Is there a reliable way to identify regions with negatively-correlated winds?

Question

When examining the potential for large-scale electricity grids, and when identifying the lowest-cost ways to generate clean electricity, a recurring theme is of spreading wind generation across a wide-enough area that it evens out. One way to bring down costs a lot, is to combine on the same grid, regions where the wind over a period of weeks to years, are negatively correlated: that is to say, it helps if we can easily identify pairs of regions where low winds in one region tend to happen at the same time as high winds in the other. At a scale of days, sufficiently distant regions are uncorrelated. At a scale of weeks to years, a set of correlations of reanalysis data (e.g. ECMWF or CFSR) suggests that there are pairs of regions which do exhibit negatively correlated wind, either seasonally or annually. Is there a reliable way to identify such combinations of regions?

Answer 1

Sure, you could identify such pairs of complementary regions, just from your datasets. "Reliably" - that's the "kicker" -- you would have to consider the range of customary variability of the combined generating power, the variability given unexpected large weather events (fronts, hurricanes, etc.), and due to transmission line possible failures (breakages, shorts). Then, you would have to design your grid connections to minimize the cost of energy transport.

The backdrop for that is the time to activate very-short-term massive energy storage (so far, not designed into the grid!), short-term startup (hydro startup few minutes, gas startup moderate minutes, coal startup 1 day, nuclear startup days).

Also, to consider, load cutting vs. power dumping: utilities can cut load with "smart" = remotely-controlled appliances, but I don't know how excess power is avoided.

-- Cheers, -- Mr. d.