Municipal Energy Planning

Intep leaves no stone unturned for its municipal clients with Urbio

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Specialist of municipal energy planning for over 40 years, Intep chose Urbio to efficiently respond to municipal energy mandates, and rely on a replicable and science-based approach.

Customer

Intep

Sector

Consultant

Locations

Switzerland

Germany

In Urbio, complex data is clearly prepared and concentrated on the really important statements. This brings everyone on the same page when starting interdisciplinary projects.

Max Talmon-Gros, Project Engineer at Intep

Challenge

Intep approached Urbio to overcome 3 issues

Inefficient process for gathering accurate data over a perimeter
Tedious combination of spreadsheets and GIS tools
Inadequate macro analysis makes it hard to deliver actionable solutions to implement now

Benefits

95% reduction time to collect building data and design first maps for the report

All-in-one platform allows dynamic calculation and synchronized visualization with modern and beautiful GIS maps
Accuracy guaranteed by relying on certified industry norms and enhanced through the use of ML and energy models
Traceability of 100% of adopted data sources used in the projects
Actionable solutions defined down to the building scale

Solution

Intep was mandated to conduct a municipal energy plan for a Swiss-German municipality of around 1’500 buildings.

Today, gathering the key insights for preliminary municipal energy plan is challenging and takes a lot of time, mainly because the process requires starting from scratch in every new city.

With Urbio, gathering and visualizing data was easy and transparent. Combined with automatic scenario generation, Urbio provided a scalable solution to the municipality’s most urgent needs.

Today our projects require to consider larger perimeters which are difficult to handle with our standard DBs and tools. We need a tool to manage our projects with a complete overview.

— Max Talmon-Gros, Project Engineer at Intep

Structure the data

Relying on Urbio’s curated data and on the municipality’s own data, the energy engineer quickly set up an accurate digital twin of the building stock characterized by dozens of criteria.

Visualize the current state

Once the Digital Twin was built, the engineer selected the most relevant criteria to illustrate the municipality’s current state.
The instant creation of customized maps contextualized the analyzes and served as figures for the discussions with the stakeholders.

Identify the key levers

The engineer applied its custom filters and summary templates to quantify the impact of specific measures on the municipalities objectives.
Based on these metrics, the city was able to take strategic decisions such as targeting the most impactful buildings for retrofit measures or renewable electricity production.