Enhanced weather forecast for your energy network
Your heat demand forecasts need better weather data
Errors in temperature forecasts greatly impact heat demand predictions causing uncertainty. How much heat energy should be produced? How much electricity is available to sell? You cannot be certain without reliable weather forecast.
Getting temperature forecast right ensures your heat demand prediction is as accurate as it can be.
Improving your weather forecast with local observations
The best way to improve local weather forecasts is to measure the local environment.
Our Cast sensors use the same Vaisala measurement technologies trusted by meteorological agencies worldwide. Now you can get all the benefits of operating a custom sensor network without the hassle and responsibility.
We design, deploy and maintain your customer sensor network and provide you with enhanced forecasts through our API.
How it works
Deploying your custom sensor network
First step is to examine your district heating network with its unique characteristics and needs with our meteorologists and data scientists. That gives us essential data to start designing your hyperlocal weather sensor network.
Monitoring and maintaining
Our network operations center ensures the sensors run smoothly 24/7 and act when needed so you can trust your weather data.
Enhanced forecasts through an API
Access enhanced weather forecasts through our well documented APIs and build your operations around the best heat demand predictions.
36% improved accuracy with Xcast technology
Forecasts enhanced with local observations and advanced machine learning demonstrate significant improvements in forecasting accuracy:
- 36% more accurate forecasts (RMSE) than the best alternative
- 59% less large errors (<2.5°C) in 24h temperature forecast
Top-ranked weather models
Wx Beacon uses globally top-ranked forecasting models
Fast update intervals
Forecasts are updated every 15 minutes so that you can make decisions with the latest information.
Generated to your locations
Weather forecasts are modeled to your point of interest for maximum accuracy
"Our observation network of Vaisala weather stations provides us with accurate local data of critical weather parameters, enabling us to optimize heating supply temperature more precisely than before."
59%
less large errors (2.5+°C) in Fortum's 24-hour forecast
Viki Kaasinen
Head of Asset Digitalization
Fortum
