Explore Asset Life
Forecast & Investment
- Create long-term investment plans that minimize financial risk
- Decisions that reduce CAPEX by 35%
- Maintain and improve network reliability
- Optimize within budget constraints
- Make and compare future scenarios
- Integration with GIS and metering databases
Maintenance & Planning
- Mobile application for registering all asset replacements, repairs, and inspections
- Insights that reduce OPEX by 25%
- Resource planning with GANTT overview
- Easy access to instructions and data manuals
- Integration with ERP and GIS systems
- Aligned with DS/IN 13306 and ISO 9001 standards
- Open-source risk assessment software for regulators and data scientists
- Algorithms for probability of failure, consequences of failure and risk matrices
- Weibull analysis on failure statistics
- Train probability of failure models on new data and create new asset categories
- Aligned with ISO 55000 standards
We work for
In 2021 Ofgem (Office of Gas and Electricity Markets, the regulator in Great Britain) released the new updated CNAIM 2.1 version. In short CNAIM is an asset failure risk assessment model following the ISO 55000 standard based on the United Kingdom’s electricity distribution.
Veksel A/S who operates the electrical grid of Langeland, has purchased Utiligize’s Asset Life platform, in particular the Forecast & Investment tool to optimize investments to efficiently expand the grid.
We are very happy to expand our team and are welcoming Daryna Shybaieva, Kenneth Røsland Rosenørn, Sergey Klyapovskiy, Kristian Thy and Jens Knudsen to Utiligize. Daryna or ‘Dasha’ comes with unique experience from Ukraine where she led a team of GIS professionals, IT development- and IT infrastructure teams and is our infrastructure engineer.
There is great potential in increasing the efficiency of district heating consumption-, distribution- and production by managing district heating users’ consumption more intelligently. Optimized control of district heating units can improve energy efficiency in households and provide better cooling of the return temperature in the district heating system, thus reducing heat loss.
Eviny Ventures – a subsidiary of the Norwegian energy company Eviny – plus the privately owned Danish venture fond, 2L Holding, buys equity in Utiligize of close to 2M€, securing an ownership of approximately 11% each.
As electric utilities plan for a tsunami of electric vehicles and heat pumps, and a fresh boom of onshore wind and solar farms, it is interesting to look at the grid’s basic features: value and age.
Electric utilities are under enormous pressure to modernise their business practices and support electricifcation of transport, heating and industrial processes. At Utiligize, we optimize daily operations through data-driven decision making and present it to users through an intuitive dashboard and mobile app that provides task management, time registration, document management and a form-building tool.
Danish version here (Dansk version her). TREFOR El-net has chosen Utiligize’s software, Asset Life, to provide a complete overview of their current network loading and forecast of future loading considering different green transition scenarios.
At Utiligize, we’ve spent the last couple of years fine-tuning our asset management software to minimise costs for utilities. Losses are a key driver of costs, whether you operate a gas, water, heating or power network.
The Danish Energy Agency today published our report on how distributed energy resources (DERs) like electric vehicles (EVs), heat pumps and solar panels will impact the distribution grid in Denmark.
The green transition will require significant investment in utility infrastructure. Many countries have restrictive income caps or fixed tariffs that do not allow for investment to support the electrification of transport, heating and agricultural processes.
This white paper discusses a data-driven approach to investments, maintenance and containing risk, using forwarding looking asset management for utilities. Download a copy here.
We are extremely proud of Jules Truong, who finished his Master Thesis under Utiligize’s and Professor Pierre Pinson’s supervision. He applied machine learning to forecast production and consumption on Evonet’s (now merged into N1) network – from high to low voltage.