Manjodh Kaur PhD’s Post

The role of AI in green hydrogen adoption The growing transition towards hydrogen adoption in the market, and the significant shift in hydrogen combustion characteristics compared to diesel and gasoline engines. While hydrogen has unveiled a broader potential for air-to-fuel ratio mapping, it has also promoted the risks of abnormal combustion phenomena near the limits of air-to-fuel ratios, such as pre-ignition. To mitigate the potential hazards associated with hydrogen internal combustion engines (ICEs), an Advanced AI Analysis ICE Tool (AAAICE) software has been developed to understand the prediction and elimination of abnormal combustion comprehensively. The software is designed to process ICE engine data and generate a complete cycle production of up to 200 cycles, with an AI-provided resolution of 0.1 crank angle. This innovation is poised to revolutionize the adoption of hydrogen ICE technology. Stay tuned for the upcoming results and a thorough comparison between actual abnormal and AI-generated cycles.

🤖 AI can 𝗌̲𝗂̲𝗀̲𝗇̲𝗂̲𝖿̲𝗂̲𝖼̲𝖺̲𝗇̲𝗍̲𝗅̲𝗒̲ improve 𝗴𝗿𝗶𝗱 𝘀𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 – here’s how: AI can 𝘱𝘳𝘦𝘥𝘪𝘤𝘵 energy production and demand accurately. This keeps supply and demand balanced dynamically. AI helps absorb fluctuations from renewable sources. ⚡️ It reduces peak loads, making the grid more stable. Here’s how AI improves grid stability: 𝟭. 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝘀𝗺𝗮𝗿𝘁 𝗴𝗿𝗶𝗱 𝘀𝘆𝘀𝘁𝗲𝗺𝘀:  ↳ AI monitors the grid continuously.  ↳ It detects anomalies and adjusts automatically. 𝟮. 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗺𝗮𝗶𝗻𝘁𝗲𝗻𝗮𝗻𝗰𝗲:  ↳ AI spots potential equipment failures early. ↳ It schedules maintenance proactively, reducing downtime. 𝟯. 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗲𝗱 𝗲𝗻𝗲𝗿𝗴𝘆 𝗳𝗹𝗼𝘄𝘀:  ↳ AI finds the most efficient energy routes. ↳ It reduces grid congestion and energy losses. 𝟰. 𝗥𝗲𝗻𝗲𝘄𝗮𝗯𝗹𝗲 𝗲𝗻𝗲𝗿𝗴𝘆 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻:  ↳ AI predicts weather conditions to optimize energy production. ↳ It minimizes the impact of intermittent sources on grid stability. 𝟱. 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰 𝘀𝘄𝗶𝘁𝗰𝗵𝗶𝗻𝗴:  ↳ AI enables faster response to outages. ↳ It limits the impact of outages and boosts system resilience. These AI applications make the grid more 𝗌̲𝗍̲𝖺̲𝖻̲𝗅̲𝖾̲, 𝖾̲𝖿̲𝖿̲𝗂̲𝖼̲𝗂̲𝖾̲𝗇̲𝗍̲, and 𝗋̲𝖾̲𝗅̲𝗂̲𝖺̲𝖻̲𝗅̲𝖾̲. They help meet the challenges of the modern energy transition.

"Powering AI with Clean Energy - A Future We Can Root For 🌍💡 Exciting news from the energy sector! Nuclear power companies Constellation Energy and Vistra are gaining momentum in the S&P 500, hot on the heels of Super Micro and Nvidia. While tech companies are usually the stars of investment portfolios, this shift is indicative of increasing bets on clean energy to power AI technology. With the incessant advancement in AI, its energy demand is soaring. This new attention to sustainability signifies a much-needed green pivot in the tech world. It's also a reminder that technology and sustainability can and should go hand-in-hand. So, what does it mean for the industry? Tech companies and power suppliers working together to fuel AI developments promotes a circular economy. It encourages innovation, making the future of AI brighter and greener. It's a win-win for the planet, the consumer, and businesses. So what are your thoughts on this clean energy movement in tech industry? Will it lead to more sustainable progress in AI? Let's discuss! 💭

In the future with wetware and nano technology, AI systems will be able to harvest energy from natural sources in several ways: Solar Energy: AI systems could use solar cells made from organic materials to capture sunlight and convert it into energy, similar to how plants perform photosynthesis. Soil: AI could harness energy from the soil through microbial fuel cells. These cells use bacteria in the soil to generate electricity by breaking down organic matter. Plants: AI systems might extract energy from plants by tapping into their natural processes. For example, they could use bio-electrochemical systems that draw electricity from the energy plants produce during photosynthesis. Decomposing Matter: AI could utilize decomposing organic matter as a source of energy. Microorganisms break down this matter and release electrons, which can be captured and used to power AI systems through bio-batteries. By integrating with natural processes, AI systems can become more self-sufficient and environmentally friendly, using renewable energy sources to sustain themselves.

