Dave Jones, the insights director at energy thinktank Ember, said the findings marked a potential turning point. “It’s the beginning of the end of the fossil fuel era,” he said. “Finally, the world seems like it is past peak fossil power, a crucial milestone in the energy transition. [This report] shows that 2023 will mark the end of fossil power growth. As of this year we are likely to be in a new era of declining fossil power.” But he added: “Peaking is not enough – we need deep and rapid CO2 cuts to keep within our vanishingly small carbon budget. We are doing the right things, we just need to do them even faster.” Fatih Birol, the IEA’s executive director, hailed the developments as a positive sign for the fight against climate breakdown, though he said far more effort was needed. “The power sector produces more carbon dioxide emissions than any other in the world economy, so it’s encouraging to see that the rapid growth of renewables and a steady expansion of nuclear power are on course to match all the increase in global electricity demand over the next three years,” he said. “This is largely thanks to the huge momentum behind renewables, with ever cheaper solar leading the way, and support from the important comeback of nuclear power. While more progress is needed, and fast, these are very promising trends.”

The IEA’s annual analysis of market developments and policies, Electricity 2024, published on Wednesday, showed that global electricity demand increased by 2.2% in 2023, and was likely to reach about 3.4% from 2024 to 2026. Most of the increase was expected to come from rapidly emerging economies:chiefly China, India and south-east Asia. However, the IEA also warned that the growth of power capacity was still uneven around the world. For instance, while electricity supply has increased overall in Africa, on a per capita basis power use across the continent has remained stagnant for more than three decades.This is a brake on economic and social development, as people in poverty turn to polluting sources of energy such as biomass and paraffin......read on   https://www.theguardian.com/environment/2024/jan/24/nuclear-power-output-expected-to-break-global-records-in-2025   

What Are SMRs and Why Do They Matter? SMRs are small nuclear reactors that can make electricity or heat. They are much smaller than traditional nuclear plants. Most SMRs will make between 10 and 300 megawatts (MW) of power. That’s enough to power a town or a factory. Big reactors take over 10 years to build and cost billions of dollars. SMRs are different- they are.......Build in factories......Easier to transport........Faster and cheaper to install. The IEA says SMRs are designed to be safer and more flexible, offering a low-carbon power option. They can be used in remote areas, near factories, or with solar and wind power. These features make SMRs useful for the energy transition. Most SMRs under development could cost less than $2 billion compared to more than $10 billion for traditional nuclear plants. They also use advanced safety features and can be installed in areas where large plants wouldn’t fit .              

Where Are SMRs Being Built?    Interest in SMRs is growing quickly. In the United States alone, over 20 gigawatts (GW) of SMR capacity has been proposed, especially by tech companies looking to power their growing fleets of AI data centers. Some utilities, like Dominion Energy, plan to add 1.3 GW of SMR capacity by 2039 to meet rising electricity demand. China is also exploring SMRs, expecting them to play a role between 2030 and 2035. In fact, the IEA estimates that low-emissions electricity (including SMRs) will supply 60% of power for Chinese data centers by 2035. In the U.S., this share could reach 55% by the same year. Although many SMRs are still in the planning phase, they could begin commercial deployment after 2030, especially as clean energy policies become stronger and electricity needs increase.

So, here are the many ways AI aids in boosting SMR applications.

AI Supports SMR Design and Operation-....Designing a nuclear reactor is very complex. Engineers must decide how big each part should be, how to keep the core cool, how to manage radiation, and how to make it safe. This usually takes years of modeling and testing. But AI is changing that.The IEA explains how generative AI and machine learning can run fast simulations of reactor designs. This allows scientists to test thousands of options in less time. AI is especially useful in adjusting the geometry of the reactor to improve how heat is managed and to avoid unsafe temperature levels.                                                                                                       AI is also used in materials testing..... Inside a reactor, the materials need to handle very high temperatures and radiation for long periods. AI tools can now predict how metals and other materials will behave, reducing the need for long lab tests. This helps engineers choose stronger, more reliable materials faster.Smart Fuel Management and Monitoring. Fuel is one of the most important parts of a nuclear reactor. Engineers must load it carefully and plan when to replace it. AI can help make these decisions better. According to the IEA, predictive AI can improve fuel loading and switching, making the process more efficient and reducing waste. The IEA also notes that AI-powered predictive maintenance can find system issues before they become serious, which lowers costs and keeps reactors running longer.     AI Helps Explain Safety Risks. AI is not just used inside the reactor. It can also help outside the plant—especially with safety reports and rules. Getting approval to build a nuclear reactor takes years. Governments and safety agencies have to read thousands of pages of technical documents.The IEA explains that large language models (LLMs) can help speed this up. These models turn complex data into clear summaries that both engineers and regulators can understand. They also help explain system faults in plain language during training or emergency situations.

SMRs and the Energy Transition....read on    https://carboncredits.com/from-code-to-core-how-ai-is-fueling-the-rise-of-small-modular-reactors/

AI’s need for speed.....The US alone has roughly 3,000 data centers, and current projections say the AI boom could add thousands more by the end of the decade. The rush could increase global data center power demand by as much as 165% by 2030,according to one recent analysis from Goldman Sachs. In the US, estimates from industry and academia suggest energy demand for data centers could be as high as 400 terawatt-hours by 2030—up from fewer than 100 terawatt-hours in 2020and higher than the total electricity demand from the entire country of Mexico.There are indications that the data center boom might be decelerating, with some companies slowing or pausing some projects in recent weeks. But even the most measured projections, in analyses like one recent report from the International Energy Agency, predict that energy demand will increase. The only question is by how much.  

Many of the same tech giants currently scrambling to build data centers have also set climate goals, vowing to reach net-zero emissions or carbon-free energy within the next couple of decades. So they have a vested interest in where that electricity comes from. Nuclear power has emerged as a strong candidate for companies looking to power data centers while cutting emissions. Unlike wind turbines and solar arrays that generate electricity intermittently, nuclear power plants typically put out a constant supply of energy to the grid, which aligns well with what data centers need. “Data center companies pretty much want to run full out, 24/7,” says Rob Gramlich, president of Grid Strategies, a consultancy focused on electricity and transmission. It also doesn’t hurt that, while renewables are increasingly politicized and under attack by the current administration in the US, nuclear has broad support on both sides of the aisle.  The problem is how to build up nuclear capacity—existing facilities are limited, and new technologies will take time to build. In 2022, all the nuclear reactors in the US together provided around 800 terawatt-hours of electricity to the power grid, a number that’s been basically steady for the past two decades. To meet electricity demand from data centers expected in 2030 with nuclear power, we’d need to expand the fleet of reactors in the country by half.

New nuclear news......Some of the most exciting headlines regarding the burgeoning relationship between AI and nuclear technology involve large, established companies jumping in to support innovations that could bring nuclear power into the 21st century.read on    https://www.technologyreview.com/2025/05/20/1116339/ai-nuclear-power-energy-reactors