Tom Brown Profile picture
Feb 23 7 tweets 3 min read
Ever wanted to run an energy system model with your own assumptions?

We've made a simplified version of our 45-node European sector-coupled model available to run online.

It includes renewables, CCS, nuclear, power, hydrogen, biomass, industry, etc.

model.energy/scenarios/
You can ask it questions like:

i) At what cost does nuclear take over (around 3-4000 EUR/kW)

ii) What happens if we restrict power or hydrogen grid (costs go up!)

iii) What happens if we relax restriction on carbon sequestration from 200 MtCO2/a (costs go down!)
See scenarios others have run here:

model.energy/scenarios/resu…

Submit your own scenarios here (takes several minutes):

model.energy/scenarios/subm…
To run in reasonable time with open source, there are some strong simplifications:

a) Model is greenfield, e.g. ignores existing generators.

b) Time resolution is sampled for full year at most 25-hourly.

c) Only 45 nodes for Europe (proper model requires 200 for good results).
More info on the original, full model PyPSA-Eur-Sec here (that doesn't include above simplifications):

github.com/PyPSA/pypsa-eu…

Any feedback/comments very welcome, but cannot fix things quickly ;-).
PS The online interface is still rough around the edges and the model needs more explanation everywhere (it was an after-hours hobby project).

But the code is open and anyone can contribute to further development:

github.com/PyPSA/pypsa-se…

#freethemodels
PPS There is more detail and context on the underlying model in this slide deck:

nworbmot.org/energy/brown-e…

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More from @nworbmot

Dec 9, 2021
a learning curve for silicon solar cells...from 1972

when cumulative capacity was just 600 kW (today it is more than a million times higher)

most capacity back then was in space industry

if I read this right, they fit a learning rate of 31% or 21% depending on point selection
Most solar learning curves start much later, so it's nice to back-fill to the beginning, see e.g. this example

The 1972 learning curve is from the paper "Historical development of solar cells" by M. Wolf.

It's a fun, brief read.

Here's a scan:

nworbmot.org/historical_dev…
Read 6 tweets
Jun 17, 2021
how to avoid (panic about) declining market value of wind and solar

OR

how I learned to stop worrying about market value & love shadow prices

a DUAL perspective on a primal problem

new paper by @ReichenbergLina and me:

doi.org/10.1016/j.enec…
summary:

traditional "primal" view says low-marginal-cost wind and solar push down market prices when they produce a lot, suppressing revenue

we present another "dual" point of view: it is subsidies that suppress revenue, not variability

both are correct, but framing matters!
since market value decline is flip side of pushing in VRE with quotas/subsidies, it is a result of policy choice

we can also fix the problem by changing policy: by drawing in VRE (and other low-C gens) with carbon pricing instead

this avoids market value decline even at 100%
Read 30 tweets
May 22, 2021
- Learning effects lead to path dependency

- Including learning in your model => many distinct local optima

=> Diverse choice of low-cost future energy systems

- Can't just look at one

Conclusions from Niclas Mattsson's pioneering work in 1990s:

research.chalmers.se/en/publication…

1/12
(above graphic is from @MichaelGrubb9's fabulous book "Planetary Economics", downloadable here: climatestrategies.org/publication/pl…)
So what did Niclas do?

He ran an energy model with built-in learning curves and showed that with exactly the same model (same equations, all same data inputs, costs, etc.) you can get radically different energy pathways with similar total costs:
Read 13 tweets
Mar 30, 2021
Great to see this paper on long-duration electricity storage:

- Storage energy cost & efficiency critical

- Needs <= 50 USD/kWh to be relevant next to VRE, batteries, "firm" gen

- Needs <= 1 USD/kWh (e.g. salt cavern for hydrogen storage) to make serious dents in "firm" gen
I'd also be interested in the question posed the other way round: what is the value of "firm" clean generation in the presence of VRE, batteries and long-term storage?

E.g. how much does system cost reduce by adding nuclear/CCS etc. to wind+solar+batteries+hydrogen.
Either way, the system costs of all these options is in a similar ball park, which throws up the question:

What do we actually want?

What can we build quickly, with wide public approval?
Read 5 tweets
Oct 22, 2020
C. Darwin: an "admirable speech"

In 1863, William Armstrong advocates:

- end of coal
- efficiency
- electrification
- renewables (he developed first hydro power)
- open data
- technological learning ("tendency of progress is to quicken progress")

vimeo.com/75975295
You can read more about him here:

en.wikipedia.org/wiki/William_A…

williamarmstrong.info

And in @henrietta999's biography "Magician of the North".

Don't know if there is a transcript of the speech floating around anywhere (if not, we should transcribe one!).

His speech inspired the first suggestion I know of for green hydrogen (renewables + electrolysis of water to make hydrogen):

Read 6 tweets
Oct 17, 2020
Last thread on history of renewables + hydrogen (promise):

TL;DR:

- Idea of using electrolysis of water & storing hydrogen is almost as old as electrolysis (1789)

- Already a lively debate in *1863* about combining variable renewables with electrolytic hydrogen to replace coal
The above quotation is from Jevons' (he of paradox fame) marvellous 1865 treatise "The Coal Question":

oll.libertyfund.org/titles/317#Jev…

(h/t @physicspod)

and refers to an exchange in The Times of London in 1863, started by this letter on page 10 of the 2nd Sep 1863 edition:
G.A. Keyworth of Hastings followed up a few days on 16th Sep 1863 later with an elaboration of his ideas:
Read 11 tweets

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