Coupling Models for Cloud Datacenters and Power Grids

Liuzixuan (Peter) Lin; Andrew A Chien. 4 November, 2020.
Communicated by Andrew Chien.


We study the impact of rise of renewable growth and cloud computing power consumption, and in particular how the load of cloud computing can be coupled to the grid for the benefit of both. We consider three models static cloud loads, selfish local-optimization by each datacenter (DC) to minimize power cost (DP-ONL), and load orchestrated by the power grid using economic dispatch (GC).Our results show that dynamic coupling can improve grid dis-patch cost, renewable absorption, and datacenter power prices.However, the market power exercised by datacenters as large loads can both benefit and damage the price experience of both datacenter and other customers, so care should be taken to ensure equitable coupling methods.

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