Plan a data center the grid can actually connect.
The hard part of a new data center is no longer the build. It is getting power. Interconnection queues run for years and grid capacity is scarce, so behind-the-meter generation, storage and microgrid options decide whether a site is viable. Sympheny models them together and builds the cost, CO2 and resilience case before any equipment is specified.
Every energy-system option for a data-center concept on one chart: life-cycle cost against carbon, produced from a single project.
Data centers get stuck on power and permitting, not efficiency.
Interconnection is the bottleneck
Grid interconnection queues now run multiple years in most US markets, and large new loads are increasingly told there is no capacity for them. The site, the capital and the demand are ready; the connection is not. Behind-the-meter generation and a smaller, well-evidenced grid request are often the only way to move.
Behind-the-meter generation is moving from optional to essential
When the grid can't serve the full load on the timeline, on-site generation, storage and a microgrid carry the gap, fully or in phases. Sizing that system against a real, variable load instead of a nameplate number is what makes it bankable and connectable.
AI load makes the energy case harder
AI and high-performance workloads swing sharply, pushing up both cooling demand and the grid capacity charge. A system sized on a flat average is wrong for real operation, and an oversized connection request runs straight into the queue. The load shape has to be modeled, not assumed.
Design the on-site system that gets the data center powered.
Sympheny models electricity, cooling, heat and storage together and uses mixed-integer optimization to find the mix of on-site generation, storage, flexibility and grid connection that meets the load at the lowest total cost, while hitting the CO2 and resilience targets in the same run. Where a district heating offtake exists, recovered server waste heat becomes a revenue line and a permitting lever as well.
Size on-site generation and the microgrid as one system.
Model PV, storage, gas, fuel cells and the cooling plant together rather than in isolation, so the microgrid is justified by the load it serves and the grid capacity it avoids. The system is sized against the site's real, variable load, not a nameplate figure.
- On-site generation, storage and cooling optimized as one system
- Microgrid sized against the site's real hourly load, not a peak guess
- Cooling capacity matched to AI and HPC load swings, not a flat average
Cut the grid request with behind-the-meter flexibility.
Optimize PV, storage and load flexibility against capacity charges and connection limits, so the request to the grid is smaller and easier to approve, and the energy bill is lower. A smaller, well-evidenced connection is what moves through a multi-year interconnection queue.
- Behind-the-meter generation and storage sized on the real load shape
- Flexibility used to shave demand peaks and capacity charges
- A smaller grid connection request, easier to approve and queue
Build a defensible Scope 1, 2 and 3 pathway.
Compare supply and technology options across the full emissions boundary, including PPAs and on-site renewables, with every option fully quantified, so the clean-power and carbon case holds up to scrutiny from regulators, hyperscale tenants and lenders. Each step is costed, not assumed.
- Scope 1, 2 and 3 emissions modeled together
- On-site renewables and clean-power sourcing compared on cost and CO2
- Outputs ready for permitting and customer due diligence
Scale the investment against load and interconnection.
Stage the capital spend against the load ramp and the interconnection timeline, so on-site capacity carries the early phases and grid capacity is added when it actually arrives. Compare staged scenarios on one Pareto front.
- Investment staged against the way load and interconnection develop
- On-site capacity carries the phases the grid can't yet serve
- Scenario comparison with automated sensitivity analysis
On a 5 MW data center, indicative modeling points to a behind-the-meter system that cuts the contracted grid capacity needed, holds a PUE near 1.15, and earns waste-heat revenue in the order of a few hundred thousand dollars a year where a heat buyer exists. These are directional ranges from a reference model, not a guaranteed outcome for any specific site.
Sympheny does not replace your electrical or equipment design tools, and it is not a DCIM, switchgear or detailed-engineering platform. It sits upstream of them, deciding whether a system is the right one before any component is specified. Once the concept is fixed, your detailed-design, interconnection and delivery partners take it from there.
