With the global carbon emissions tipping point right around the corner and catastrophic climate change becoming an ever more likely outcome for the not-too-distant future, finding a way to curb emissions and encourage cleaner energy production practices has never been so important or so urgent. To that end, it is also imperative that the technology around cleaner energy alternatives to fossil fuels continues to advance and that it does so in a hurry.

Currently, one of the biggest hurdles standing in the way of renewable energies like solar and wind power is the fact that they are variable, meaning that they depend on external and uncontrollable factors. They are only able to generate energy when the sun is shining or when the wind is blowing, and depending on the whims of the weather does not lend itself to steady, dependable energy production. As Oilprice reported earlier this year, “the simplest and most realistic solution for creating the kind of flexibility that the grid would need in order to run smoothly off of renewable energy lies in energy storage.”

The report goes on to point out that this realization is not new and that, in fact, the energy storage industry is not only already booming is continuing to grow at a rapid pace. According to a report by Energy Storage News based on an April Wood Mackenzie analysis, “grid-connected energy storage deployments have increased significantly around the world in the past five years, with an impressive compound annual growth rate of “74% worldwide in the years 2013 to 2018, with a ‘boom’ in deployment figures expected over the next five years.”

But in order for these systems to work as efficiently and inexpensively as possible, a further tech breakthrough is needed--and the answer lies with Artificial Intelligence. Whatever direction our energy future is headed, AI is likely going to play a large role in it. This is not new news either. Back in May of 2017, Oilprice reported in an article aptly titled “Artificial Intelligence Is Crucial For The Energy Industry” that “though the necessary technology is still in development, AI would be able to use predictive algorithms to balance grids, negotiate joint actions to self-heal networks in case of bugs or hacks, and to assess the reliability of production and consumption figures created by producer-consumers. The system will have to learn the minutiae of each locality’s behavior of supply and consumption, with the ability to store or release energy as needed to keep the grid balanced.”

Now, two and a half years later, the technology has advanced considerably, along with the urgency of finding a wide-scale solution to making variable renewable energies like wind and solar a viable replacement for high-polluting fossil fuels. As reported by the World Economic Forum, a non-governmental organization (NGO) that lobbies for deregulation on behalf of a consortium of 1,000 multinational corporations, “the pressure is on to cut carbon emissions and, as a result, methods must be found to manage the increasing gigawatts of unpredictable, weather-dependent renewable energy flowing on to power grids. The cost of electricity is also a concern, not just for consumers, but for governments keen to keep their voters happy. In short, there is a global demand for clean, cheap, reliable energy – and artificial intelligence (AI) is increasingly being used to help meet this need. Enabling the growth of low-carbon, green electricity is an AI application with a potentially huge long-term impact.”

Currently, the research around AI in the energy sector is devoting a lot of time and energy to investigating the complex decision-making capabilities of AI in applications that are simply too complicated for humans to do efficiently, if at all. AI can potentially be used to “manage electricity shortfalls by briefly switching off power demand across entire communities or regions.” Aidan O’Sullivan, head of University College London’s energy and AI research, told reporters for the World Economic Forum that “This might be thousands of refrigerators in people’s homes or large sites of demand, such as industrial plants [...] The speed and complexity of this task requires advanced AI.” Related: What Broke The Bond Between Oil And Gold?

While this may sound invasive or dystopian to the average energy consumer, it’s actually just a continuation of the way our appliances and energy access already work. The energy grids that we depend on are evolving all the time, whether we are aware of the changes or not - and let’s be honest, even for savvier consumers, it’s more likely to be not. It’s really not a big departure from the current energy landscape, according to the World Economic Forum’s report, which continues: “Ceding control of your home to a remote AI might seem like the stuff of science fiction, but the integration of AI into our appliances is already underway. For example, AI is being used to manage energy use in a device most of us use every day – mobile phones. The latest iteration of Google’s Android phone operating system includes a function which studies your app habits to ensure battery is deployed only on the ones you like the most. Meanwhile, rarely used apps, which would previously hum away in the background consuming power, are shut down.”

What’s more, the applications of Artificial Intelligence in the energy sector’s future is not limited to solar and wind power - far from it. Artificial Intelligence is being intensively researched for its potential applications in the nuclear power industry as well. Nuclear fission, while far from perfect, is still regarded by many as the energy of the future thanks to its massive efficiency with absolutely zero carbon emissions. Despite all the promise it holds for decarbonizing our energy landscape, however, the nuclear industry is struggling in the West, where nuclear power has been unable to compete in an energy market flooded by cheap natural gas, and continues to face massive scrutiny and distrust from politicians and constituents alike. This is, in large part, thanks to high-profile nuclear disasters like the tragedies at Fukushima, Three Mile Island, and Chernobyl.

Artificial Intelligence, however, could be the key to turning around the public’s distaste for nuclear energy and revitalizing the industry in the United States. This June, in an article titled “Can Artificial Intelligence Save The Nuclear Industry?” Oilprice reported that robots are being dispatched to solve some of the most concerning problems in the nuclear power industry--cleaning up radioactive waste. According to reporting by ExtremeTech, scientists have “created imaging software that lets the robot “see” the world around it and identify objects like pipes, handles, and other materials common inside nuclear decommissioning sites.” These nuclear cleanup robots are still in development, but this model is likely an early iteration of what will become an industry-wide standard.

And then of course, there is nuclear fusion: the holy grail of clean energy. Scientists have long dreamed of making commercial nuclear fusion a reality. As soon as researchers are able to crack the code of being able to successfully achieve nuclear fusion on earth without applying more energy than the process creates, nearly all of the world’s energy qualms will be solved. The ultra-powerful process of fusing atoms results in absolutely no nuclear or radioactive waste of any kind and emits no carbon, making it the ultimate clean energy - if we can ever get it to work, that is. Related: Protect The Oil: Trump’s Top Priority In The Middle East

Here is where Artificial Intelligence once again enters the picture. Just this August a group of scientists from the supercomputing facility Oak Ridge National Laboratory reported a breakthrough that could finally lead to the realization of commercial nuclear fusion. The lab reported that “a team of researchers has leveraged supercomputer-powered AI in an effort to address one of the key problems with scaling up fusion energy.” As Oilprice went on to explain in its own report, “that key problem is the tricky issue of managing plasma.” The article went on to explain: “Currently, in the majority of nuclear fusion research, plasma is created and maintained inside of a device called a tokamak [...] but even the most cutting-edge versions of these devices still have a lot of limitations” which allow plasma to escape and disrupt the fusion reaction. This issue is exacerbated when fusion reactors are scaled up. AI could fix this, however, by forecasting and avoiding these issues before they even occur.

The potential applications of Artificial Intelligence in the energy sector are widespread and diverse, which in and of itself is a good thing. What our current oil-addicted energy industry needs most is innovation, experimentation, and, above all, disruption. It’s uncertain which applications of AI will take off and which will be blips on the timeline of energy evolution, but you can be absolutely sure that whatever our energy landscape looks like in 30 years, AI will be a huge and crucial part of it.

By Haley Zaremba for Oilprice.com

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