Fox News anchor Bret Baier examines the U.S. power supply on'Special Report.' Over the next two decades, global electricity demand is expected to double, growth we haven't seen since post-World War II. To meet historic projections, we need to generate abundant, reliable and affordable energy at a massive scale. But new generation won't be enough. We must dramatically modernize the country's electrical grid infrastructure, the invisible backbone of our entire energy system.

AI is "not my thing," President Donald Trump admitted during a speech in Pittsburgh on Tuesday. However, the president said during his remarks at the Energy and Innovation Summit, his advisors had told him just how important energy was to the future of AI. "You need double the electric of what we have right now, and maybe even more than that," Trump said, recalling a conversation with "David"--most likely White House AI czar David Sacks, a panelist at the summit. "I said, what, are you kidding? That's double the electric that we have. Take everything we have and double it."

Artificial intelligence (AI) has become a crucial instrument for streamlining processes in various industries, including electrical power systems, as a result of recent digitalization. Algorithms for artificial intelligence are data-driven models that are based on statistical learning theory and are used as a tool to take use of the data that the power system and its users generate. Initially, we perform a thorough literature analysis of artificial intelligence (AI) applications related to renewable energy (RE). Next, we present a thorough analysis of renewable energy factories and assess their suitability, along with a list of the most widely used and appropriate AI algorithms. Nine AI-based strategies are identified here to assist Renewable Energy (RE) in contemporary power systems. This survey paper comprises an extensive review of the several AI techniques used for renewable energy as well as a methodical analysis of the literature for the study of various intelligent system application domains across different disciplines of renewable energy. This literature review identifies the performance and outcomes of nine different research methods by assessing them, and it aims to distill valuable insights into their strengths and limitations. This study also addressed three main topics: using AI technology for renewable power generation, utilizing AI for renewable energy forecasting, and optimizing energy systems. Additionally, it explored AI's superiority over conventional models in controllability, data handling, cyberattack prevention, smart grid implementation, robotics- AI's significance in shaping the future of the energy industry. Furthermore, this article outlines future directions in the integration of AI for renewable energy.

The Fourth Industrial Revolution – artificial intelligence in particular – has the potential to solve some of the current conundrums of the green transition. Over the last two centuries, the world's major energy transitions were driven primarily by technological breakthroughs. The steam engine allowed coal to fuel the Industrial Revolution and displaced traditional biomass in the world energy mix. Then the internal combustion engine opened the door for oil to dominate the transport sector and the global energy mix for decades – a position it still holds to date. Today, one major development is still unfolding; its final impact is difficult to predict or even comprehend at this stage.

RIYADH, March 9, 2022 – Pasqal, a developer of neutral atom-based quantum technology, and ARAMCO announced the signing of an MoU to collaborate on quantum computing capabilities and applications in the energy sector. Objectives include accelerating the design and development of quantum based machine learning models as well as identifying and advancing other use cases for the technology across the Saudi Aramco value chain. To that end, both companies plan to explore ways for collaborating and cultivating the quantum information sciences ecosystem in the Kingdom of Saudi Arabia. Quantum computing can be used to address a wide range of upstream, midstream and downstream challenges in the oil and gas industry including network optimization and management, reaction network generation and refinery linear programming. The collaboration will explore potential applications for quantum computing and artificial intelligence in these areas as well.

Machine learning and AI are probably the most buzz commendable business terms that you hear nowadays. Along these lines, business across enterprises are searching for ways of executing them to improve and computerize their center cycles. Also, the energy business is no exemption! Truth be told, sustainable power organizations (wind, solar, hydro, nuclear) have extraordinarily profited from the force of AI throughout the long term. They have figured out how to bring down their expenses, improve forecasts, and increment their portfolio's pace of return.

Marshall Worth, senior project manager AI at PowerSecure, discusses artificial intelligence and a practical approach that microgrid customers can take today to achieve their energy goals of the future. With as fast as technology has progressed over the last decade, and with the promise of self-driving cars on the horizon and the electrification of everything, it's only natural to question when this is all going to filter into our everyday, energy consuming lives. In this device-driven age, shouldn't we already have the artificial intelligence (AI) capabilities to reduce our carbon footprint today and our energy bill tomorrow? Those of us who work in the energy industry are fortunate; we are naturally driven to innovate and build the future of energy. However, it's a bit ambitious to think that the same machine that drives our car and controls our thermostat today can also manage on-site generating assets.

In researching for this blog, I reached out to Brendan Bennett, a Reinforcement Learning Researcher at the University of Alberta, for his thoughts on how emerging digital technologies may be deployed in the energy industry. Brendan and I discussed how some recent landmark accomplishments in artificial intelligence might soon make their way into the energy industry. Digital innovation in commercial spheres has largely been a story of improving efficiency and reliability while reducing costs. In the energy sector, these innovations have been a result of oil and gas companies doing what they do best: relying on talented engineers to improve on existing solutions. Improvements have quickly spread across the industry, bringing down costs and making processes more efficient.

However, most companies don't have the resources to implement sophisticated AI programs to stay secure and advance digital capabilities on their own. Irrespective of size, available budget, and in-house personnel, all energy companies must manage operations and security fundamentals to ensure they have visibility and monitoring across powerful digital tools to remain resilient and competitive. The achievement of that goal is much more likely in partnership with the right experts. MIT Technology Review Insights, in association with Siemens Energy, spoke to more than a dozen information technology (IT) and cybersecurity executives at oil and gas companies worldwide to gain insight about how AI is affecting their digital transformation and cybersecurity strategies in oil and gas operating environments. Energy sector organizations are presented with a major opportunity to deploy AI and build out a data strategy that optimizes production and uncovers new business models, as well as secure operational technology. Oil and gas companies are faced with unprecedented uncertainty--depressed oil and gas prices due to the coronavirus pandemic, a multiyear glut in the market, and the drive to go green--and many are making a rapid transition to digitalization as a matter of survival.

AJ Abdallat is CEO of Beyond Limits, the leader in artificial intelligence and cognitive computing. Our world has reached a point where society recognizes the planet is under stress, with energy and technology sectors at the forefront of this reckoning. Microsoft, in association with PwC, revealed the urgency of the challenges currently facing our planet, reporting that 91% of people don't live in standard air quality-controlled areas, 60% of biodiversity has been lost since 1970, and greenhouse gases are at their highest levels in 3 million years. To get ahead of these challenges, we must reduce carbon footprints. AI will play a crucial role in supporting the energy industry's goals of achieving a more efficient, connected and sustainable future.