AI represents a huge opportunity for grid operators facing a rapidly changing load landscape, but there is little room for error. Moving away from trusted legacy ...

Traditional load-forecasting methods rely heavily on extensive historical data to predict future values, thus limiting their applicability in long-term forecasts where historical data may be ...

Electric load forecasting’s accuracy and reliability are pivotal for enhancing the dispatch efficiency of power systems and the integration of renewable energy into the grid. In response to this need, ...

The Federal Energy Regulatory Commission (FERC) on Sept. 18 advanced four reliability measures for the U.S. bulk power system (BPS), formalizing frameworks around supply chain risk, cloud computing ...

Electricity is produced by a variety of generating units, each with different lead times and costs to be readied for service, and production costs once brought online. Because electricity is a ...

The Energy Systems Integration Group (ESIG) has released a report examining how utilities and planners forecast long-term electricity demand and distributed energy resources (DERs) in an era of rapid ...

(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 ...

Traditional long-term forecasting models are no longer sufficient as electrification, DER growth, EV adoption, extreme weather events and new large loads introduce unprecedented complexity. The future ...

While there's little doubt electricity demand in Texas will continue to grow these next few years — especially with new data centers being constructed in hubs like Dallas-Fort Worth — determining just ...