S&P Global Buys Enertel AI for Power Price Forecasting

The deal adds AI-driven nodal price forecasting to S&P Global Energy’s existing long-term intelligence portfolio. Thus giving traders and utilities a single source for short- and long-range power market data.

S&P Global completed its acquisition of Enertel AI Corporation, extending its Energy division’s capabilities into real-time, AI-powered electricity price forecasting for North American wholesale markets. 

The Ontario-incorporated company, founded in 2021, delivers probabilistic, nodal-level price forecasts across all major Independent System Operators (ISOs) in North American wholesale power markets. Its models cover day-ahead and sub-hourly forecasts, applying Graph Neural Networks (GNNs) that integrate market prices, grid load, weather data, fuel costs, and other price-formation inputs to generate decision support for physical power traders, utilities, and asset operators. 

S&P Global Energy has built its position around long-term power market intelligence benchmarks, historical price data, and strategic forecasts distributed under the Platts and CERA brands. Enertel fills a gap at the shorter end of that timeline, adding next-day and intraday nodal pricing that the division did not previously offer at scale.

“The power markets are undergoing unprecedented transformation, and our customers need intelligence that moves at pace.” Dave Ernsberger, President of S&P Global Energy, said in the company’s press release. He described Enertel as “a natural and compelling addition” to the division and framed the deal as part of a deliberate push into higher-value segments of the energy data market. 

S&P Global disclosed that the acquisition is not expected to have a material impact on the company’s financial results or on S&P Global Energy’s division-level performance. No purchase price was disclosed in the press release. It is unclear whether financial terms will appear in a subsequent regulatory filing with the U.S. Securities and Exchange Commission. 

The move comes as North American power grids face accelerating complexity: higher renewable penetration, retiring baseload capacity, and demand growth driven partly by data center expansion. Nodal pricing, which sets electricity costs at individual grid connection points rather than averaged regional figures, has become a critical input for asset operators who need to optimise dispatch decisions in near real time. GNNs, which model relationships across interconnected grid nodes, have gained traction in this domain because they capture transmission constraints and congestion patterns that conventional forecasting models handle less precisely.

S&P Global Energy’s four operating units are Platts, which covers pricing and news; CERA, which handles research and advisory; Horizons, which addresses energy expansion and sustainability; and a managed events business. Enertel’s toolset is expected to be integrated into Platts’ pricing and intelligence infrastructure, though S&P Global did not specify a timeline for the integration in its announcement.

Disclaimer: This article is based on publicly available reporting, including S&P Global’s official press release.NervNow has not independently verified the claims, figures, timelines, or statements attributed to executives and public officials cited herein.

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