  Cloud providers are adapting datacenter (DC) capacity to reduce carbon
emissions. With hyperscale datacenters exceeding 100 MW individually, and in
some grids exceeding 15% of power load, DC adaptation is large enough to harm
power grid dynamics, increasing carbon emissions, power prices, or reduce grid
reliability.
  To avoid harm, we explore coordination of DC capacity change varying scope in
space and time. In space, coordination scope spans a single datacenter, a group
of datacenters, and datacenters with the grid. In time, scope ranges from
online to day-ahead. We also consider what DC and grid information is used
(e.g. real-time and day-ahead average carbon, power price, and compute
backlog). For example, in our proposed PlanShare scheme, each datacenter uses
day-ahead information to create a capacity plan and shares it, allowing global
grid optimization (over all loads, over entire day).
  We evaluate DC carbon emissions reduction. Results show that local
coordination scope fails to reduce carbon emissions significantly (3.2%--5.4%
reduction). Expanding coordination scope to a set of datacenters improves
slightly (4.9%--7.3%). PlanShare, with grid-wide coordination and full-day
capacity planning, performs the best. PlanShare reduces DC emissions by
11.6%--12.6%, 1.56x--1.26x better than the best local, online approach's
results. PlanShare also achieves lower cost. We expect these advantages to
increase as renewable generation in power grids increases. Further, a known
full-day DC capacity plan provides a stable target for DC resource management.
