Here's a link to the ESIG report: www.esig.energy/wp-content/u...

It's remarkable how closely the projections match how much solar was being installed in the year the projections were made, basically assuming that additions would stay the same in perpetuity.

Credit where it's due: this is an updated of the classic solar vs. IEA chart from @aukehoekstra.bsky.social and @drsimevans.carbonbrief.org. It's striking to see how much WEO scenarios and actual additions have evolved in the years since the original comparison.

Who wore it better? @cmu.edu

Exactly. California and Hawaii have high rates but low consumption, so total household energy expenditures are lower than average.

This figure is from our Energy Wallet report: energywallet.epri.com/en/current.h...

From GIs' rations to supply chains, energy systems, and climate policy: the diet problem shows how OR turns messy reality into a solvable problems... and how reality pushes back. Happy 111th, George!

You can read more here: resources.mpi-inf.mpg.de/departments/...

Moral of the story: models are only as good as their data, definitions, and constraints. Also, good models don't replace judgment but organize it. Dantzig's wife studied the menus and said, "I'll put you on my diet." And he lost 22 pounds.

Then: two pounds of bran per day. Anne threatens to take him to the hospital, imposes a cap, and swaps in blackstrap molasses. New constraint, similar nutrients. Classic LP substitution.

Next day the model prescribes 200 bouillon cubes/day. Anne Dantzig drops a legendary pun: "What are you trying to do, corner the bullion market?" Doctor confirms: no upper bound on salt in the requirements. So Dantzig adds one. Behold, the origin story of upper bounds.

First menu from the IBM 701 includes... 500 gallons of vinegar. Because the source listed vinegar as "very weak acid" with water content = 0, the model treats it like dense fullness. "I decided vinegar wasn't a food."

While at RAND, Dantzig's doctor tells him to go on a diet. So he models his own diet as an LP to maximize "feeling full." Objective ≈ food weight minus water weight. What could go wrong?

Background: Dantzig invents the simplex algorithm for solving linear programming problems but needs a test case. In a Pentagon bull session, Marvin Hoffenberg suggests: "Try Jerry Cornfield's diet problem for GI rations" (i.e., finding a low-cost diet meeting nutritional needs).

bsky.app/profile/bist...

Ultimately, what matters is the emissions intensity of electricity generation. On that front, you're right that CA is currently lower than TX, but TX has made much faster progress (from a higher starting point) and is catching up to California.