New research reveals that "foundation models" trained on vast, general time-series data may be able to forecast river flows accurately, even in regions with little or no local hydrological records.

Power systems are undergoing a rapid transition toward operation with high penetration of renewable energy and power electronic interfaced devices—often ...

Energy Forecasting, Electricity, Renewable Energy, Energy Planning, Demand Smoothing Share and Cite: Mishra, S. , Sharma, M. and Avittathur, B. (2026) Mid-Term Forecasting of Electricity Demand with ...

S&P Global today announced the completion of its acquisition of Enertel AI Corporation, a company specializing in AI and machine learning-driven short-term power price forecasting for North American ...

In the development of a new power system dominated by green energy, green electricity has become a standardized commodity circulating nationwide through market mechanisms. The role of green ...

U.S. fossil fuel generation could rise over the next two years as surging electricity consumption from data centers ​tightens ...

Utilities worldwide are turning to artificial intelligence (AI) and machine learning to stabilize networks, forecast ...

Kalshi says it's more than just betting and that it offers high-quality forecasts. Now, a research paper from a group of Federal Reserve economists is backing that up. The researchers found that ...

Industry Insight from Reuters Events, a part of Thomson Reuters. Growing power demand for oil and gas operations and technology manufacturing are creating openings for U.S. power plant developers ...

With AI-powered data centers rapidly driving up demand for electricity, predicting future needs is essential for planning the region and ensuring a reliable and affordable power supply. Accurate ...

(The Center Square) – With AI-powered data centers rapidly driving up demand for electricity, predicting future needs is essential for planning the region and ensuring a reliable and affordable power ...