Running Australia’s electricity grid has always been complex. But managing a grid that’s transitioning from centralised fossil fuel generation to millions of distributed renewable sources is a different order of difficulty. AEMO has acknowledged that their traditional tools aren’t up to the task, and they’re investing heavily in AI and advanced analytics.

This might sound like inside baseball, but it directly affects every household’s electricity price, reliability, and the pace of the energy transition.

What AEMO actually does

AEMO (Australian Energy Market Operator) is responsible for operating the National Electricity Market across five states, managing the gas markets, and planning for the future grid. In real-time, they balance supply and demand across the NEM, dispatch generators, manage system security, and respond to emergencies.

This balancing act happens every five minutes. Every dispatch interval, AEMO’s systems calculate the optimal combination of generators and storage to meet demand at the lowest cost while maintaining system security. With hundreds of generators, thousands of MW of battery storage, and 20+ GW of rooftop solar, the optimisation problem is enormous.

Where AI fits in

Demand forecasting. Predicting electricity demand used to be relatively straightforward — weather, time of day, time of year. Now, demand is also affected by millions of rooftop solar systems (which reduce apparent demand during the day), batteries (which shift demand in time), and EVs (which add unpredictable new loads).

AEMO is using machine learning models that incorporate all these variables to produce more accurate demand forecasts. Better forecasts mean less reliance on expensive reserve generation and more efficient dispatch.

Renewable generation forecasting. Solar and wind output forecasting has improved dramatically through AI. AEMO’s Australian Solar Energy Forecasting System (ASEFS) uses satellite imagery, ground sensors, and machine learning to predict solar output across the NEM. Similar systems exist for wind.

These forecasts are critical for scheduling backup generation and managing grid security during rapid weather changes. A thunderstorm crossing Sydney that reduces rooftop solar output by 2GW in 30 minutes requires advance warning and preparation.

Power system security assessment. As the grid becomes more complex, traditional security assessment tools struggle to evaluate all possible failure scenarios. AI-assisted tools can rapidly assess thousands of contingency scenarios (what happens if this transmission line fails, or that generator trips) and identify potential security risks before they materialise.

Market design. AEMO is also using data science to inform market reform proposals. Analysis of historical market data helps identify market design flaws, gaming opportunities, and potential improvements. This doesn’t directly use AI in operations but benefits from the same analytical capabilities.

The specific projects

AEMO has been working with technology partners on several initiatives:

Project EDGE (Energy Demand and Generation Exchange): A project that tested how distributed energy resources (solar, batteries, EVs) can be coordinated to provide grid services. AI was central to the aggregation and dispatch algorithms. AI consultants in Adelaide and other technology firms contributed to the demand response algorithms used in pilot programs.

Enhanced ASEFS: The solar forecasting system has been upgraded with deep learning models that process satellite imagery in real-time, providing five-minute resolution forecasts up to six hours ahead.

Frequency control optimisation: As traditional synchronous generators (coal, gas) retire, the grid loses inertia — the physical rotational energy that helps maintain frequency at 50Hz. AI tools are being developed to optimise the dispatch of fast-frequency response batteries and inverter-based resources as replacements.

Why it matters for you

These might seem like abstract technical improvements, but they have concrete impacts:

Lower electricity prices. More efficient dispatch and better forecasting reduce the system’s total cost of operation. These savings should flow through to retail prices over time.

Fewer blackouts. Better security assessment and faster response to contingencies means a more reliable grid. AI-assisted grid management should reduce both the frequency and severity of supply disruptions.

Faster renewable integration. The better AEMO can manage renewable variability, the more renewable energy the grid can absorb. This means fewer curtailment events for rooftop solar owners and faster progress toward decarbonisation goals.

Smarter DER integration. Distributed Energy Resources (your solar, battery, and EV) will be increasingly integrated into grid management. This means more opportunities for VPP participation and demand response programs — more ways for your equipment to earn money while supporting the grid.

The challenges

AI in grid management isn’t without risks. Cybersecurity is a major concern — grid control systems are critical infrastructure, and AI systems introduce new attack surfaces. AEMO takes this seriously, but the threat landscape is evolving.

There’s also the question of explainability. When an AI system recommends a dispatch decision that affects millions of consumers and billions of dollars, operators need to understand why. “The neural network said so” isn’t acceptable for critical infrastructure. AEMO is investing in interpretable AI that provides reasoning alongside recommendations.

My take

The modernisation of grid management through AI is one of the most important — and least discussed — aspects of the energy transition. We talk endlessly about solar panels and batteries, but the invisible infrastructure that coordinates all these resources is equally important.

AEMO’s investment in AI capabilities is encouraging. The grid of 2030 will be vastly more complex than today’s, and managing it with 20th-century tools isn’t an option. AI won’t solve every grid challenge, but it’s becoming essential for managing the complexity of a distributed renewable energy system.

And that benefits everyone — whether you’ve got panels on your roof or not.