Wednesday, 1st December 2021
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Flexible data centres can reduce grid carbon emissions

Lancium™, a technology company focused on the energy transition, has published a Company-sponsored report “Impact of Large, Flexible Data Center Operations on the Future of ERCOT.” The report assesses the energy and environmental impact of deploying 5,000MW of flexible data center capacity in the Electric Reliability Council of Texas (ERCOT) grid by 2030. ERCOT manages the flow of electric power to more than 26 million Texas customers, representing approximately 90 percent of the state’s electric load.

“As grids move towards incorporating higher levels of intermittent resources, such as wind and solar, flexible demand will play an ever more important role in keeping the electrical grid system stable,” said Joshua D. Rhodes, PhD, author of the paper.


The paper’s analysis concluded that:

•Adding data center load to electrical grids incentivizes more wind and solar power to be built than a base case of no flexible data centers.


•Operating flexible data centers that can rapidly vary their load can result in a net-reduction of carbon emissions.


•Higher levels of flexible demand response results in a lower probability of the grid reaching critical levels of reserves that would require firm load shed (i.e., blackouts).


•Siting such centers in power-congested locations with historically depressed prices can decrease congestion and the need to build new transmission capacity, reducing overall system costs.


•Net CO2 reduction could exceed four million tons per annum by 2030.


“The paper outlines the case that large-scale solutions are required to enable the continued growth of renewable energy,” said Lancium Chief Executive Officer, Michael McNamara. “Lancium Controllable Load Resources (CLRs) act like large power stations in reverse by absorbing abundant renewable energy, while simultaneously providing grid ancillary services. This paper shows that such an approach can reduce costs, enable the growth of renewable energy, provide low-cost power, and have an impact on climate change.”


The methodology used 2018 as a baseline year for the grid optimization analysis. Baseline year data included spatial load and renewable generation profiles, since the same meteorological conditions that drive renewable generation also impact load. All data used in this analysis are based on public ERCOT reports.


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