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High-Density Computing Systems for Modular, Scalable, Demand-Responsive Baseload and Smart Grid Applications
With the modernisation of electrical grid systems as well as the increasing diversification of energy sources, there is a need for an overall control system to unify these different systems. Smart grid has been touted as the solution although problems such as grid stability remains.
This technology offer helps to address the grid stability problem by offering modular, scalable, demand-responsive high-density computational baseloads as a service. Ideal potential users are those involved with baseload energy generation, stranded power (flare gas, biomethane, etc.) or transmission-constrained renewable energy (e.g., surplus solar PV generation). The technology owner is seeking partnerships with energy producers and carbon offset project developers for both compliance and voluntary markets in the renewable energy space. This technology is production-ready for baseload applications (demand response functionality at a prototype stage) and the owner is looking for partners interested in collaborating on pilot projects.
Technology Features, Specifications and Advantages
This technology provides modular computational baseload systems that are fully automated and demand responsive, with a fifteen-second ramp-down response and a twenty-minute ramp-up response from standby to full-load. They are available in modular configurations ranging from 0.3MW to 3.3MW and are fully compliant with UL and NEC standards. Unlike conventional data centres that are designed to provide continuous service, this technology is optimised for interruptible batch computations like simulations, deep learning, financial modelling, blockchain mining etc., that may be completed on a best effort basis and thus curtailed and restarted as required by the demands of the energy grid. This technology can generate over US$400/MWh (continuous) for energy generators who can use demand response functionality to choose between selling energy to the computational baseload or selling energy to the grid as required.
The primary application of the technology is to help baseload generators better cope with grid instability introduced by intermittent renewable energy (IRE) like solar PV. The technology is also applicable to stranded power applications (flare gas, biomethane from capped effluent ponds etc.). The total market size for this technology is estimated to be 7TW if stranded power, surplus generation and constrained generation are considered.
This technology helps energy producers recover lost revenue, reduce curtailment and thermal cycling. As a result, renewable generation can be easily scaled as its impact on the grid is reduced. New renewable energy projects can also benefit from immediate off-take in the form of computational baseload while local demand grows to reach their capacity — thus improving the return on investments for renewable energy projects. For stranded power applications, flare gas used for generation reduces carbon emissions and such projects may be able to generate additional revenue through carbon credit creation. Exact financial performances and operational efficiencies obtainable will depend on the particulars of the implementation.