Electrical, not political. A DOE study found that - duh - if you give
consumers information about time varying cost of electricity they will
save money by shifting some power usage from peak to off-peak times.
Consumers in the study lowered their electric bills by 10% and lowered
their peak demand by 15%. This is a big deal because although the
operating cost component of electricity (fuel) depends on the total
energy consumed, the capital cost component (generating plants) depends
on the peak power generation.
Solar power is particularly valuable to a utility because its peak
production occurs in the middle of the day when summer demand from air
conditioning is highest. But there's another peak around 5-6 when people
come home from work and turn on appliances, and by then solar power
production has fallen off. Thus adding photovoltaic power alone may not
drastically reduce peak requirements for fossil fuel power plants.
Wind power along the California coast has an almost complementary
generation curve to that of solar power, because of the onshore and
offshore breezes in the mornings and evenings. Adding wind power alone
may not drastically reduce peak fossil demand because the wind often
dies down mid-day when the air conditioning load is highest.
But adding solar and wind power together could greatly reduce peak
fossil demand, though perhaps not economically eliminate it entirely.
Then if you added time of day metering to allow consumers to voluntarily
shift their load, that would level even more peaks. Ditto various energy
storage systems like the plan to use night time wind power to pump water
back up a hydroelectric dam for use the next day, super capacitors, and
plug-in hybrid cars. The key to effective and economical use of
renewable energy is a balance of power supply with demand.
The computer industry tries to do the same thing with servers. Demand
for computing services typically follows daily, weekly, and monthly
cycles. When the data center is provisioned for the highest possible
demand, there is a lot of wasteful excess capacity. Even with the most
efficient hardware and the best power management software, running
servers at low utilization is extremely wasteful compared to moderate
utilization. So we try to balance computing supply with demand by
virtualization and workload consolidation, especially if we can find
workloads that are complementary (like wind and solar) in their resource
requirements and/or their load versus time of day.
As network capacities increase and software becomes more sophisticated, you can imagine systems configuring computing resources worldwide to
maximize computing power to the customer at minimum electric cost. Think
of a customer connected from California in the middle of a hot day with
time-of-day electric meters set to the highest price. Of course he might
be routed to servers in Europe or India where the computing demand is
off peak. He might also be routed to servers in Colorado where the
computing demand might still be high, but the electricity demand and
price might be lower. Or to Oregon where a heavy rainfall and cold wave
might mean cheap renewable hydro-power, even at peak electric demand;
and lower than usual data center cooling costs thanks to mixing filtered