Thermal energy network feasibility, settled in one model.
Campuses, federal bases and data-center districts are moving heating and cooling onto shared ambient loops, geo-exchange and heat pumps, the thermal microgrid. Sympheny sizes the network, picks the supply mix and stages the build in one run, so your engineers compare cost against carbon on real hourly demand before the feasibility study is written.
Every supply-and-network option for a thermal energy network on one chart: life-cycle cost against carbon, from a single project.
What campus and federal thermal energy network teams are up against.
Aging central plant meets a decarbonization mandate
Steam and hot-water plant on campuses and bases is reaching end of life just as decarbonization targets land. A thermal energy network, an ambient loop with distributed heat pumps, is the route most studies point to, but proving it out against the existing plant on cost and carbon is the hard part.
Electrification piles load onto a constrained grid
Swapping boilers for heat pumps moves the load onto the electric side, where interconnection queues already run for years. A network that shares and balances heating and cooling across buildings cuts the peak electric demand, but only if the loop, the sources and the storage are sized together against the real hourly profile.
Feasibility studies have to be defensible
Federal programs, funders and A&E clients want the evidence behind the recommendation, not a spreadsheet with two options. A thermal energy network feasibility study has to compare ambient-loop, geo-exchange and conventional options on the same basis and survive review.
Size the network, the supply mix and the staging in one optimization.
Sympheny models the buildings, the ambient loop, heat pumps, geo-exchange, recovered heat and storage as one multi-energy system and optimizes it with mixed-integer programming. The network temperature, the source mix and the build order come out of the same run, compared on life-cycle cost against CO2 on hourly demand, rather than stitched together from separate studies.
Model the campus or district as it actually is.
Start from the site, not a blank sheet. Sympheny's GIS-enabled view holds the buildings, their heating and cooling demand and the local resources, geo-exchange potential, recoverable heat, water, so the network reflects the real thermal density and what the site can actually draw on.
- GIS site view with buildings, hourly loads and network routes
- Geo-exchange, recovered heat and water sources mapped in
- From a single building up to a whole campus, base or district
Co-optimize the ambient loop and the supply mix.
Heat pumps, boreholes and geo-exchange, recovered heat, storage and any conventional backup enter the same optimization. Sympheny picks the network temperature and the source mix together, so a low-temperature ambient loop is compared against the alternatives on cost and carbon inside one model.
- Ambient-loop and conventional network options compared like for like
- Heat pumps, geo-exchange, recovered heat and storage sized by the engine
- Bidirectional heating and cooling balanced across the network
Decarbonization pathways, stress-tested.
A feasibility study gets challenged. Sympheny runs multiple decarbonization pathways and stress-tests each against shifting energy prices, electrification load and interconnection limits, so the recommendation holds when the assumptions move and when a reviewer asks why.
- Multiple pathways from cost-optimal to carbon-optimal
- Automated sensitivity analysis on the key assumptions
- Underlying data exported to Excel for the study deliverable
Show what each level of ambition costs.
Instead of a single answer, Sympheny returns the trade-off between life-cycle cost and emissions as a Pareto front, with the build order staged. Decision-makers see what the cost-optimal, the carbon-optimal and the viable middle path each cost before committing capital.
- Pareto front of life-cycle cost against CO2
- Staged build-out: what gets built first, what follows
- Investment and capacity overviews straight from the platform
For the program or developer, the feasibility study lands as a costed answer: what each level of decarbonization costs, the lowest-cost network that meets it, and the staging that fits the budget and the interconnection timeline. The figures are directional, from the project model, not a guaranteed outcome for a specific site.
Sympheny is the upstream optimization layer: it decides which thermal energy network is worth building before any pipe or heat pump is specified, then hands the concept to your A&E firm's detailed mechanical design. Our optimization engine has been applied in US Department of Defense thermal energy network feasibility studies under the ESTCP program, alongside Lawrence Berkeley National Laboratory and Modelica-based tools. It is not a substitute for detailed hydraulic or mechanical design, and not the formal interconnection request to the utility.
