iiinova — where your digital self keeps evolving

5/5 Funny observation -> let's calculate average utilisation of DE data center fleet: 17.9 * 1e6 / (1955 * 8760) = 1.045. Either one of these numbers is off, or someone’s Bitcoin farm got spotted. Honestly, not sure why. 🤔

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3/5 On power: the same report says there are 1,994 data centers in DE with >50 kW load. Over 309 of these are colocation data centers with 1,300 MW load. The total load is near 2 GW (or exactly 1,955 MW -- as can be dug out from another GDA report).

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2/5 On energy: with German C&I annual consumption is at 323 TWh (Eurostat energy balances), that is ~5.5%. If we take the commercial sector only with 117 TWh -> 15.3%.

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1/5 Good point, let's take a look. The German Datacenter Association's 2024 report says the total energy consumption of data centers in DE was 17.9×1e9 kWh → 17.9 TWh 🔗 www.germandatacenters.com/fileadmin/do...

germandatacenters.com

Georg Zachmann @gzachmann.bsky.social · 11/02/2025

Reposted by Iegor Riepin

Nice illustration how systemically biased energy scenarios could be in envisioning technology success.

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Taking average capacity factor for offwind at 0.36 and 0.11 for solar PV (rough values for DE), and ~1.8 GW of PPA capacity for each tech (from dena report), and German C&I demand at 323 TWh (Eurostat), and assuming all PPAs are signed by C&I (seemingly right, see p.6 dena) --> yields roughly 2.3%

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The German Energy Agency (dena) reports that the combined capacity procured via PPAs was at 3.6 GW in 2023 (with nearly all energy signed from solar PV and offshore wind). There is no numbers related to energy, but let's make back-of-the-envelope calculation 1/2 www.dena.de/en/infocente...

💰 With tight fiscal budgets & uncertain governmental support, 24/7 CFE offers a demand-driven path to scale new technologies. By creating a demand for long-duration storage & clean firm power, we can help these technologies get off the ground—without waiting for perfect policies 7/7

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When early adopters commit to 24/7 carbon-free energy, they create a self-reinforcing “virtuous circle”—driving innovation, attracting investment & making advanced energy tech widely available. A handful of companies & governments can set this in motion 🚀 6/7

3️⃣ As advanced technologies are deployed repeatedly, they become more competitive and are adopted widely in the bulk system, leading to emissions reductions far beyond the original voluntary commitments 5/7

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2️⃣ Hourly CFE matching becomes economical by deploying advanced tech—clean firm power & LDES—alongside wind, solar & batteries. This creates an early market, driving learning & cost reductions, lowering the cost of 24/7 CFE, and making it more accessible for others 4/7

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1️⃣ Companies aiming for 24/7 CFE directly reduce their emissions by matching a greater share of energy consumption with clean electricity on an hourly basis, which reduces the need for dispatchable fossil generation to firm variable renewable supply 3/7

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Matching electricity demand with carbon-free supply every hour isn’t just about reducing your own emissions—it’s a catalyst for the energy transition. Here’s how it works: 🧵⬇️ 2/7

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Markus Millinger @millinger.bsky.social · 23/01/2025

⏳⚡🌍 How do we scale advanced energy technologies before it’s too late? New Joule commentary by @nworbmot.bsky.social @devonswezey.bsky.social @jessejenkins.bsky.social & me shows how companies doing 24/7 carbon-free energy matching accelerate energy transition for everyone doi.org/10.1016/j.jo...

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Reposted by Iegor Riepin

🚨 New Article and Policy Brief in Nature Energy 🚨 📄We examine the value of biomass in the European energy system and its interplay with other technologies under stringent emissions scenarios. 🔗 Article: doi.org/10.1038/s415... 🔗 Policy Brief: doi.org/10.1038/s415... @natureenergy.bsky.social

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Reposted by Iegor Riepin

Fabian Neumann @fneum.bsky.social · 15/01/2025

A common criticism of energy system models is their reliance on single weather years, despite significant year-to-year variations. But how can we ensure robust infrastructure planning in this case? What happens during rare events like the once-a-decade Dunkelflaute? www.nature.com/articles/s41...

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Iegor Riepin @iriepin.bsky.social · 14/01/2025

Our work discusses in detail the former part (additional percent of flexible loads reduces costs by avg. 1.29 ± 0.07 EUR/MWh); and we have no good data about the latter part. AFAIK hyperscalers have often operation headroom, and tend to have increasing share of flexible worksloads (like AI training)

🙌 This work was done with @nworbmot.bsky.social and Victor M. Zavala. Huge thanks my colleagues @fneum.bsky.social , Fabian Hoffman and Elisabeth Zeyen for always being there when I needed them most. And of course, a nod to the whole brilliant #PyPSA community. 8/8

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GitHub - Irieo/space-time-optimization: Code for the paper "Spatio-temporal load shifting for truly clean computing"

📚 We’ve kept everything open-source — feel free to play with our open model! 🐙💻 🔗 The paper (in Advances in Applied Energy): www.sciencedirect.com/science/arti... 🔗 Explore the open model: github.com/Irieo/space-... 7/8

github.com

Code for the paper "Spatio-temporal load shifting for truly clean computing" - Irieo/space-time-optimization

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Signal 3️⃣: Follow the Sun — Earth’s rotation offers an opportunity for a clever solar power shuffle. 6/8

Illustration source: https://doi.org/10.1016/j.adapen.2024.100202

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Signal 2️⃣: Low wind correlations across locations beyond 300-400 km — when it’s calm in one place, it’s likely breezy elsewhere. 5/8

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Signal 1️⃣: quality of local renewables — think of squeezing the most out of the best wind and sun resources. 4/8

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The challenge? Moving from "clean enough" to 24/7 carbon-free electricity (CFE). Using energy system modeling, we show how one can coordinate clean energy procurement with spatio-temporal load flexibility, and what signals can help datacenters make smart space-time load shifting strategy. 3/8

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Our new paper, "Spatio-temporal load shifting for truly clean computing", shows how datacenters can play energy Tetris — shifting computing workloads across times and locations to match renewable energy availability. 2/8

Illustration by Nick Little: https://slicknick.net

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🌍✨ What if your computing jobs could chase the sun and the wind, reducing your carbon footprint as they go? 1/8

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