Iain Staffell

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New data are coming out all the time so we want to make this a live, collaborative project. All the data are hosted on GitHub, so we can work together to improve and expand this resource: https://github.com/iain-staffell/GNESTE
GitHub - iain-staffell/GNESTE: The Global and National Energy Systems Techno-Economic (GNESTE) Database

The Global and National Energy Systems Techno-Economic (GNESTE) Database - iain-staffell/GNESTE

GitHub

The GNESTE Database covers seven technologies: #coal, #gas, #hydro, #nuclear, #solar #PV, #wind, and #battery #energystorage (together >92% of global generation).

And it covers the key financial metrics: #capex, #opex, #wacc, #lifetime, build time, fuel price, plus #efficiency.

The data going into models is critically important, but often overlooked because it can be hard to find. You want cost and performance assumptions that are granular (specific to the country you are studying) and robust (harmonised across several sources to minimise bias).

Calling all power systems modellers! Are you looking at #LCOE? Calculating technology competitiveness?

Let me introduce GNESTE – a new database with over 5,000 entries from 56 sources on the cost and performance of #electricity generators🧵

https://www.sciencedirect.com/science/article/pii/S235234092400636X

What do Australia, Texas, and Eastern Europe have in common? They offered highest profits for energy storage arbitrage in 2023!

This graph shows the arbitrage profits from 38 day-ahead markets around the world. All calculated using www.EnergyStorage.ninja

Learn more about what it tells us here: https://bsky.app/profile/iain-staffell.bsky.social/post/3ktjs7veolj2o

Iain Staffell (@iain-staffell.bsky.social)

What do Australia 🌏 Texas 🌎 and Eastern Europe 🌍 have in common?  They offered highest profits for energy storage arbitrage in 2023!   This graph shows the arbitrage profits from 38 day-ahead markets around the world. All calculated using www.EnergyStorage.ninja

Bluesky Social

Calling on #energy and #power folks for a favour!

I'm trying to better understand the cost and performance of conventional power plants ( #coal #gas and #nuclear )

Can you share and leads to recent data sources? ⚡🕵️‍♂️⚡

I'm interested in global and country specific data... current and futute projections... with and without #CarbonCapture... Gen III, IV, and SMRs... You name it, I am interested in it 🤓

And finally... I'm not saying don't eat meat and don't fly.
I do both...

But, I think it's useful to see how these activities compare, to understand the scale of their impacts, so that people can make better-informed decisions.

We find that reducing meat intake to recommended healthy levels (92 cal per day) could almost halve production-phase GHG emissions. This can be rephrased as: “reducing your meat intake to three times per week is equivalent to avoiding six short-haul return flights each year”.

People resonate with more modest dietary changes... It's easier to imagine yourself cutting down than turning vegan overnight...

And people resonate with tangible examples of carbon emissions (flights, miles driven, heating your home).

So the paper's tagline is ...

In this research, led by one of our amazing Imperial College Environmental Technology Masters students, we surveyed people about how dietary change and carbon impact could be communicated more simply and effectively.