Not too smart grid
2011-08-04 20:47:05.27495+00 by
Dan Lyke
3 comments
MIT news: The too-smart-for-its-own-good grid.
What they found was that if consumer response to price fluctuation is large enough to significantly alter patterns of energy use — and if it’s not, there’s no point in installing smart meters — then price variations well within the normal range can cause dangerous oscillations in demand. “For the system to work, supply and demand must match almost perfectly at each instant of time,” Roozbehani says. “The generators have what are called ramp constraints: They cannot ramp up their production arbitrarily fast, and they cannot ramp it down arbitrarily fast. If these oscillations become very wild, they’ll have a hard time keeping track of the demand. And that’s bad for everyone.”
I'm finding similar things in traffic management and traffic forecasting.
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#Comment Re: made: 2011-08-05 10:29:50.191238+00 by:
meuon
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Real life: All Electric (plug in only) EV owners will let the car charge on it's timer, probably set to start about 11pm, no matter what. Just because.
and because they ALL set them to 11pm, unless a randomizer is added, the demand peak will eventually reach scale and be an issue.
#Comment Re: made: 2011-08-04 23:49:46.607318+00 by:
Dan Lyke
I think to see the problems that they're describing you'd have to have automated response to pricing. They're talking about latencies in turbines, which means it's the sort of thing that a "charge my car at $.07/kW/Hr but not at $.08/kW/Hr" situation might cause hysteresis with.
Of course the response to this is to account for that in your pricing model, but then you get the theoretical situation where people start to account for your pricing model...
#Comment Re: made: 2011-08-04 21:56:08.08317+00 by:
meuon
It seems this is just a theoretical model. It doesn't match observed behavior.
What we see with customers with lots of feedback (AMI/AMR and STS Prepaid)
customers is they radically change their behavior for the first month to three.. and then they go back to doing what they were. Usually with a 10% to 15% overall decrease, but not the 30 to 50% they did for a month or two.
As for the actual variations of the large scale grid demands... They don't look at residential smart meters for that data. They look at Transmission and Distribution as well as Generation level feeds.