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District Heating
Think district heating differently: Make data-driven decisions
Design efficient and economically viable district heating systems.
What if you could:
• Optimize system operation
• Make informed decisions
• Transition smoothly towards a sustainable future
With energyPRO, you can. It’s not just a tool – it’s your solution for navigating the challenges of modern district heating.
Tackling today’s district heating challenges
Key priorities include
Minimizing system imbalances
Reducing costs with smart heat delivery
Using the most cost-effective production units
Meeting market and contract obligations
Ensuring clear, transparent tariffs and billing reuse.
Investing in secure, future-proof solutions
Overview of the System Modeled
This case shows two different approaches to district heating modeling and applications of energyPRO in district heating analysis:
1
Investment Analysis:
Evaluate and plan future-proof, regulation-compliant, and cost-effective investments in efficient and easy-to-operate heat production units, ensuring security of supply and alignment with public and political expectations.
2
Scenario Analysis:
Investigate different scenarios in terms of operation, to understand the robustness of the investment scenario.
Case, Scenarios and Assumptions
The base of the analysis is to investigate an existing gas-based district heating plant placed in Denmarks bidding zone DK1, called Varmestrup (Heating-vile).
Today Varmestrup has two gas engines and one gas boiler together with heat storage.
Varmestrup needs to make new investments that are in line with regulations, future development of surrounding markets, and to meet the local opinion that their heat production should be greener and cheaper (increasing competitiveness).
Varmestrup is considering the following technologies for lowering emissions, but also overall heating prices:
- Biomass boiler, based on local straw production
- Air-to-water heat pump system
- Solar thermal plant
(All technology costs are based on the Danish Energy Agency technology catalogue).
Varmestrup is interested in selecting the most cost-effect solution and based on that investigating the effect on the heating costs of the system that today’s users are subjected to.
Below are listed some assumptions for the Varmestrup analysis:
Parameter
Value
Total yearly heat demand, MWh
100.000
Gas engine 1 & 2 heat and power capacity, MW-h/MW-e
7/3
Gas boiler heat capacity, MW-h
16
Heat storage capacity, MWh
60
Peak load heat demand, MW-h
28 MW
Biomass prices, local straw, DKK/ton
816
Gas prices
ETF daily spot 2024
Power prices
DK1 spot 2024
Modeled Components in energyPRO (some selected highlights)
1
Distribution of heat demand
- Using the built-in wizard, the total yearly load is distributed over the year based on the measured temperature.
- Splitting the heat demand to a degree dependent and degree independent demand, which is split over the day with a fixed profile of demand.
2
Varying heat storage capacity
- The capacity of the heat storage is determined based on the measured forward and return temperatures.
3
Heat producing units
- Technical power curves, including operational settings, are modeled for each unit.
- Specifically, the coefficient of performance (COP) distribution for the heat pump is included.
4
Investments scenarios
- energyPRO uses the Danish Energy Agency’s Technology Catalogue and the OPTIMZE module to determine the required capacities based on input assumptions. These can also be explicitly visualized in the COMPARE module (scenarios).
- The INTERFACE module evaluates how robust the created scenario is compared to the base case.
How energyPRO adds value
Feature
What you can do with energyPRO
What you get
Component-based structure
Add/remove units with minimal reconfiguration
Fast modelling setup
Optimal production plan
Generate an optimal production plan that dispatches units based on cost and defined assumptions
Reveals the most economical combination of production units
Advanced COP definition
Define advanced COP settings that incorporate temperature variations
Increases model realism with only a small change in inputs
Investment capacity sizing
Apply price signals and input assumptions for automated capacity sizing
Provides insight into the most beneficial size and type of new units
Visualization
Use built-in visualization tools for time-resolved views of energy use and cash flow
Improves system understanding and supports better communication of results
Preview of the project in energyPRO
Base model
OPTIMIZE setup
INTERFACE/COMPARE setup
Input
INTERFACE/COMPARE setup
Output
Key figures
Summary
This case can be used as a prefeasibility study for Varmestrup or other district heating systems. For more detailed analyses, energyPRO offers advanced calculation capabilities.
energyPRO also integrates seamlessly with tools like Excel and Python, enabling flexible workflows and customized analysis.
The modules you need
Key modules for District Heating use case
INTERFACE
Massive scenario running (good for testing robustness of scenarios)FINANCE (optional)
You can add FINANCE to add the possibility of running multiple years.ACCOUNT (optional)
Add ACCOUNT to add more features related to an in-depth feasibility study.
Learn. Apply. Succeed: Your energyPRO Training Hub
This use case is illustrative, not prescriptive. Proper dimensioning requires hydraulic and biological expertise. Still, it shows how engineers can use energyPRO to simulate dynamic, modular water-energy systems — a vital step toward smart, cost-effective infrastructure.
Dive into our comprehensive courses, webinars, and tutorials to master energyPRO’s powerful features.
