Hourly energy data and AI ranked buildings by savings potential, letting staff target low-cost fixes across municipal properties.
The big idea
CASE STUDY PRESENTATION
Hørsholm cuts CO2 with AI energy management
Hørsholm used AI energy management in municipal buildings to cut energy use, CO2 and costs with a one-year payback.
Case Study
MitigationGrid-supplied EnergyWaterBehavior and capacityImplementation & operationsPhysical/technical solutionsResource efficiencyHealth & well-being
- 6% annual energy reduction
- 190 tons CO2 saved each year
- Payback in about one year
So what?
1
The Challenge
Hørsholm wanted to find energy savings in municipal buildings, but it did not systematically collect consumption data. A few manual meters existed but were rarely used, making it difficult to identify waste or prioritize action. The municipality needed an EMS as the basis for data-driven energy management.
2
The Plan
Hørsholm used data-driven energy management to move from limited manual readings to continuous insight. The EMS did not save energy by itself; staff used its prioritized recommendations to target practical improvements in buildings.
Step 1
The municipality allocated a budget for energy management and hired staff to find solutions.
Step 2
An AI-based EMS from Ento Labs was installed across municipal properties to provide hourly electricity data.
Step 3
The team also gathered water and heat consumption data from utility companies.
Step 4
AI analysis ranked buildings with the largest energy-saving potential and identified abnormal consumption.
Step 5
Service leaders and the energy team used the insights to launch projects, supported by recurring meetings and an annual energy management cycle.
3
The Results
190 tons CO2/yr
Annual emissions reduction
993 MWh/yr
Annual energy savings
6%
Total energy reduction
2.09m DKK/yr
Annual cost savings
The municipality reports a 6% reduction in total annual energy use across municipal buildings. Annual savings are estimated at 993 MWh and 190 tons of CO2, with electricity and heat savings of about 2.09 million DKK per year. Total investment was about 2.1 million DKK, giving an estimated payback of roughly one year.
4
Key Lessons
Data alone did not create savings; Hørsholm gained results by acting on the EMS recommendations. Central energy budgeting, trained staff and recurring meetings helped turn insights into concrete building-level projects.
- No systematic energy data
- Manual meters rarely used
- Savings were hard to target
Before
- Hourly consumption overview
- AI ranks savings potential
- Service leaders act on data
After
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