Reliance Jamnagar AI Data Centre
India's first gigawatt-class AI campus co-located with the Jamnagar RE and green-hydrogen giga-complex — 24/7 clean power by design.
Footage · AIM Network · YouTube
1 GW to 3 GW
Target capacity
Phased scale-up of campus load
approx. multi-GW
Co-located RE capacity
Solar and wind within same complex
approx. GWh-scale
Battery storage
For firming and peak shifting
Giga-complex scale
Green hydrogen link
Shared electrolyser and offtake infrastructure
approx. $10bn+
Investment envelope
Across broader Jamnagar RE-H2 complex
approx. thousands of acres
Land footprint
Shared with existing energy complex
2021
Reliance announces multi-billion-dollar green energy giga-complex at Jamnagar spanning solar, electrolyser and battery manufacturing.
2023
Group signals plans for a large-scale, energy-intensive computing campus co-located with the renewable complex.
2024
Initial approx. 1 GW capacity phase discussed; site, water and grid-connectivity studies begin within the complex footprint.
2025-2027
Phased ramp toward approx. 3 GW envisaged, synchronised with expanding solar, wind, battery and hydrogen capacity.
Beyond 2027
Full-scale campus targeted to run predominantly on firm renewable and storage-backed power, reducing grid dependency.
This campus shows how India's flagship renewable-hydrogen hub can extend into gigawatt-scale digital infrastructure, proving that firm, round-the-clock clean power for hyperscale loads is bankable when built on a renewable-plus-storage-plus-hydrogen backbone rather than fossil peaking capacity. For Indian developers, lenders and DISCOMs, it is an early template for co-locating large continuous loads with generation clusters, reshaping PPA design, transmission planning, land bundling and equipment procurement strategy across similar RE corridors in Gujarat, Rajasthan and Tamil Nadu.
Indian tenders for large continuous loads can borrow this co-location logic: bundle land, transmission and water clearances with renewable-storage-hydrogen capacity under a single state industrial policy window, as Gujarat has done. Central Electricity Authority transmission planning and Green Energy Open Access rules need explicit provisions for gigawatt-scale co-located loads, while DISCOM PPAs should evolve toward availability-based, storage-backed structures. Green finance and PLI incentives for batteries and electrolysers can be layered into project financing to de-risk lenders on firm-power delivery.
Engineering, procurement and finance lessons
01
Co-locate load with generation
Siting a large continuous load inside an existing RE-hydrogen complex sharply cuts transmission evacuation costs, land acquisition timelines and right-of-way risk versus building generation and load separately.
02
Firm power needs a hybrid stack
Round-the-clock clean supply for continuous loads is only achievable by combining solar, wind, battery storage and hydrogen-linked assets; single-technology RE alone cannot meet 24/7 reliability requirements.
03
Financing must shift to availability-based structures
Lenders should underwrite on capacity-availability and firm-power PPAs rather than pure energy-only offtake, reflecting the blended generation-storage-hydrogen cost stack behind such campuses.
04
Grid codes need time-block granularity
Large synchronised loads require scheduling and forecasting at finer time blocks; utilities and SLDCs must upgrade dispatch and settlement systems to handle steep, continuous ramp profiles.
05
Shared infrastructure lowers unit cost
Water, land, substations and logistics shared across generation and load reduce per-unit capex, a replicable model for future industrial-plus-digital clusters in India's RE zones.
Sources · Reuters · Economic Times · Bloomberg · Mint · Reliance Industries investor disclosures
- Structuring hybrid RE-storage-hydrogen power supply agreements for firm, round-the-clock load requirements.
- Advising on transmission evacuation planning, land bundling and regulatory clearances for co-located generation-load campuses.
- Structuring green finance and PPP frameworks that align lender risk appetite with availability-based offtake models.