Monday, April 26, 2010

Averaging US East Coast Wind

There is an interesting paper in the most recent issue of PNAS by Kempton et al, Electric Power from Offshore Wind by Synoptic-Scale Interconnection. The paper is in a tradition of literature looking at how to solve the problem that renewables are intermittent by averaging over production in a wide geographical area - on the theory that the wind must be blowing (or the sun shining) somewhere. In this particular paper, the region studied is the US east coast. This map shows the study sites S1 - S11:

As you can see, the sites run pretty much the full length of the US East Coast from Florida to Maine. They then look at the power that could be generated by averaging all these sites together. This next graph will give you a flavor. Capacity factor is the fraction of the maximum power output of the turbine(s) that is currently being produced, and the graph is showing you that value for two week periods at the start of November and May respectively, in the 11 study sites, with the composite numbers at the bottom:

As you can see, the individual sites are extremely noisy, and the composite signal (the Pgrid at the bottom) is smoother and doesn't fluctuate as extremely. Thus the paper claims:
In the study region, using our meteorologically designed scale and orientation, we find that transmission affects output by reducing variance, slowing the rate of change, and, during the study period, eliminating hours of zero production. The result is that electric power from wind would become easier to manage, higher in market value, and capable of becoming a higher fraction of electric generation (thus more CO2 displacement).
From my non-specialist perspective, the overall result still doesn't look that great, however. If I zero in on the Pgrid, and rearrange the figure a bit:
You can see that there are stormy days in November when the entire hypothetical array of wind farms is producing at pretty much full capacity, and the capacity factor of the whole system is over 0.9. Then there are calm days in May when there's not a whole lot of wind and the capacity factor is down near 0.1. A 10x variation in power output doesn't seem like something to boast about too loudly.

The problem is that the US east coast is not really big enough to be above synoptic scale: the size of the big cyclones and anti-cyclones that govern weather in temperate latitudes. Another figure in the paper illustrates the kind of thing that can go wrong. Here the colors are wind speed (in m/s) and the lines show pressure isobars:

As you can see, with a big enough high off the coast there can be hardly any wind up or down the whole region.

There are several important points of context to make however. The first good news is that clearly east coast solar would tend to counter swings in east coast wind to a significant degree. Windless days of high pressure in the summer are exactly when you'd expect solar plants to be at close to maximum output - whereas the wind can pick up the slack in the winter (solar panels will not be doing a lot of good on those stormy days in November).

The other thing is, even within the US context, the east coast is not really where the wind is. This map from the National Renewable Energy Laboratory shows the distribution:


A very important point: the power in the wind is proportional to the cube of the wind speed, so those purplish regions in the high plains have about 10 times the potential per unit area of the yellowish-green regions on the coasts. That's where the wind is. And clearly, by feeding wind into the grid across the US, the performance is going to be smoother again, since a single high cannot cover the whole country.

It seems like with renewables, when feeding small amounts into a mainly fossil fuel grid, that's workable as they basically displace fuel use when they are available, but don't displace much capacity so the fossil fuel plants are still there to smooth the renewables out. An all-renewables grid would also be possible, but requires averaging over huge areas (and/or enormous amounts of storage). In between those extremes, things are going to be awkward.

6 comments:

Gary said...

The variability of surface winds is one of the main reasons that high altitude wind power (HAWP)looks more attractive (as well as the higher wind speeds). Looking at the east coast, one of the best locations for HAWP is near metropolitan New York. Here is my post on this subject a bit ago:
http://squashpractice.wordpress.com/2010/02/28/high-altitude-wind-power-a-review/

This paper by Archer and Caldeira considers the intermittency problem for the New York area utilizing large battery storage for low wind periods.

http://www.mdpi.com/1996-1073/2/2/307/pdf

fboness said...

The wind averages have to be clipped because below a minimum wind speed no power is generated and above a maximum wind speed no power is generated (because the turbines must be shutdown or be destroyed.)

An available power graph from this wind data would show numbers of dropout days when no power is produced.

Not so?

Stuart Staniford said...

Gary:

High altitude wind seems like an intriguing possibility, but it doesn't seem likely it would be much less intermittent. If you are in the troposphere, you'll be subject to the same synoptic scale weather systems creating large variance as at the surface. In the stratosphere, you'll be going after the jet stream, and those are very narrow, very fast, and vary a lot in position.

Gary said...

From Archer and Calderia for power from high altitude winds at 8km...

"With no storage or transmission in New York, an astonishing 2 kW/m2 are provided most (68%) of
the time, but less than 0.1 kW/m2 are provided 99.9% of the time. Adding
battery storage always increases supply of reliable power. For small battery sizes (< 100 kWh/m2), we
found improvements in both reliability and amount of wind power generated as the transmission
distance increases."

The accompanying graphs show that ~0.7 to 1.5 kW/m2 (depending on transmission distance) are available 99.9% of the time with the 100kWh/m2 battery.

So indeed its something to be dealt with, but not a show stopper.

Going Green said...

The other main issue is that wind peaks in either Winter or Spring. A Winter peak is good, but the Spring winds don't help much if at all. Peak load currently is Summer weekday afternoons when the air is still. Solar matches that fairly well but not exactly. Wind isn't even close.

Solar/wind combined helps with the duty cycle, but you still have huge balancing issues--and you are right, the synoptic scale is the proper scale for diversification.

That East Coast thing is too small for diversification and too large to be contained in one ISO--it looks like it crosses 6.

Nick G said...

there are stormy days in November when the entire hypothetical array of wind farms is producing at pretty much full capacity, and the capacity factor of the whole system is over 0.9. Then there are calm days in May when there's not a whole lot of wind and the capacity factor is down near 0.1. A 10x variation in power output doesn't seem like something to boast about too loudly.

Don't forget, it took 6 months to go from 10% to 90%. Rate of change is a crucial variable here, and the combined wind power shows much, much lower rates of change.

Also, don't forget that all power sources have variability: nuclear has to shut down almost 10% of the time for refueling and maintenance, and when it does it goes to zero output for weeks. Also, nuclear can "trip" with no notice, removing a GW of power at once with no notice, not to return for days. I'm not just picking on nuclear, either: coal has exactly the same issues of maintenance downtime and unscheduled downtime.

Grid managers don't need perfectly static sources, they just need them to be manageable. This paper helps make it clear that wind can be just that.

A key point: you don't need to have a 100% renewable grid in order to have a nation-wide grid. IOW, you can use high output in Maine to balance low output in Michigan, even if windpower is only 15%-30% of overall KWH market share.

Don't forget Demand Side Management (aka demand response); after geographical diversity, it's by far the most important tool for managing wind variation - much more so than central utility storage.

The lower wind's market share, the easier it will be to manage. OTOH, I'd estimate that it could be up to 60% of the grid.