What does AI do in a smart grid, and why is it becoming essential?

AI helps grid operators make better decisions by rapidly processing huge volumes of data from sensors, smart meters, weather forecasts and operational systems. In practical terms, it improves load forecasting, spots patterns humans and traditional models can miss, and supports real-time control so the grid can respond to sudden changes in demand or generation. It is becoming essential because the electricity system is changing quickly: renewables add variability, extreme weather is more common, and new large loads such as AI data centres can appear and shift at speed. AI enables operators to move from reacting after the fact to preparing in advance, improving reliability while unlocking efficiency savings.

How does AI improve load forecasting compared with traditional forecasting models?

Traditional forecasting generally relies on mathematical models tuned using historic demand curves and seasonal patterns. That works well on “normal” days, but it can struggle when something unfamiliar happens and there is no relevant historical reference, such as unusual weather or a sudden shift in how people use electricity. AI models learn from complex, multi-source data and can adapt as conditions change, making them stronger at recognising and predicting atypical behaviour. The goal is not to dismiss legacy models, but to reduce the growing gap between forecast and reality on the days when errors are most costly, helping operators run the system more efficiently and avoid serious disruptions.

Can AI help prevent blackouts and improve grid reliability?

Yes, but it does so by strengthening preparedness rather than acting as a magic switch. More accurate, faster forecasting supports better scheduling of generation, storage and flexibility, and helps operators anticipate stress on the network before it becomes critical. AI can also support dynamic grid management by analysing conditions in near real time and recommending actions that keep frequency and supply–demand balance stable. Importantly, utilities treat this carefully because the consequences of mistakes are severe. AI works best as part of a broader resilience toolkit alongside established forecasting, market signals and experienced operational oversight, so decisions remain robust even when the system behaves in unexpected ways.

What can we learn from Hydro-Québec’s use of AI for load forecasting?

Hydro-Québec provides a clear example of how AI is adopted safely and pragmatically. After a proof of concept using a neural network on a single substation, the utility invested in years of research before deploying deep neural networks into production. It now uses AI for short-term forecasting within a 36-hour window, hourly forecasts 10–12 days ahead using meteorologists’ forecasts, and even longer outlooks based on “historic normal” weather values. Crucially, it runs AI alongside legacy models to compare outputs and flag significant discrepancies for human review. During a heatwave, one legacy model needed major corrections while the AI model successfully anticipated an unusual demand pattern, illustrating where AI can add the most value.

How can AI data centres support grid flexibility rather than simply adding demand?

AI data centres can be a difficult load to predict, particularly during model training, which can consume substantial power. However, they can also become a flexible resource if their workloads are orchestrated in response to grid conditions. Trials such as National Grid’s work with Emerald.AI explore “smart mediation”, where software observes data centre workloads, identifies which tasks are non-critical, and adjusts computing activity to shape electricity demand. This can include ramping down by a defined number of megawatts, holding reductions for an agreed period, and ramping back up gradually to avoid “snapback” that can destabilise the grid. Done well, it creates a more symbiotic relationship between digital growth and system reliability.

Power Technology

Synera secures full offtake for Formosa 4 offshore wind project in Taiwan

The final allocations were secured through two new corporate power purchase agreements.

Synera Renewable Energy Group (SRE) has confirmed that all 495MW of clean energy from its Formosa 4 Offshore Wind Project in Taiwan has now been completely subscribed.

The final allocations were secured through two new corporate power purchase agreements (CPPA), completing the subscription of the project’s full capacity.

SRE chairperson Lucas Lin said: “We are delighted to see Formosa 4 reach such a significant milestone in its CPPAs.

“This achievement signals Taiwan’s urgent need for renewable energy, and we are proud to support local export-oriented industries with large-scale offshore wind power that strengthens their global competitiveness.”

These follow the CPPA signed in early December with Taiwan Smart Electricity & Energy. The latest agreements cover the remaining volume, with one signed by a “top-tier” company and the other by a power services provider.

With full offtake in place, Synera is urging government bodies and domestic financial institutions to coordinate credit backing and project finance.

The company highlighted these as essential to move into construction and help speed up renewable energy delivery in line with Taiwan’s sustainability ambitions and economic priorities.

Lin added: “We look forward to working under the government’s guidance to swiftly advance project financing.

“The government’s support to accelerate financing and credit guarantees is pivotal in enabling the project to commence construction and ensuring the timely delivery of green power essential for our corporate partners’ decarbonisation goals and Taiwan’s sustainable future.”

Formosa 4 is planned offshore from Miaoli County.

It won capacity in the first auction round of Phase 3 in 2022 and received its establishment permit in late 2024, making it the first project in its group to reach that point.

When operational, the wind farm is expected to produce around 2 billion kWh of green electricity each year.

In August this year, Cadeler entered an agreement with SRE to oversee the transport and installation of 35 Siemens Gamesa 14MW turbines for Taiwan’s Formosa 4 Offshore Wind Farm.