Case-studies
Leading energy and real estate companies use Urbio to outpace the industry
Making the right choice when developing district heating networks requires careful analysis of all available options.
Rafael Mesey, Head of Department New Energy
The challenge
-
Lack of data on buildings and areas of interest
-
Changing environment requiring multiple repetitions of analyses
-
Time-consuming methodology for evaluating multiple scenarios
"Feasibility studies are vital to our work, but also time-consuming given the large amount of data and scenarios to consider."
Benefits Achieved
-
5x faster analysis enabled by instant map generation and computation of metrics
-
Faster ROI achieved by sorting out and focusing on the most high-impact buildings
-
3x more scenarios evaluated within the area of interest for feasibility studies
-
High data accuracy guaranteed by relying on certified industry norms and enhanced by Machine Learning and energy models
-
Streamlined workflow from data import to visualization of building data, to calculation of key project metrics
The project
CKW needs to know which areas to prioritize for a new district heating network (DHN) deployment.
Today, this activity involves a lot of manual effort: collecting building attributes from spreadsheets, applying complex formulas for estimating demands and mapping this data to footprints in a GIS tool for visualization and prospection purposes.
With Urbio, the full process was automated, hours of work were saved, and the team could focus on the exploration of scenarios with the support of maps and key metrics.
1. Centralize available data
2. Identify most suited areas
3. Get key metrics
I used Urbio for several district heating network projects in order to accelerate the development of our renewable activities. I am very happy with the results, in particular the screenshots and metrics which I showcased to our partners.
Rafael Mesey, Head of Department New Energy
