The global hive brain holds the key to rethinking energy

As the UN warns of crunch time for climate change, the need for globally sustainable energy has reached tipping point.

International carbon emissions hit record highs last year, with current trends putting the world on course for a sweltering 3.1C rise by the end of the century.

More widely, climate-impacted adverse weather events, like the devastating floods in eastern and southern Spain, are occurring with increasing frequency. Globally, communities are grappling with storms, heatwaves, wildfires, and droughts. Events like these are jeopardizing power supply and displacing millions around the world.

Almost three quarters of global emissions (72%) stem from energy production of all types. The energy system must decarbonize. Digitalisation can help.

Technologies like AI, machine learning (ML) and data analytics running on the cloud have powerful capabilities to promote agile, resilient green energy production.

Predicting the future

By leveraging AI models trained on historical data, utility companies can more accurately predict demand, manage varying energy sources, and finetune their operations.

For instance, by analysing sensor information from wind turbines and solar panels, AI can precisely forecast energy generation patterns by the hour, day or season. This allows grid operators to minimise reliance on fossil fuels and maximise the integration of renewable energy sources.

An example of this in action is Ontario Power Generation, where thousands of sensors operate in unison to optimize the maintenance and production of renewable and nuclear energy sources, meeting 50 per cent of Ontario’s electricity needs.

Power companies are also deploying technology to optimise the efficiency of PV cells, wind turbines, and energy storage systems. By programming AI models to adjust settings based on real-time data, businesses are able to build-in resilience and schedule optimised maintenance repairs.

Another example can be seen in Xcel Energy. The Minneapolis-headquartered firm, which has been a wind power operator since 2005, uses an integrated data management platform to predict drops in wind speed hours in advance. Operators now know when winds are likely to die down, so they can fire up backup plants in a way that minimizes wear and tear on the equipment. This enables them to run the plants at their most efficient rates. Over six years, the company estimates it has saved roughly $46 million.

On the demand side too, AI-driven energy management systems are empowering consumers and businesses to take charge of their own energy usage. By analysing consumption patterns and providing personalised recommendations, these applications promote energy efficiency and reduce costs.

The role of open source

The potential of AI- and ML-infused energy networks can be accelerated by open-source collaboration. Open technologies create a common language for data exchange, ensuring compatibility across diverse systems. This allows data from various sources — such as sensors, smart meters, weather stations, and maintenance logs — to be integrated and analysed collectively.

In the past, the proprietary nature of energy systems stymied innovation, but modern open technologies facilitate the cross-sharing of data and ideas across companies, states, and even country borders.

This seamless data flow supports rapid experimentation and innovation, leading to faster progress in addressing critical challenges like renewables integration, grid optimisation, energy efficiency, and carbon reduction.

Open-source frameworks enable organisations of all types — large and small, academic and commercial—to collaborate on software solutions tailored to local, regional, or global needs. This kind of radical, joined-up intelligence is essential to reimagining how we produce, distribute, and consume energy.

The power of the global hive mind

Achieving ambitious climate targets calls for radical collaboration. A sustainable energy ecosystem can only be built on a bedrock of transparent, interoperable data that enables efficient decision-making and comprehensive carbon tracking.

Open technology standards unlock the alchemy of human ingenuity and computational power, laying the foundation for the energy sector to become more agile, resilient, and efficient.

Through urgent action and the use of collaborative technologies, governments, businesses and consumers alike can work together to safeguard our planet now and in the future.