To make and secure all the electrical energy systems essential to our world, artificial intelligence makes it possible to envisage major improvements.
The future of electricity and infrastructure is based on algorithms, not concrete or cables. Companies that master data -based decision -making will build the networks of tomorrow – whether through new projects or by optimizing saturated and aging systems. But responding to the growth of the world’s population and the thrust for decarbonation requires new approaches in infrastructure. Not only should aging systems be modernized, but public services must become resilients and agile to deal with economic uncertainties and extreme climatic events.
The recent power cuts in Spain and Portugal have highlighted the urgent need for more resilient infrastructure capable of managing unforeseen disturbances. Based on traditional models based on manual controls, partitioned approaches and static planning is no longer sufficient. This is where algorithms come in.
Why solving infrastructure problems is based on AI
Led by the industrial applications of artificial intelligence and supported by the Internet of Things and the Cloud, energy infrastructure becomes smarter and more ecological. If we focus only on infrastructure, all of these technologies play a multifacette role in modern energy management.
To adjust energy production, reduce waste and improve reliability, AI algorithms can predict energy demand with precision and optimize the integration of intermittent renewable energies such as wind and solar using IoT data in the cloud. Compared to traditional methods based on vast hypotheses and periodic schedules, these innovations make measurable improvements for public services whose resources are limited: real -time loops allow operators to optimize decisions and prevent problems before they arise. According to the International Energy Agency, integrating digital technologies today could generate $ 1.8 trillion in global investments that electrical networks will require over the next two decades.
How to go to the infrastructure managed by AI
Duke Energy, one of the largest public service companies in the United States, knows how to generate savings and improve performance using algorithms. Its one -shop surveillance and diagnostic center monitors a wide variety of assets ranging from renewable energies to coal and gas facilities in 60 seven American states power states. Using inexpensive sensors and AI algorithms, the company follows more than 500,000 data points and performs more than 11,000 automated models. Its operators now have real -time visibility on performance and are alerted before the occurrence of problems or as soon as they occur. They saved more than $ 250 million thanks to predictive interventions, which includes the early detection of a dysfunction which could have cost $ 34 million alone.
Elsewhere, the innovative management of networks attacks the proliferation of new devices such as electric vehicles, smart meters and solar panels. UK Power Networks, the largest electricity distribution company in the United Kingdom, provides electricity to 19 million households in one of the largest populated areas in the world. Aware of the limits of reactive maintenance, they have developed a data -based platform that processes 4 billion data points per day. The analysis fueled by the AI predicts the breakdowns before they occur, thus reducing the cuts and improving efficiency. Thanks to a centralized management center and rationalized operations, operators can focus on network resilience, burden balancing and strategic decisions related to infrastructure.
Why human intelligence remains the spine of public services improved by AI
If AI accelerates the modernization of networks, it cannot do it without human intervention. It is only by programming, monitoring and adjusting digital systems according to commercial and social objectives that experienced professionals can achieve higher results.
It is clear that the information generated by AI can guide long -term planning, and that algorithmic adjustments in real time can meet immediate challenges. However, none of these elements can replace human expertise. This is why the majority of energy producers (75 %) in the main global markets will prioritize AI investments in the next 12 months, according to a recent study.
Ensure the future of the energy sector through the collaboration of stakeholders
The rise of digital public services is a matter of time. With the growth of the EIA in energy, the annual rate of which is made up of 36 % until 2030, data -based technologies will play an essential role in the construction of secure and decarbon energy systems to support the future of humanity.
However, there are three conditions essential for the effectiveness of the digital transformation led by AI: clear regulatory executives, strategic partnerships between technology and investors suppliers, and an open dialogue with customers. Algorithms can consolidate the future of energy, but only by involving all stakeholders. The question is no longer whether the sector will adopt AI, but if it will do it quickly enough to remain competitive.
