Distribution and Management of Datacenter Load Decoupling
Liuzixuan Lin, Andrew A. Chien

TL;DR
This paper explores how to effectively distribute and manage load decoupling in datacenters to maximize renewable energy absorption and reduce carbon emissions, considering economic and site-specific factors.
Contribution
It introduces methods for optimal distribution and management of datacenter load decoupling, demonstrating significant carbon reduction and economic benefits.
Findings
Optimized distribution achieves over 98% of potential carbon reduction.
DC-grid cooperation increases carbon reduction by 1.4 times.
Decoupling can be economically beneficial despite costs.
Abstract
The exploding power consumption of AI and cloud datacenters (DCs) intensifies the long-standing concerns about their carbon footprint, especially because DCs' need for constant power clashes with volatile renewable generation needed for grid decarbonization. DC flexibility (a.k.a. load adaptation) is a key to reducing DC carbon emissions by improving grid renewable absorption. DC flexibility can be created, without disturbing datacenter capacity by decoupling a datacenter's power capacity and grid load with a collection of energy resources. Because decoupling can be costly, we study how to best distribute and manage decoupling to maximize benefits for all. Key considerations include site variation and datacenter-grid cooperation. We first define and compute the power and energy needs of datacenter load decoupling, and then we evaluate designed distribution and management approaches.…
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Taxonomy
TopicsCloud Computing and Resource Management · Software-Defined Networks and 5G · Distributed and Parallel Computing Systems
