🇩🇪 Visualizing Germany's Renewable Coverage Over the Past 10 Years As winter approaches, we will see LinkedIn posts switching from "Duck Curve" 🦆 (periods where high solar production rapidly ramps down) to "Dunkelflaute" 🌑 (those dark, windless periods that challenge renewable grids). I wanted to visualize both, not just the Duck Curve but also the Dunkelflaute. Using ENTSO-E data from 2015 to 2025, 15min granularity, I ended up with some interesting heatmaps. Each chart shows the percentage of electricity demand covered by renewables in Germany only ((Solar + Wind) / Demand). Colors range from red (low coverage) to green (high coverage). Here's what stands out: 🔷 Impressive difference across time. In 2015 we could not see green zones (>80% coverage) whereas in 2025 they're quite frequent during solar peak hours from March to October. ☀️ Also, windy times are managing to cover some periods (check end of 2023, where a wind period made the end of the year mostly covered by renewables) ❄️. 🔷 Summer Ducks 🦆 becoming more and more frequent: Deep midday "bellies" from solar dominance, creating surplus energy. A good opportunity for battery storage. 🔷 Dunkelflaute 🌑 has remained a consistent winter challenge, even as renewable capacity has grown. Some examples: the Dunkelflaute at the beginning of 2023 with extended dark periods. Or January 2017, where fog and lack of wind pushed conventional plants to cover most of the demand. 💡 Why It Matters: These visuals tackle a core question: when can Germany rely on variable renewable energy alone, and when does it need support? PS: what motivated me to do this analysis was to see a lot of experts talking about how solar and wind complement each other on a daily or seasonal granularity. But in electricity the real challenge isn’t daily or seasonal totals, it’s matching supply and demand in much finer granularity. Since solar/wind peaks don’t always align with consumption peaks, without more storage, demand response, and flexibility, daily/seasonal balances don’t translate into reliability in practice. Do you see additional patterns hiding in the data? I'm curious to hear. #RenewableEnergy #DuckCurve #DataVisualization #Germany #Dunkelflaute #BESS
When can a country rely on unreliable (non-dispatchable) power is a question that answers itself: other dispatchable backup is essential. A reliable grid is an economic cornerstone of a developed county's economy. Who would want to be in an airplane with unreliable engines halfway across an ocean ?
Taísa Felix can you show curtialment / negative pricing also? Or is that still too little to resolve on this scale?
Complementing this info: installed capacity triple to quintuple redundancy, soaring costs, plus a broken to be bidding zone that no one wants to connect to, and imports from France... Redundancy https://www.linkedin.com/posts/victorsdmp_greendeal-fitfor55-energytransition-activity-7206716906605527040-xYQ8?utm_source=share&utm_medium=member_ios&rcm=ACoAAAA4r2wB-P8-OvTok2mtIR_mwNqFXcoxVE0 Broken to be https://www.linkedin.com/posts/victorsdmp_splitting-germany-delu-in-electric-activity-7324030155486617600--0Wa?utm_source=share&utm_medium=member_ios&rcm=ACoAAAA4r2wB-P8-OvTok2mtIR_mwNqFXcoxVE0 Nobody wants to connect https://www.linkedin.com/posts/victorsdmp_regeringen-avsl%C3%A5r-ans%C3%B6kan-om-tillst%C3%A5nd-f%C3%B6r-activity-7207427724427018240-HNbU?utm_source=share&utm_medium=member_ios&rcm=ACoAAAA4r2wB-P8-OvTok2mtIR_mwNqFXcoxVE0 Soaring costs https://www.linkedin.com/posts/victorsdmp_energiewende-activity-7171655213848772609-GtwW?utm_source=share&utm_medium=member_ios&rcm=ACoAAAA4r2wB-P8-OvTok2mtIR_mwNqFXcoxVE0 Imports https://www.linkedin.com/posts/adam-russell-77b0171bb_electricity-nuclear-hydro-activity-7215988021752459265-sWxi?utm_source=share&utm_medium=member_ios&rcm=ACoAAAA4r2wB-P8-OvTok2mtIR_mwNqFXcoxVE0
Great visualisation, those solar “bellies” are interesting and they are getting more pronounced, but the winter voids really highlight where resilience breaks down. Feels like storage, demand flexibility, and maybe even industrial loads need to be considered closely when we think about resilience. Curious what's your take on the most overlooked lever for closing that winter gap?
Taísa Felix Taísa Felix Fantastic viz. To move from “coverage” to climate impact, we’d need: • Hourly carbon intensity (incl. imports/exports), • Curtailed MWh and storage state-of-charge (round-trip losses), • Ramping/restarts of conventional plants. These reveal when variability shifts emissions rather than cuts them. Do you have a gCO₂/kWh-weighted version (ENTSO-E + neighbors)? It would be especially insightful for winter Dunkelflaute. https://app.electricitymaps.com/map/zone/DE/12mo/monthly
Very interesting, Taísa Felix. Yes, I can imagine doing interesting things with your data. - First is to plot (100%- ED(RE)) where ED(RE) is the percentage of demand supplied by variable renewables. -- I'd also play with a 2-d line plot (offset-stacked on an annual basis) for absolute consumed RE energy vs your demand % satisfied with REs. -- From this, one can construct a 2-d "inverse" plot of both axes, I.e., unmet demand vs absolute MWh shortfall. From this, "model" what a range of natural-gas backup generation capacities could do: --- Start with how many GWh of installed nat. gas capacity could cover 100% of annual unmed demand and figure the capacity factor. -- Now, try lower amounts of installed nat gas assuming increasing on-demand electricity to import. -- It would be interesting to estimate, in each case, the cost of nat gas generation installation (with cost of capital which depends inversely on capacity factor), and historical nat gas cost. Since there is no extant universal long-term grid-scale storage (ULGS) tech, natural gas is to be the de-facto ULGS for over-installed variable renewables in Germany - & apparently soon the UK, if I understand the latters' new policies, but thankfully with some nuclear added
Thanks for the analysis and charts, Taísa! What I see from my humble point of view is a grid getting greener, despite challenges (like nuclear phase out and the mery fact that Germany was once one of the most coal dependent EU country). Step by step, we will all make it. ♻️🌍
how can we visualize the amount of French nuclear power bought by the (anti-nuclear) Germans ? 😬
Phenomenal graph from ENTSO-E data, thanks! Is the data public? Couldn't find it on the quick. I'm wondering how ENTSO-E can have such "coverage" data though, as it's well-known that Germany lacks a good end-user data capturing system... Could the green fields in your graph partly be exports to neighbors? Or did you really have acces to more than just generation, and you actually do see mid-granular coverage (i.e. matching) data? Was it obtained using substation data as good enough proxy for end-user consumption? I'm asking because MTU history available to the public is 60 minutes prior to 2021. Of course operators and ENTSO-E would have more granular data... Also, if you had an idea how to visualize the AC dichotomy between resistive, inductive, capacitive loads... I'd be a taker! Thanks Taísa Felix!
MSR Coordination Team
3wReally interesting data, Taísa Felix 👍 Now I think you should compare those graphical analysis with another version, including all low-carbon energy sources (i.e. including nuclear and hydropower), and with a color indicating directly the carbon impact of electricity generation (green when close to 0 gCO2/kWh, dark braun when higher than 400 gCO2/kWh, and black if higher than that). So we can see if the Energiewende (including nuclear phase-out) had any impact on carbon emissions...