Saving major utilities $0.5M to $2.5M per power station, annually
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Every megawatt-hour traded, dispatched or curtailed runs through a weather forecast. When that forecast is wrong, the losses are immediate.
Every generation technology — gas, wind, hydro, solar, geothermal — is exposed to weather. Yet most energy companies still rely on coarse, off-the-shelf forecasts that treat entire regions as a single point. As balancing requirements grow, these errors compound into imbalance penalties, missed bids, and curtailment waste.
Sources: Ember European Electricity Review 2025 · NESO Annual Balancing Costs Report 2024/25
hylosense deploys dedicated forecast models across your entire asset portfolio — gas, wind, hydro, solar, geothermal — each calibrated to the site's unique microclimate. The result isn't better weather data. It's drastically less imbalance penalties, tighter trading positions, and measurable savings within 30 days.
Every asset location modelled individually — trained on local terrain, elevation, and atmospheric patterns to capture what generic forecasts miss across your entire fleet.
Up to 64% improvement in forecast accuracy, validated against on-site observations. Our clients see €0.5M–€2.5M in annual savings per power station from reduced imbalance exposure alone.
No infrastructure, hardware changes or workflow disruption. hylosense integrates into your existing forecasting, trading, and SCADA systems — and delivers calibrated results within the first month.
Gas, wind, solar, hydro, and geothermal all rely on weather to forecast output, schedule operations, and avoid costly mismatches between expected and actual generation.
Electricity prices, intraday positions, and imbalance exposure are driven by short-term weather variability, making forecast uncertainty a direct financial risk for trading desks.
Grid capacity, congestion, losses, and operational safety depend on ambient weather conditions, especially as networks operate closer to their physical and regulatory limits.
Charging and dispatch strategies for storage assets depend on weather-driven supply and demand dynamics, where timing errors directly impact revenue and system stability.
Whether you're managing risk, optimizing dispatch, or running the grid — hylosense plugs directly into your workflow.
How energy companies across Europe are using hylosense to turn forecast accuracy into measurable savings.
Energy Output Forecast
hylosense is running an active pilot with Fortum to improve hyper-local weather accuracy across generation assets in the Nordics — targeting measurable improvements in operational efficiency and generation forecast accuracy. The project grew out of Fortum's Spark Innovation Challenge, where hylosense was awarded best startup and best pitch.
Energy Output Forecast
Across gas power plant locations in the UK and Germany, hylosense delivered up to 64% improvement in temperature forecast accuracy — directly reducing imbalance exposure and improving trading positions. Models were live and calibrated within 30 days of deployment.
Site Risk Assessment
Evaluating the right locations to build new solar power plants is a task with long-term consequences. By employing the power of climate projection data under different GHG emission scenarios, terrain elevation as well as land cover data, we're able to assess future threats to multiple locations with high accuracy.
Data delivered via encrypted REST API
Integrates with existing operational infrastructure
Hourly and sub-hourly forecast updates, 24–48h horizon
Confidentiality protected from day one
We work with generation, trading, and grid operations teams at major utilities worldwide. Book a session to see how hylosense integrates with your existing systems and workflows.
Schedule a Technical Briefing