AI is one of the most transformative forces behind the future of load forecasting and management, greatly improving the dependability of power grids. Hydro-Québec, one of North America’s largest investor-owned utility providers, is leading the charge in this revolution. AI is already helping the organization’s operators to predict energy demands with greater precision, keeping the nation connected while preventing blackouts and making the grid more resilient.
Hydro-Québec mainly applies the technology for short-term forecasting, usually within a 36-hour period and delivering hourly forecasting, which incorporates meteorologists’ guidance. Besides short-term projections, the utility uses AI to develop longer-term outlooks based on historical weather patterns. Starting in 2028, Hydro-Québec will start using a bottom-up, regional approach to load forecasting. This strategy will include more than 350 substations and will continue to take advantage of highly advanced AI technology.
Another impressive aspect of the AI models implemented by Hydro-Québec is their complexity. These non-linear models are fitted using the Easy Nonlinear Least‐Squares Inequality Programme algorithm (ENLSIP). They involve dozens of highly complex functions and require constant tweaking of hundreds of parameters. This complex yet intelligent strategy is what equips the utility to better manage uncertain future energy consumption developments.
AI’s Role in Preventing Blackouts
The promise of AI to help stop blackouts can be huge. During such trying conditions as extreme weather events, especially heatwaves, AI has been successful at predicting atypical demand patterns. This new capability is essential to give operators the tools they need to dial back supply when needed and avoid blackouts.
“At a minimum, AI can help to run systems more efficiently. At a maximum, it will avoid catastrophic blackouts.” – Vijaykar
Hydro-Québec has a climate strategy that fights to mitigate climate change. When AI systems are implemented and embedded, these systems can offer wide-ranging, immediate signals for action—often on short notice from the utility. This nimbleness helps operators quickly react to changes in demand, keeping their systems stable and safe.
AI’s ability to deal with unusual cases makes it even more valuable. Similar to the problems with traditional forecasting methods against unexpected weather events or a sudden spike in demand. Digital twins AI allows operators to minimize gaps between predicted and real-world demand. This is particularly important on days when mistakes might lead to significant operational disaster.
Enhancing Forecasting Accuracy
Hydro-Québec’s use of AI for load forecasting is a project that truly redefines the game. More than four million smart meters provide a data rich environment. That data trains AI models, letting the utility sense broader patterns and sharpen forecasts. The flexibility of the technology to update with new data results in better overall accuracy.
“Having to deal with data from more than four million smart meters is another ball game.” – Hydro-Québec’s spokesperson
Like Hydro-Québec as it ramps up its own AI capacity, the objective here should be continuous improvement in operating these systems. From 2026 through 2027, the utility will work with Techstars to develop a prototype using renewable energy forecasting. Plus, they’ll work hand in hand with smart meter data from the start.
Hydro-Québec remains committed to improving its AI models. Yet they understand that load forecasting is both a challenge and an opportunity. AI’s enormous and unpredictable demand AI changes everything on the supply side. At the same time, it presents a unique opportunity to wield those tools and deliver more meaningful outcomes.
“Load forecasting has always been an important function. AI is both a challenge and an opportunity on both sides of that equation.” – Vijaykar
Future Directions and Challenges
Hydro-Québec is purposely deploying AI alongside its traditional grid planning and forecasting approaches. We hope this new approach will change what load forecasting looks like in the future! It’s just one of many execution strategies needed. Experts are quick to point out that even though AI provides unparalleled benefits, it isn’t a silver bullet. Rather, it should be seen as an addition to current processes and a powerful contributor to greater operational flexibility and therefore resilience.
“AI complements but does not replace grid planning and forecasting.” – Adkins
Challenges remain. This variability in renewable energy, which has become more prevalent with the growing adoption of renewables in the energy sector, makes sales forecasting even more challenging. Utilities should reorient their approaches to navigate this uncertainty.
“The increasing penetration of renewables introduces variability and uncertainty into grid operations.” – Adkins
Hydro-Québec is just starting down an ambitious path into AI-powered load forecasting. They are clearly poised to meet the challenges and leverage the possibilities that this technology provides. Like any AI-based utility system, the utility is still working hard on training its AI systems to make sure they live up to their full potential.
“When they get confident, Hydro-Québec will stop using the old model.” – Clermont