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For most of the history of power trading the grid was a black box. You knew your own assets and positions, and everything beyond them was a guess or a report that arrived too late. That is no longer true. The data is public now, but it is spread across 70+ sources, from ENTSO-E to every national TSO, each in its own format, and every desk rebuilds the same integrations to reach it. The Grid API puts production, load, price, flows and frequency for 200+ zones into one data model and one API. The Grid Map shows what that looks like. Signals come next, built in the open.

Modity trades and manages risk for renewable producers across the Nordics. As prices grew more volatile, sharper trading and optimisation decisions became essential, and a portfolio that carried more risk needed more sophisticated forecasting input and output. With rebase.energy, Modity built a decision-support system its traders use daily. Icing is one input: a forecast tied to the trading decision, showing the risk to wind output early. "We built a stronger decision support system, more data-driven, user-friendly, and robust," says Kruno Kuljis, Head of Analysis at Modity.

A few weeks ago, we launched TimeDB ⚡ Our open-source time series database built on PostgreSQL and TimescaleDB (check it out here: https://lnkd.in/drrpdf3c) One of our main motivations for building TimeDB was to have a super-fast and snappy database for dealing with overlapping and auditable time series data. Naturally, we turned to PostgreSQL as the go-to database for dealing with relational data. After some iterations and talks with time series database experts, we realised that some of the guarantees (mainly around transactions) that PostgreSQL provides are also making it slower than necessary. By adopting a dedicated time series database, we can achieve speedups of +10X, without really losing out on relevant functionality for our use case. The road led us to ClickHouse, and after some benchmarking using the TimeDB schema, we see some really clear and promising speedup. We’re already migrating our platform to TimeDB, powering how we deliver forecasts and historical data to our customers by the second. If you want to contribute to TimeDB, feel free to jump in 🚀 #timeseries #databases #energydata #opensource #letsrebaseenergy ⚡

There is always a lot happening in the intraday market ⚡📈 Let’s take a look at one day in February. When the market opens at 15:00 (D-1), prices initially follow the day-ahead clearing. But liquidity is still thin, and not all delivery windows have active bids. As the evening progresses, bids start appearing for almost all contracts. Around 03:00, liquidity for the morning hours begins to build 🌅. At some point bids appear well below the spot price, but as delivery approaches most contracts get back up again. The most interesting moment comes around 12:00. Afternoon contracts begin to move unpredictably up and down ↕️. The market suddenly becomes short, and many players enter to buy power and balance themselves. Production expectations and market conditions can quickly change. Having multiple signals and a reliable, fast data infrastructure to capture them is becoming increasingly important. This is something we are actively working on: lean data schemas, combining different forecast models and horizons, and making it easier to analyse how the market evolves ⚙️. All the data behind this video is stored in our TimeDB, preserving not only the values but also the time-of-knowledge ⏱️. This makes it possible to analyse things "as they were seen" at any given moment. This is essential for proper backtesting, forecast evaluation, and strategy development. #energymarkets #intradaytrading #energydata #timeseries #forecasting #letsrebaseenergy ⚡

Tomorrow is a historic day for European power markets with the go-live of 15min (SDAC) ⚡ ⚖️ Why is this a big deal? The function of a market (in general) is to bring buyers and sellers together as well as provide price signals for the traded goods (price discovery). Electricity is a very special "good". It is generated and consumed almost instantly and cannot easily be stored on a large scale. Until today, the market design has been to represent the power prices as hourly blocks, which is, of course, an approximation of the "true" price. Tomorrow is the first day after the transition to 15min day-ahead prices. This means that we can, for the first time, observe the true underlying price volatility within the hour. For SE3, it turns out that the largest difference between the hourly mean and the 15min prices is 101 €/MWh. That is more than twice the average electricity price in SE3 in 2025. In other words, it's a big deal 💶 I can't resist thinking: "What is the 5-minute volatility within the 15-minute blocks?" Is 15min going to be "good enough" to provide adequate price signals or are we eventually going to see 5min electricity prices? What do you think? #energymarkets #marketvolatility #15min #SDAC

No forecast is perfect. But as we get closer to the event, forecasts generally improve in accuracy. 📈 An example of a wind speed forecast update in UK is shown in the picture below. What is interesting is that even small wind speed changes can cause large shifts in power - and profits. In reality, traders have to handle vast areas and several assets. So only looking at one coordinate point is not ideal when operating in the intraday market and managing assets spread across different countries. One of the best solutions is to visualise the weather forecast differences directly on your map 🌦️, together with all the assets you’re managing. We call it “Weather Delta” ⚡, and it will be available to all Beta users of our Dashboard in the next few days. If you’d like access to the Rebase Dashboard, comment “Beta” or send me a PM.