Forecasting software Sunairio has launched the new Omniscale Next-generation Ensemble (ONE) offering to provide critical weather and energy insights.
“Sunairio ONE is trained on the Sunairio High-resolution Earth Dataset (the SHED), our proprietary, high-resolution historical weather data archive that’s purpose-built to replicate granular risks for the modern grid,” said Rob Cirincione, CEO of Sunairio.
Sunairio started with the industry’s benchmark historical weather data, leveraged machine learning to sharpen resolution, then trained ONE on that data while incorporating changing climate fundamentals. Sunairio ONE generates 1,000-member hourly ensembles compared to traditional methods that stop at 50. The result is expanded forecast fidelity for load, renewables and grid stress across all time scales.
“Alternative forecast methods rarely issue more than 50 forecast scenarios, preventing users from seeing the make-or-break events,” Cirincione explained. “Imagine if I told you there was a one-in-50 chance of winning the lottery, except you don’t win the lottery, you black out the power grid or bankrupt your company. That’s the risk we’re taking with these limited forecasts.”
Sunairio ONE forecasts support actionable intelligence for reliable planning across power markets and utility operations. It is designed to support a range of use cases, including:
- Probabilistic energy trading and hedging strategy: Ensembles predict future energy price ranges and show potential for risk versus reward.
- Asset-level renewables forecasting: Sunairio ONE provides probabilistic forecasting for individual renewable energy assets (including availability and curtailment losses) for independent power providers, utilities, and public market participants.
- Climate-aware portfolio risk management: Accurately calculates the risk to energy investments resulting from weather-driven impacts across load, wind, and solar.
“Some of the greatest risks to power grids are hiding in plain sight. They don’t always look like hurricanes, which makes them more insidious. Increasingly, they look more like unusual combinations of weather that increase demand while reducing renewables output: heat that lingers past twilight or polar vortex cold snaps that arrive with calm winds,” said Raiden Hasegewa, PhD, Director of Data Science, Sunairio. “By combining weather and energy in a sophisticated forecast model, we’re giving companies insight they can’t get anywhere else.”
News item from Sunairio
