Artificial intelligence applications are shown at Artificial Intelligence Pavilion of Zhangjiang Future Park during a state-organized media tour June 18, 2021 in Shanghai, China. (Photo by Andrea Verdelli/Getty Images)Getty Images
Artificial intelligence is all the rage—crazy things that can improve energy efficiency, productivity, and outcomes. But it’s a young concept with room for error. And that’s why the smart move is to test a problem and simulate solutions, sharing the best results across the industry.
Artificial intelligence – or AI for short – gives companies a holistic view and collects data to improve productivity, limit expenses and reduce environmental costs – a process that is now possible thanks to bandwidth capacity and cloud technologies. AI can develop algorithms and thus eliminate repetitive tasks. This allows managers to increase productivity and minimize costs, enabling them to compete globally.
Consider the massive deployment of renewable energy and its impact on the power grid—the most advanced machine ever invented: the addition of intermittent resources is making delivery more complex, compounded by the deployment of electric vehicles and battery storage.
“If we want people to do that, we’re going to need many, many, many more of them to the point where it doesn’t make economic sense anymore. However, let’s assume we can use these technologies properly. In this case, it can help us manage a very complicated grid to bring low-cost, decarbonized energy to everyone,” says Jeremey Renshaw, chief technical officer of the Electric Power Research Institute.
Renshaw, who spoke at the United States Energy Association’s virtual AI summit where this reporter was a panelist, adds that the technology is enabling grid operators to make key decisions in real time. For example, the utility industry can collect hundreds of thousands of images of the transmission and distribution system – these are used to create algorithms that integrate data and offer solutions.
AI eliminates “mundane activities” so those running heavy industrial operations can solve problems and improve performance, resulting in more profitable businesses. For power plants, technology can help managers balance supply and demand issues, maintain their assets, and improve safety measures.
How reliable are the algorithms? at Hewlett-Packard Enterprises (HPE), operates a robot (developed in collaboration between HPE and German AI startup Aleph Alpha) that can speak and answer questions at HANNOVER MESSE 2023, the Hanover technology fair, in Hanover on April 17. April 2023. – The fair will take place from April 17th to 21st, 2023. (Photo by Axel Heimken / AFP) (Photo by AXEL HEIMKEN/AFP via Getty Images)AFP via Getty Images
In other words, the machines run through countless scenarios and remember all sorts of patterns – something that humans cannot do. The algorithm takes the data and updates it as circumstances change. When this performance is combined with cloud computing and high-speed 5G networks, businesses can harness the intelligence and gain a competitive edge.
According to McKinsey & Company, AI and digitalization can increase plant productivity by up to 20% while reducing maintenance costs by 10%.
AI can also predict weather patterns, allowing grid operators to accurately estimate when wind and solar resources will be available. The network is therefore more reliable.
Marc Player, Head of Global Business Development at Nvidia, explained to the audience that the technology can accurately and effectively simulate weather and climate forecasts. The practical effect is to maximize wind and solar resources — and know where they are — not just now, but 10 to 20 years from now. System designers use this information to design the required infrastructure.
“We can get an accurate representation of future climate,” he says. However, “I don’t expect that we’re going to see a lot of autonomous operations without humans in circulation.”
Where’s the manager?
Of course, AI is not foolproof. Its answers are mathematical algorithms developed by humans. Something unforeseen can happen: earthquakes, solar flares or forest fires that require a real person to intervene and make decisions. Such events can lead to widespread power failures and endanger lives.
When an undesirable event occurs, who or what is to blame: the developers of the algorithm, the energy company that relies on artificial resources, or the person on site managing the problem? Because the web is so complex, companies need to properly train their leaders so they can make informed decisions. As the economy becomes decarbonized and requires more electricity — wind and solar — the network must expand and have the intelligence to redirect electrons to avoid congestion or hotspots.
Daniel Robertson, senior director of innovation at Landis + Gyr, says it’s analogous to automated vehicles. In this case, the chain of possible liability extends from the automobile manufacturer to the technology developer and the driver.
“We have a complex and sensitive system that should not be entrusted entirely to an AI system,” adds John E. Savage, Wang Professor Emeritus of Computer Science at Brown University. “If a scenario isn’t planned and you don’t have someone on the ball, you’re in trouble. AI is a very powerful and useful tool. It increases productivity everywhere and we will live with it for the rest of our lives. On the other hand, we also have to understand the associated risks.”
That is well said – especially in the energy sector, which is the basis for human existence and economic progress. In the United States, the sector accounted for 4.8% of gross domestic product. AI holds tremendous potential and poses pitfalls that are forcing the corporate world to tread carefully.
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I’ve been involved with energy since the late 1990s, beginning with the rise and fall of Enron—first as a magazine writer before becoming a columnist and editor. I’ve been a columnist for Forbes for more than 11 years. My focus has shifted from the “old energy industry” to the “green energy industry”. My stories, which cover the whole world, have appeared in and been quoted by dozens of publications and broadcasts. I’m also Editor-in-Chief of Environment+Energy Leader and the Coalition for Rainforest Nations, representing 53 rainforest countries worldwide. My job is to research and write about these countries and help them reach net zero to fulfill their Paris promises. My features and my columns have won several national awards. Twitter: @Ken_Silverstein. Email: [email protected]
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