of the future, there remains the consistent objective to improve network resilience. "Both of these are possible," insists Barnfather. "But it will require a shiƒ in mindset away from centralised planning around assumed scenarios and a move towards more dynamic, data-driven decision making." Above and inset: NGN engineer Gary Pickles and the Stan robot, which can travel up to 250m along the length of an underground gas pipe.