Demand Analytics

Levels of peak electricity demand are known to affect the necessity and extent of network upgrades. This means that to plan the network efficiently and effectively, greater understanding of local demand trends is required.

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Demand is affected by various aspects of the weather, especially temperature. But when it comes to looking at how weather impacts the delivery of electricity, the data is generally based upon a simplistic, high level model that looks at weather across a wide geographical area.

This makes it extremely difficult to separate the effect of weather versus consumer behavior on demand, and results in planning and investment uncertainty.

Given that generation output levels are known, our model exposes underlying trends by quantifying weather driven demand. This enables us to create scenarios using a range of weather and generation inputs that allow asset owners to see how their network will respond to future weather events.

By understanding demand at this level of granularity, we can provide asset owners with the tools to improve the targeting of investment, while helping them to develop tools to deal with the modernization and decentralization of the distribution network.

Asset Health

A wide range of environmental conditions, especially wind, are known to impact the wear of overhead lines (OHL) conductors and fittings, influencing how long they can reliably function before they need replacing.

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Unsurprisingly, assets with a higher level of exposure are at the highest risk of damage. Increased exposure stems from a combination of factors, including local weather characteristics, the type of landscape and the mechanical properties of the assets themselves.

Depending on the levels of exposure, different assets have varying rates of deterioration. By understanding the expected level of exposure on a span-by-span basis, asset owners can optimize investment by delaying or advancing re-conductoring programs, adjusting fittings maintenance/painting schedules and improving asset inspection/monitoring processes.

Utility companies already employ methods of classifying OHL spans in terms of wear and defects, but our technology provides this same data in less time and at reduced expense, without resorting to invasive or destructive testing.

By quantifying the effect of both wind exposure and corrosion on the expected defect rates of OHL assets, this data enables the optimization of investment by providing a clearer understanding of asset deterioration over time.

We are able to apply our wind-induced wear and corrosion models to any OHL asset, anywhere on the planet, and calculate asset life modifiers that will not only optimize asset management strategies, but also increase system reliability and protect investment.

Renewable Forecasting

As the volume of renewable power connected to the grid increases, it presents energy utilities with both exciting possibilities and demanding challenges. This means that understanding when and where this energy will be produced is more important than ever.

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By utilizing high quality meteorological data, which is refined using specially-designed adaptive models, we can provide highly-accurate long and short-term forecasts for wind and solar production anywhere in the world. These forecasts not only enable a better understanding of the impact of renewable energy generation on power prices, but also of the amount of energy that is likely to be generated. This means demand can be matched to supply, minimizing the risk of imbalance.

Our methodology is industry-leading in terms of quality and accuracy, combining our inherent understanding of technology with meteorological data from high-quality weather models. This allows us to deliver extremely accurate power forecasts that are able to pinpoint region, time-step and delivery time.

A fully customizable service, it can be tailored to meet any requirement, with predictions supplied anywhere from one hour to two weeks in advance, with regular updates provided exactly when needed, resulting in a deeper, more insightful understanding of the data.

Constantly refined and evolving, our advanced models provide brilliantly reliable forecasts, the data from which helps to maximize returns from energy trading, minimize imbalance costs, inform operational decisions and aid energy integration.

Extreme Weather Analysis

Weather conditions can present significant challenges to transmission and distribution companies. Better understanding of them can therefore improve design, planning, safety and, ultimately, the cost related to Overhead line (OHL) routes.

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To be really effective, any weather data used to inform decision-making needs to be highly accurate, which means it needs to be specific to individual towers.

Consequently, as part of this weather analysis, we report on the wind and icing characteristics at every tower location on the OHL route. Our clients can then use this information to identify cost saving opportunities on foundations, steel works and labor.

The tower-specific nature of this data also enables development teams to make informed decisions on the risks associated with weather exposure, as well as future weather risks for different spans across the route.

If undertaken early in the project, this analysis allows companies to improve planning and costing, while also increasing safety. It also facilitates the delivery of better design solutions and offers easier integration with standard processes​.​

This has already been tested on more than 1000 OHL towers, so an uncertainty report is readily available if desired.

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