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Writer's pictureNoaa Cohn

Enabling local procurement with new generation from the built environment

As the urgency of the climate crisis demands faster and more tangible action, more companies are taking a climate leadership position by making a commitment to sustainability, as exemplified by the 24/7 Carbon-Free Energy Compact. That commitment is to match each hour of every day of demand with locally-produced carbon free energy. 


This is, for large and energy intensive organisations such as data centres (DCs), a journey which starts with commitment, but quickly meets the complex demands of reality. 


Energy flow between distributed buildings

Data centres comprise 3% of the world's electricity demand, and is expected to grow up to 40% YoY. DCs look to match their constant, usually flat, energy demand with sources of local, renewable energy such as wind and solar. As an on-site solar installation would, at best, only meet 10-20% of their total energy demand from on-site generation, DCs require additional procurement avenues to meet the remaining 80-90%. 


The supply and demand gap 


The growing energy demands of DCs quickly outpace the market’s supply of local renewable energy. New builds of solar farms, for instance, have years long lead times for grid connectivity, and significant space requirements which results in locations outside of the regional grid of the point of demand. 


The built environment - in particular commercial and industrial (C&I) buildings like warehouses - presents a significant opportunity in enabling new generation. The UK C&I warehousing sector alone offers 350 million square meters of rooftop, expected to grow by 60% over the next decade. When fully utilised with rooftop solar power, a warehouse’s on-site demand usually requires only one-third of its generation capacity, leaving the remaining two-thirds available for sale. With the expected growth of this sector, warehouses could fulfill as much as 60% of DCs’ energy demands.


Closing the gap


DCs need to meet their climate commitments while mitigating their exposure to the volatility of energy markets, and optimising their operational expenses. They require access to predictable, economical renewable energy at data centre scale. And, that energy needs to be available quickly enough to meet their commitment timelines. 


Excess generation from warehouses must be aggregated across these distributed assets, treating them as a unified generation facility with a predictable volume and shape, delivered at a fixed long-term tariff. This allows DCs to manage their balancing risks, and make a significant dent in their 24/7 matched energy goal. 


Aerial view of warehouse with solar pv

On the warehouse side, the financials need to stack up, with a fast path to commercially operational that meets DCs’ procurement timelines. Landlords will need to up-size their installation, as opposed to right-sizing it to meet the needs of the on-site tenant alone. 


For that to be financially feasible, landlords need to secure a fixed, long-term export tariff for their excess energy. For it to be operationally feasible, the traditionally manual and slow processes of planning and design, grid application, permitting, payment reconciliation, and more need to be automated and streamlined. 


Realising the opportunity


Delivering these generation facilities requires a highly dynamic and optimised supply and demand matching mechanism. 


This mechanism must leverage advanced forecasting for generation and demand over time for each warehouse, accounting for location-aware information like grid capacity and weather. It must also be dynamic in the face of real-time shifts in operational performance and grid congestion. This requires an AI-driven data platform with fine-grained data flowing from and into operational sites, enriched with local grid and environmental data, for optimised real-time matching.

 

Gap closure requires a comprehensive approach which automates the significant operational efficiency hurdles: the complex and costly nature of feasibility studies, the intricate financial modeling required, lengthy grid application processes, and the complications of legal considerations. 


A paradigm shift


Realising the opportunity demands a paradigm shift in the energy ecosystem: toward AI-powered forecasting, aggregation, and matching, and toward fully utilised and operationally efficient generation sites. This paradigm shift is vital for new generation from the built environment to meet the growing demand for local renewable energy.


InRange is creating a new energy asset class from the built environment, unlocking new revenue streams for landlords and saving energy costs for tenants. The InRange platform provides guaranteed 10-year fixed export tariffs, with AI-powered matching of surplus energy to data centre and other in-network building demand through the InRange Marketplace. 



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