Plan district cooling and campus energy as one system.
Cooling, solar, storage and the grid connection belong in one model, because each decision changes the economics of the others. Sympheny optimises them together and shows every concept on the same cost and CO₂ chart, early enough to shape the master plan.
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India is starting to plan cooling the way Europe plans heat.
The reference projects exist and the policy direction is clear. What most developments still lack is the planning step in between: a rigorous, comparable analysis of which cooling and energy concept fits the site. That step is what this page is about.
District cooling is moving from concept to infrastructure
GIFT City operates India's first large district cooling system, Rajkot has piloted district cooling under its smart-city programme, and UNEP has supported district cooling roadmaps in states including Tamil Nadu and Maharashtra. The direction is set: cooling planned as shared infrastructure, not building by building.
Cooling decides the economics of Indian sites
On a campus, township or IT park in most of India, cooling is the dominant load and the dominant electricity cost. Whoever plans it well controls the energy economics of the whole development.
The window to decide is the master plan
District cooling needs density, routing and a central plant site. Those are master-plan decisions. Once the layout is fixed, the option quietly disappears, which is why the comparison has to happen at concept stage.
GIFT City, Rajkot and the UNEP roadmap work are referenced as market context. Sympheny was not involved in these projects.
What the model does with a cooling-led site
Sympheny treats a campus or township as a multi-energy hub system: demands, technology candidates, costs and constraints in one MILP optimisation, solved on the Gurobi engine. Deterministic, auditable, and re-runnable when assumptions move.
Cooling as a first-class carrier
Chillers, thermal energy storage and cooling networks sit in the same optimisation as solar, batteries and the grid connection. Sector coupling is captured, not approximated: the model sees that thermal storage lets chillers run when power is cheap.
Hourly resolution over a reference year
Cooling economics live in the peaks. The model dispatches every technology hour by hour across the year, so peak shaving, storage cycling and tariff exposure are calculated rather than assumed.
Network versus decentralised, answered directly
A central plant with distribution piping against building-level systems, on one Pareto chart. The optimiser searches 50,000+ technology and capacity combinations, including options a manual study would never construct.
Phasing modelled explicitly
Townships build out over years. Build stages are part of the model, so the phase-one plant is sized for the full vision without overbuilding for day one.
The numbers an investment committee will push on
A district cooling decision is a capital commitment with a thirty-year tail. The committee's questions are predictable: why this concept, what does each alternative cost over its life, what happens if demand or tariffs move, and why now rather than later.
Sympheny's outputs are built to survive that room. Every scenario carries its assumptions with it, and when someone asks for a variant, the model re-runs in the same workflow instead of triggering a new study.
Life-cycle cost and CO₂ for every scenario on one chart, traceable to assumptions your investment committee can interrogate
Capital phasing visible by build stage, so financing follows the actual infrastructure schedule
Sensitivity runs on tariffs, demand growth and technology costs, showing where the concept is robust and where it is exposed
Outputs that support IGBC and GRIHA energy criteria and the BRSR narrative, from the same model that made the engineering case
Proven on European districts and campuses. Delivered in India with ORMAE.
No Indian reference project yet, so judge the capability on its record. The model is carrier-agnostic: the same hub formulation that planned these heat-led systems handles cooling-led ones, and ORMAE in Bengaluru provides local delivery, model support and training.
A research campus modelled as twelve interconnected energy hubs in one project, with technology selection, sizing and hourly dispatch solved together. The closest analogue to an Indian institutional campus or IT park.
Read case studyA district of six connected energy hubs with 90,000 MWh annual throughput, evaluated across more than thirty price and demand scenarios before infrastructure commitment.
Read case studyA district thermal network for around one hundred buildings: expansion strategy, source mix and economics compared in one model. The same network logic applies to district cooling.
Read case studyFrequently asked questions
Can Sympheny model district cooling?
Yes. Cooling is a first-class energy carrier in Sympheny's multi-energy hub model, alongside electricity, heat, hydrogen and storage. Chillers, thermal energy storage, cooling networks and the electricity system that drives them are optimised together in one MILP run, at hourly resolution across a reference year.
How does Sympheny compare district cooling against decentralised cooling?
Both options are modelled on the same baseline: a central plant with a distribution network versus building-level systems, each with its capital cost, operating cost, space and CO₂ implications. The optimiser evaluates configurations of both kinds and the results sit on one Pareto chart, so the comparison is direct rather than assembled from separate studies.
Has Sympheny been used on Indian district cooling projects?
Not yet, and we won't claim otherwise. The platform is proven on 40+ European district and campus energy projects, including multi-hub campus models and district network expansion studies. The model is carrier-agnostic, so the same workflow applies to cooling-led Indian projects. Delivery, model support and training in India come from our optimisation partner ORMAE in Bengaluru.
What inputs does a campus or township cooling study need?
Building-level floor areas and usage types, load profiles where they exist (standard profiles can fill gaps), tariff structures, technology candidates and any site constraints such as space or grid sanction limits. A first model can usually stand within days once the inputs are assembled.
What outputs does the study produce?
Pareto comparisons of every scenario on life-cycle cost and CO₂, Sankey energy-flow diagrams, hourly demand and dispatch profiles, storage sizing, and investment breakdowns. Outputs are viewable in the browser and the underlying data exports to Excel.
Run your campus or township through the model.
Message Rohan on WhatsApp with the site context, or start a free trial and set the first model up with us. Either way you'll know within days whether the concept holds, not after a three-month study.
