IIOT Power

Big Data Rewrites the Rule Book on Power System Risk Analysis

Extreme weather patterns, net zero acceleration, and shifting regulatory regimes demand a new methodology to assess and mitigate network challenges across both the immediate and long term.

The integrity, performance, and flexibility of energy networks have become progressively more important in the face of rapid technological, economic, and environmental change. And the challenges in maintaining robust systems are only made tougher by increasingly complex grid systems, the demand for ever more reactive response times, and higher levels of unpredictability—including, but not limited to, extreme weather, fluctuating demand, and intermittent supply.

Real-time, rigorous, and data-driven assessment, therefore, has a significant role to play in the operation, maintenance, management, and investment planning of modern networks, whether electrical, gas, or hydrogen. The key is to determine probabilistic risk levels, and to act on the information provided, when making decisions at all levels and stages. Application of the philosophy results not only in increased efficiencies but also reduced costs over both the immediate and longer terms.

The Norwegian company Promaps Technology, which Vysus Group acquired earlier this year, occupies a unique place at the leading edge of that next-generation solution. Its software is designed to navigate through, and mitigate against, a multitude of destabilizing factors.

More Than a ‘Gut Feeling’

The methodology developed by Promaps is based on granular data drawn from across a given network, such as transformers, capacitors, switch gear, and cabling, and includes variables such as power flows, temperature, vibration, and weather conditions, among others (Figure 1). Historic data such as failure rates and performance are also reflected in the algorithm.

1. Using the power of Big Data, Promaps provides a decision-making methodology based on more than a “gut feeling.” Courtesy: Vysus Group

The process is defined across four distinct steps: apply the power of Big Data, create insight into inherent risk properties, determine proactive actions to mitigate fast-changing risks, and deploy real-time system data as the baseline for future decisions. It is a dramatic departure from what has traditionally been a disparate, individual, and ad-hoc series of risk assessments based more on “gut feelings” than any systematic application of the information available.

With our approach, an accurate picture of performance is established both in real time and over time, providing a risk assessment profile that can be used to manage operations, schedule and prioritise maintenance, and plan investments or network augmentations. Clients can access the information via a straightforward control centre dashboard either through direct two-way connection to dedicated servers or, for larger customers with more complex systems, through an in-house or cloud-based interface. Early adopters to have tested the technology include Statnett, UK National Grid, Landsnet, Elvia, Lede, and Tensio, all of which are already realising the value in real-life applications.

Success in Critical Environments

In addition to the valuable insights into how any given network is operating, probabilistic risk assessment also provides the tools necessary to react to the ongoing challenges facing all power systems: maintenance and repairs, outages, and extreme weather. The latter is of increasing importance as climate events become more unpredictable; recent winter storms in the U.S. state of Texas were a stark illustration of what can happen when a network is unprepared, and then overwhelmed, by extreme conditions.

Modelling developed by Promaps already includes weather among other variables to be considered, for instance, the potential impact of wind on power line integrity and the network’s ability to cope with failures. However component-level inputs will provide additional and early indications of increasing risk in a system battling against mother nature. And while no system is 100% impervious to conditions, next-level risk assessment will minimise the exposure and allow for the planning necessary to insulate against the worst.

Outside of storms, outages linked to equipment failures can also be both predicted and mitigated under the Promaps methodology, avoiding price tags that can quickly escalate into significant sums and—over 12 months—into hundreds of millions. In one example, the company’s technology pinpointed a problem component a full 19 hours before it reached a critical stage. Not only does this save millions, it can help keep communities safe.

Maintenance is also key to network integrity. Using probabilistic risk assessment, operators can predict the impact of scheduled works; highlight any knock-on effects from overlapping, delayed, or overrunning repair programmes; and weigh the wider options for action in what is an increasingly complex infrastructure class. And data built over longer periods will provide additional detail on which components have the biggest impact on system integrity, on where maintenance should be prioritised, and on the cost-effectiveness of competing solutions.

Planning for the Future

In addition to immediate applications, information presented through next-generation probabilistic risk assessment can also be leveraged to optimize the planning of longer-term decisions on grid expansions and investments. The technology allows various scenarios to be considered such as the impact on the wider system of a given upgrade, high-detail comparisons between different investment options, and the cost-benefit of different generator/supply models. And of course grid augmentation planning is also supported.

Even specific variables such as spinning reserve can be considered, including where on the network it should best be located to maximise effectiveness. Furthermore, scenarios for future connections to any system can be mapped, avoiding the point at which costs outweigh contributions. The unique package of risk assessment data also extends to the optimisation of an existing network including inputs from renewables, battery storage, and traditional generators with an eye to meeting net-zero requirements and making a meaningful contribution to the ongoing energy transition.

Scope to Go Further

The potential of probabilistic risk assessment does not stop with national networks—it can be expanded both across entire energy systems as well as internationally. On the former, Promaps offers a vision for large consumers of power, such as data centres or smelters, in which the software monitors and profiles not only their internal power needs but also that of surrounding networks—protecting security of supply across both while providing for load management in times of highest risk.

This level of coordination, taking in industrial customers, as well as transmission and distribution operators, has the potential to achieve significant optimization of any network; simultaneously balancing the needs of the entire power system to the benefit of all. The approach could further extend to coordination across networks of different stripes; one might imagine national-level risk assessment of a country’s electricity, gas, and hydrogen grids, for instance, ensuring security of supply in real time in the face of ever-changing demand, supply, maintenance, and weather profiles. And in an increasingly interconnected world, legislation such as that already being introduced in the European Union and under discussion in markets including Australia will require grid operators and utilities to risk-assess the impact of actions both short and long-term, and on neighbouring and interlinked systems.

Networks for Today and Tomorrow

Modern power infrastructure is facing unprecedented demands for change as the global journey to net zero accelerates toward its goal. And the challenges are not limited to the shift from very large fossil fuel generation assets to more decentralised, renewables-rich networks. Extreme weather, increased cross-border interconnection, and new regulatory regimes bring their own demands.

At Vysus Group, we believe probabilistic risk assessment, delivered in real time, should form the basis of every decision in this modern energy landscape. There are efficiencies to be gained, and potentially large amounts of money to be saved, across the value chain.

Calculations based on dependable, tested information—rather than gut feelings, however well informed—will optimize the full range of power system activities including operations, maintenance, reinvestment, and long-term planning. Crucially, it will also help to deliver the networks necessary not just for today, but also for tomorrow.

Mark Andrews is vice president of Grid and Power Systems at Vysus Group, and Arne Brufladt Svendsen is vice president of Vysus Group—Promaps Technology.

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