In this Story
At E-world, our experts will walk you through concrete platform improvements, live demos, and early previews, showing how recent developments support real-world energy operations.
Exploring What’s Next in MetX
Beta: Be Among the First to Try the AI Assistant in MetX
The new AI chat and text assistant is designed to make the platform faster and easier to use from the start. Instead of searching through menus or documentation, users can now configure dashboards, explore data, and request weather information using natural language.
Whether you're new to MetX or working under time pressure, the assistant simplifies interaction and helps you get to what you need, a lot faster.
Sneak Peek: The Future of Energy Forecast Visualizations in MetX
At E-world, we’re offering an exclusive first look at the next generation of UI and UX for energy forecasting in MetX. This prototype showcases upcoming improvements to forecast visualizations and model comparison views.
Every element has been redesigned to support clear insight across changing scenarios. This is your chance to explore and influence the direction of a more intuitive, more responsive interface before it goes live.
Key features:
- Multi-model forecast comparison (up to 6 models simultaneously)
- Support for wind and solar forecasts
- Advanced threshold management (up to 5 custom thresholds)
- Synchronized model run selection
- Hourly granularity filtering for EURO1k
- Geographic location switching
- Hindcasts and forecasts
- Weekend and temporal context markers
If your workflow depends on understanding changes at a glance and comparing forecasts with confidence, this preview is for you.
Operational Forecasting, Upgraded
AI-Enhanced Portfolio Solar and Wind Power Forecasts
Achieve measurable annual cost savings, from tens of thousands to several million euros.
Our solar and wind power forecasts combine physics-based weather models with machine learning trained on real power output data. This hybrid approach improves accuracy by around 13% for solar and up to 50% for wind, with gains that translate into measurable operational and financial impact.
The AI layer adjusts forecasts for real-world effects that are difficult to capture with weather models alone, such as shading from terrain or vegetation, snow cover, installation differences, self-consumption, turbine wake effects, ageing, and manual operational interventions. By learning how assets actually behave in operation, forecasts align more closely with delivered power.
Sub-Minute Forecast Access and 33% Faster API Performance
Capture market signals first and act before your competitors.
We’ve significantly sped up how quickly model data reaches your systems. Model outputs now arrive via our API in under one minute, and average query response times are 33% faster across the board.
Energy workflows are highly time-sensitive, and getting updated forecasts sooner gives teams more lead time on forecast changes, enabling quicker adjustments and tighter operational control.
Because we deliver full, high-resolution data consistently (not just a reduced subset, like most providers) the performance gains apply to all locations, parameters, and resolutions you rely on. Dashboards refresh faster, large datasets load more smoothly, and scripts or models that depend on weather inputs iterate more quickly, all of which supports more responsive operational decisions.
Enhanced Radiation Skills in EURO1k
Consistent and reliable forecasts for intraday planning, dispatch and trading workflows.
We’ve extended the radiation capabilities of the EURO1k model to further strengthen how it captures real-world conditions such as cloud cover, aerosols, and terrain effects that impact solar power forecast accuracy.
For energy operations, this means fewer sudden changes during the day, more consistent results across sites, and radiation data that remains reliable as weather conditions change.
More Country-Level Aggregates
Reduce data fragmentation and streamline cross-market analysis.
We’re expanding our set of country-level aggregates to support consistent analysis and benchmarking across energy markets. This makes it easier to compare forecasts and outcomes across regions without building and maintaining custom aggregation logic for each country.
For teams operating internationally, this reduces data fragmentation and streamlines cross-market analysis, helping ensure results are comparable and workflows stay aligned.