Sizing multi-energy systems against a hard constraint 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+ price and demand scenarios. The same low-grade-heat-into-a-network problem a data center poses when a heat buyer is next door.
Read case studyA district roadmap that tested whether on-site and wastewater heat could anchor an ambient network, reaching an 83% CO2 cut by 2040 across three fully costed pathways. The same on-site-resource modeling a data-center microgrid relies on.
Read case studyA city-wide supply strategy confirming a CO2-free supply by 2035 at similar life-cycle cost, on a capacity-weighted tariff. The same grid-capacity logic a data center faces at interconnection.
Read case studyFor whoever gets it powered and whoever builds it.
The developer needs an interconnection path and an economic case that holds. The engineering partner needs a concept they can defend in detailed design. Sympheny serves both from the same model, which is why it works as the upstream layer ahead of detailed engineering.
Data-center developers and operators
The behind-the-meter and microgrid case, the clean-power pathway and the grid-cost story that turn a stalled interconnection into a buildable, financeable site.
Engineering and A&E partners
The optimized upstream concept, generation, storage, cooling and grid connection, ready to hand to detailed design, with the rigor to defend it in front of the client.
Upstream of detailed design and delivery
Sympheny supplies the optimization engine and the concept it produces. Interconnection hardware, the formal utility request and on-the-ground microgrid delivery sit with your engineering and delivery partners. It is the upstream concept layer, never a substitute for the interconnection request to the utility.
Data-center power and microgrids, explained.
What is a data center microgrid feasibility study?
It is the upstream analysis that decides whether a data center can be powered with on-site generation, storage and a microgrid when the grid can't serve the full load on the timeline. It sizes behind-the-meter generation, storage and flexibility against the site's real load, compares them on cost, CO2 and resilience, and quantifies how much grid capacity is still needed. Sympheny runs that feasibility analysis and returns a Pareto front of options rather than a single answer.
Why is it so hard to get a data center powered in the US?
The constraint is rarely the technology. It is grid interconnection. Queues run for years in most markets and large new loads are increasingly told there is no capacity. Behind-the-meter generation, storage and a microgrid carry the load while a smaller, well-evidenced grid request moves through the queue. A credible on-site energy plan is becoming part of the license to build.
What is behind-the-meter generation for a data center?
Behind-the-meter generation is on-site power, PV, storage, gas, fuel cells, that serves the load directly without crossing the utility connection. For a data center it reduces the contracted grid capacity, hedges interconnection delay and can run as an islanded microgrid for resilience. Sympheny sizes the behind-the-meter system against the real, variable load so it is bankable rather than a rule of thumb.
How does Sympheny fit alongside electrical and DCIM tools?
It sits upstream of them. DCIM, electrical and equipment design tools answer how to build and run a system once it is chosen. Sympheny answers whether it is the right system in the first place: which mix of on-site generation, storage, cooling and grid connection hits the cost, CO2 and resilience targets. Once that concept is fixed, the detailed design tools take over. The two are complementary.
Can Sympheny model the variability of AI and HPC loads?
Yes. AI and high-performance computing workloads swing sharply, which drives both the cooling demand and the grid capacity charge. Sympheny optimizes generation, storage and load flexibility against that variability, so the system is sized for real operation rather than a flat average, and capacity charges stay contained.
Can a data center still recover and sell its waste heat in the US?
Where a district energy system or thermal energy network is nearby, yes. Servers reject heat at roughly 30 to 50 C; recovered with heat pumps it can feed a thermal network as a revenue line and a community benefit. It is a secondary angle in most US markets today, strongest on campuses and in thermal-energy-network districts. Sympheny quantifies the revenue alongside the cost and CO2 effects for a specific site before any commitment.
Power, heat and the network around the site.
Plan a data center you can actually power.
Bring us a site. We will model the on-site generation, the storage, the grid cost and the clean-power pathway together, and show you the system worth building before anyone specifies a component.
