Am uploading this 20 page PDF for safekeeping. It is also worth reading.
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DeCarolis, Joseph F, Sauleh Siddiqui, A LaRose, J Woollacott, Cara Marcy, Chris Namovicz, J Turnure, K Dyl, A Kahan, J Diefenderfer, N Vincent, B Cultice, and A Heisey (October 2024). A new generation of energy-economy modeling at the US Energy Information Administration — Working Paper 204. Washington DC, USA: US Energy Information Administration (EIA). Public domain status.
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2024-decarolis-etal-a-new-generation-of-energy-economy-modeling-at-the-us-energy-information-administration-working-paper-204.pdf (626.9 KB)
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Thanks for sharing. I quickly went through and perceived two main ideas:
- LP optimization is limiting (with quote of @stefan.pfenninger 2014 article), but I didn’t get what it is supposed to be replaced with: I didn’t see MILP mentioned, but HiGHS is cited as solver (MILP/MIQP) and Iptopt (local NLP), along with probable commercial solvers
- Modularity is important, which is being prototyped with Pyomo’s blocks which I have heard about (and seen several discussions on the Julia/JuMP discussion forum, since JuMP doesn’t have an equivaleent), but never practiced
I guess you are referring to this article from @stefan.pfenninger @hawkez99 and James Keirstead:
- Pfenninger, Stefan, Adam Hawkes, and James Keirstead (1 May 2014). “Energy systems modeling for twenty-first century energy challenges”. Renewable and Sustainable Energy Reviews. 33: 74–86. ISSN 1364-0321. doi:10.1016/j.rser.2014.02.003.