Sizing low-temperature networks against real demand is what we do.
A low-temperature thermal network moving 90,000 MWh a year of heating and cooling, modeled across six hubs and 30+ scenarios, the ambient-loop problem a campus or base TEN poses.
Read case studyA district roadmap testing whether on-site and wastewater heat could anchor an ambient network, reaching an 83% CO2 cut by 2040 across three fully costed pathways.
Read case studyA district network expansion across 74 buildings, five candidate segments and three plants, with the build order staged and the source mix compared in one model.
Read case studyBuilt for the feasibility decision, with the pedigree to back it.
Plenty of tools touch parts of thermal energy network planning. Sympheny is built for the specific decision a feasibility study has to defend: which network and supply mix to build, and why.
Not detailed mechanical design
Hydraulic and mechanical design tools size pipes and plant once the concept is chosen. Sympheny sits upstream, deciding which network and supply mix is worth building in the first place.
Empa / ETH technology pedigree
Sympheny is an Empa spin-off out of the ETH Domain, with 10+ years of R&D behind the optimization engine, the same Swiss lab lineage behind early ambient-loop and 5GDHC networks.
Applied in US federal energy work
Sympheny's optimization engine has been applied in US Department of Defense thermal energy network feasibility studies under the ESTCP program, as the design-optimization layer that compares system options on cost and energy ahead of detailed mechanical design.
TEN feasibility, explained.
What is a thermal energy network?
A thermal energy network (TEN) connects buildings to a shared loop that moves heating and cooling between them, usually a low-temperature or ambient loop with distributed heat pumps and sources like geo-exchange or recovered heat. Because it is bidirectional and low-temperature, it can reuse heat that would otherwise be wasted and run far more efficiently than a conventional high-temperature steam or hot-water system. It is also called a fifth-generation district heating and cooling network (5GDHC) or an ambient loop.
What is a thermal energy network feasibility study?
It is the upstream analysis that decides whether a TEN is worth building for a campus, base or district: which buildings to connect, what network temperature, which sources and storage, and how it compares to the existing plant on life-cycle cost and carbon. Sympheny runs that analysis as a multi-energy optimization and returns a Pareto front of options with a staged build order, rather than a single recommendation.
How is a thermal energy network different from traditional district heating?
Traditional district heating distributes high-temperature hot water or steam from a central plant in one direction. A thermal energy network runs at low or ambient temperature and is bidirectional: each building can draw heat or reject it, with heat pumps lifting to the temperature needed locally. That lets the network recover and share low-grade heat, couple heating with cooling, and run at much higher efficiency, which is why campuses, bases and data-center districts are moving to it.
Can Sympheny model geo-exchange and ambient loops?
Yes. Geo-exchange (borehole fields), ambient loops, distributed heat pumps, recovered heat and storage all enter the same optimization as candidate technologies. Sympheny sizes them against the site's real hourly heating and cooling demand and picks the network temperature and source mix that meet the cost and carbon targets, so the ambient-loop concept is compared against the alternatives on the same basis.
Does Sympheny support DoD, federal and ESTCP feasibility work?
Sympheny's optimization engine has been applied in US Department of Defense thermal energy network feasibility studies under the ESTCP program, alongside Lawrence Berkeley National Laboratory and Modelica-based modeling, as the design-optimization layer that compares system options on cost and energy. It is used as the upstream concept-stage tool ahead of detailed mechanical design, not as a replacement for it.
Where does Sympheny fit alongside our A&E firm?
It sits upstream of detailed design. Sympheny answers whether a thermal energy network is the right system and which configuration to build; your A&E firm takes the chosen concept into detailed hydraulic and mechanical design. The two are complementary stages. Most of the decisions that determine whether a TEN pencils out are made at the concept stage Sympheny is built for.
Related US planning topics and proof.
Run the feasibility study on numbers you can defend.
Bring a campus, base or district to a demo and watch the network, the sources and the staging resolved in one model, or start a free trial and build the first concept yourself.
