Digital Engineering will be at the 47th CIGRE Colloquium in Paris
August 24, 2018
Rob Sunderland and Aleks Modelewska will be attending the 47th CIGRE Colloquium in Paris next week. They will be discussing solutions and possibilities brought by data analytics to the processes of operations and maintenance in the utility sector. If you are interested in learning about how Digital Engineering can help you with prioritization of overhead […]
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Digital Engineering’s Bristol team take to the skies!
August 24, 2018
Last week Digital Engineering’s UK office team had the experience of a lifetime, taking a hot air balloon flight over our home city of Bristol The trip was to celebrate the successful conclusion of our innovative Overhead Line Asset Health project, working with the National Grid’s innovation team to improve how they classify Overhand Line […]
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Welcome to our newest team member.
May 23, 2018
We are delighted to welcome Aleks Modelewska to our team. Aleks will be representing us in the US as Business Development Executive for Transmission & Distribution. She completed her studies at McGill University, located in Montreal, Canada. Prior to Digital Engineering, she spent several years at CEATI International, leading the transmission, protection & control, vegetation management, […]
Read moreWe’re at the IEEE!
April 5, 2018
This week Rob and Aleks are representing us at IEEE PES T&D Conference in Denver, CO. Join us at booth 464 to learn more about our innovative products and services, and enter the competition to win a “ReMarkable” Tablet (www.remarkable.com)! We will be presenting a Products & Services Session on Wednesday 18th at 8:00am in […]
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Line Rating Assessment Pilot Project
Digital Engineering (DE) has developed a system that uses weather modeling and data analytics to assess the effects of weather on the static line rating for each span, to identify routes that can safely have their static line ratings increased.
Wind-induced Wear and Corrosion Assessment Pilot Project
Using data analytics and weather modeling, Digital Engineering can accurately predict spans with a high likelihood of defects, leading to more cost effective inspection programs, optimal asset management strategies and the potential of millions of dollars of savings in deferred asset replacement.
Weather-Normalized Demand Analytics
An original study was led by Digital Engineering Ltd. (DE), in which the effect of weather patterns and consumer behavior on peak electricity demand were analyzed at the level of individual substations. The described method was applied to a distribution network managed by a Distribution System Operator (DSO).
Creating more powerful power forecasts for Bloomberg
With weather the most frequent driver of short-term movements in the power and gas markets, Bloomberg wanted access to reliable energy forecasts.
Exploring the effect of exposure on asset degradation for the National Grid
The National Grid wanted to find a way to accurately predict the degradation of their assets due to environmental exposure.
Analyzing the impact of weather on demand for SP Energy Networks
SP Energy Networks wanted to find a way to separate the effect of weather and consumer behavior on peak demand at a more localized substation level, instead of just license level.
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