Spire Expands AI-Driven Wind and Solar Forecasting to ERCOT
Spire Global has extended its AI-enhanced wind and solar generation forecasting tools to the Electric Reliability Council of Texas (ERCOT), adding one of the nation’s fastest-growing power markets to its coverage.
The company’s Power Generation Forecast uses a high-resolution model and AI-driven analytics to produce hourly predictions of wind and solar output. The forecasts draw on proprietary satellite observations and data assimilation techniques, including hub-height wind conditions and surface solar radiation, to help utilities, grid operators, traders, and developers better anticipate changes in renewable generation. The expansion aims to support planning, bidding strategies, and reliability during tight grid conditions.
“Recent NERC assessments show rising, around-the-clock electricity demand from data centers alongside winter conditions that can strain generation resources,” said Shawn Mechelke, General Manager of Spire Weather & Climate. “Spire’s Power Generation Forecast uses AI and satellite-enhanced data to translate atmospheric dynamics into hour-by-hour, MW-level outlooks that customers can act on immediately. As new technologies, including AI, increase demand across the grid, we provide utilities, traders, and energy providers the clear, reliable power insight they need to operate with confidence.”
Spire’s forecasting tools are already used in several European markets, including France, Germany, the Netherlands, Austria, Hungary, and the United Kingdom. Adding ERCOT extends that coverage into a major North American region with significant renewable generation. The system supports multi-model comparisons by integrating Spire’s High-Resolution, Global Forecast, and AI models with external sources such as IFS, giving analysts a consolidated view for assessing variability and uncertainty.
“MW-level predictions show exactly how much electricity wind and solar resources are expected to generate each hour,” said Elliott Wobler, Senior Machine Learning Engineer at Spire. “By combining proprietary satellite observations with machine learning and multi-model inputs, we translate atmospheric uncertainty into clear power generation outlooks that traders and operators can use in real time – delivering a streamlined view of expected renewable production and enabling decisive action.”
Spire provides a suite of weather and climate tools used across industries including energy, logistics, utilities, and agriculture.
