Ruaridh Macdonald

@FedParolin We welcome feedback on the work. The preprint is available here: arxiv.org/abs/2504.08503

Another great paper by @FedParolin, showing how to decompose large energy system models spatially and by sector, and the significant speed-up this gives large and high-resolution models. This work will allow more models to be scaled up on large computer clusters #EnergyTwitter #EnergySystems

This is ongoing work, supported by @mitenergy, and we are currently developing several linear approximations to improve runtimes even further. We'll apply these faster models to larger grid case studies.

Clearly, incorporating these non-linearities increases model runtimes so we've explored the runtime-accuracy trade-off of several approximate models. It's up to each user to decide the best balance for their work but we hope this paper will help inform these decisions.

Are current capacity expansion models missing crucial details for thermal storage? @taemin_heo and I are investigating how storage state-of-charge impacts charge/discharge capacities—and why non-linearities matter for #ZeroCarbon grid planning models: arxiv.org/pdf/2411.07805

Tagging the man himself: @FedParolin

The pre-print can be found here: arxiv.org/abs/2409.19079 We welcome feedback and thoughts

For anyone modelling long-duration storage in capacity expansion models, Federico Parolin - a visiting PhD student @mitenergy, has just published a new formulation which reduces runtimes by at least 30% in our tests and avoids common constraint violations

The Sustainable Engineering Initiative @nyutandon has multiple postdoc openings on the topic of decarbonizing chemical manufacturing, spanning computational and experimental topics. Miguel Modestino and I are looking to hire researchers across three projects -a thread:

@JohnSmillie42 Would you count thermionic generators as another type?

@jacob_mays It would be great to hear more

PNNL is setting up an Energy Storage Participation Algorithm Competition, currently in the pilot phase. Info sessions 1/30, 4-5pm ET and 2/9, 3-4pm ET. If this sounds like something you may be interested in, let me know and I'll forward details!

@SamHamels @HighsOpt @JuMPjl @gurobi On the Julia note - if you just want to model a system, not add new features, you can use the current run files without needing to know Julia. You only need to alter the CSV inputs. That's the big simplification that's come from making DOLPHYN a Julia package.

@rrmacd @HighsOpt @JuMPjl @gurobi Looking forward to the day where I can just have a conversation with an LLM to set up and run a simulation in this kind of model. I'd love to use something like DOLPHYN, but I lack the time and patience to delve into Julia.

DOLPHYN, our multi-sector capacity expansion model, is now a Julia package: github.com/macroenergy/Do… This lets you use it directly through Julia and we will continue to make it easier to use. DOLPHYN currently models H2 and electricity - using GenX as the electricity model

@duncancampbell Not a bad question at all. A lot of it is momentum once the project started in Julia, but we've also been very happy with the runtime and memory performance, and we preferred how JuMP.jl handled model <--> solver control compared to alternatives at the time

@rrmacd This is so cool! Dumb question from an uninitiated person: why Julia over other languages?

@SamHamels @HighsOpt @JuMPjl @gurobi This was something I was looking at this weekend with the new ChatGPT/create tools. As a first step we're going to try have it set up sequences of runs in response to questions, e.g. "How much does the round-trip efficiency of Li-ion matter here"

@whatisnuclear Thermionic conversion always seems a great option to me. There's a great pair of textbooks on the details and pairing with nuclear systems. archive.org/details/Thermi…

Ever wonder about ways to convert nuclear power to electricity without boiling water? The US Atomic Energy Commission put together a 39-pg booklet on this topic that's available for free, and it is awesome. Direct Conversion of Energy by W. Corliss, 1964 osti.gov/biblio/1130979

DOLPHYN optimizes energy system models using @HighsOpt by default. Thanks to @JuMPjl, DOLPHYN can also run with many other solvers. We do most of our testing with HiGHS and @gurobi

This is the product of hard work by the DOLPHYN team, led by @dhariksm, @Guannan_He and myself. We will soon new sector models for CO2 storage and transport, and biofuels. Please get in touch if you have questions or would like to add more sectors for your own work.

Hi, I'm recruiting a postdoc to work on multisector energy models at the MIT Energy Initiative Please share with anyone you think would be interested We're looking for folks with a background in optimization. Experience of energy system modelling is a plus careers.peopleclick.com/careerscp/clie…