Great speaking on the Leadership Panel “Optimising energy efficiency and how digital technologies will transform the energy value chain” at the #FEA2024 strategic summit. We spoke about what plants can do to get #sustainability results in the near term while the new #decarbonization infrastructure is being built. We spoke about #EnergyEfficiency and #EmissionsReduction as target areas which can be tackled through new, more mature, approaches to #digitalization using plant #automation. The good news is that the solutions are already available. I gave several examples or readymade automation solutions for energy efficiency and emissions reduction. Specifically, a common theme throughout was the need for sensors and #AI. Sensors provide the new data which is foundational to improvements. The need for AI to embed domain expertise, how equipment work, fail, and foul was discussed, i.e. mechanistic AI. It is a matter of using the right type of AI tool for each task. My key call to action is that automation is a key strategy for plants to achieve operational excellence. Therefore a larger portion of the company’s technology budget must be directed towards plant automation for transformation of work. If you don’t, you won’t be able to achieve sustainability improvements in the near-term. Big thankyou to the other panelists: @Eugene Loke of Trilliant, Ivan Tan of SP Digital, Luis F. Gonzalez of AboitizPower, Dr. Saurabh Katiyar PhD. ดร. นายชาวร้าฟห์ คาติยาร์ of CP Group, @Yogesh Agarwal of @ABB, and expert moderator and coach Eithne Treanor, Media Trainer and Communications Expert. Connect here to learn more about these automation solutions: https://lnkd.in/gXv4jExP

Artificial Intelligence, Machine Learning, Generative AI and Quantum Computing innovation is driven and composed of experienced energy professionals with "Sustainable Development Goals" in mind. Im honored to be working closely with like-minded individuals that have the same goals in mind, for all mankind. AI innovation within renewable energy involves key leadership and team members. Education, background and expertise always play a key roll in driving motivation within core competencies. As leading providers of renewable energy solutions, committed to driving innovation and sustainability in the energy sector, we have always found it best to allow equity of any said innovation to be the true tempature gage of one's idea or innovation. This creates ownership in idea's that may or may not be intellectual property of one said individual and definitely drives innovation. Supernova, its operations and team members are celebrating seven years of innovation today with opening our open door policy even futher by allowing all clients and customers to schedule meetings with one of our C-Suite and Account Executives. The Customer always comes first and that's how innovation happens.

Building on the power of reinforcement learning, let's explore how we can further revolutionize the wind energy industry. One promising avenue is the development of digital twins for wind turbines. By creating virtual replicas of real-world turbines, we can: Simulate various scenarios to test different operating strategies and identify optimal configurations. Optimize maintenance schedules by predicting component failures and proactively scheduling repairs. Reduce downtime and improve overall turbine efficiency. Another exciting area is the integration of edge computing with wind turbines. By processing data locally, we can: Reduce latency and improve real-time decision-making. Enhance data security by minimizing the transmission of sensitive information. Lower operational costs by reducing reliance on centralized data centers. As we continue to push the boundaries of wind energy technology, it's essential to consider the ethical implications of AI-powered solutions. How can we ensure that these technologies are developed and deployed responsibly, addressing concerns such as data privacy, job displacement, and environmental impacts? Let's discuss these topics and explore the future of wind energy together. What other innovative applications of AI do you envision?

As artificial intelligence (AI) technologies grow, they demand more power, stressing our energy grids and increasing carbon emissions. Training sophisticated AI models consumes vast amounts of electricity, posing challenges to grid capacity and environmental sustainability. However, renewable energy offers a promising solution. It can provide a sustainable power supply, enhance grid stability through smart management, and is increasingly cost-effective, aligning with regulatory and social pressures for greener practices. Renewables like solar, wind, and hydro can meet AI’s energy needs while minimizing its environmental footprint. By investing in clean energy, the AI industry can mitigate the impact of its power consumption, ensuring a sustainable path forward. This synergy between AI and renewable energy not only addresses pressing environmental concerns but also showcases how technological advancement can coincide with ecological responsibility, paving the way for a more sustainable future. At Nadia Partners we partner with amazing CEOs to build companies from scratch in both of these sectors. More to come.

AI will solve more problems than it will create! AI’s Impact on Data Centers: The rise of AI is significantly increasing the demand for data centers, which in turn is straining energy grids globally. Energy Consumption: Data centers are consuming vast amounts of electricity, with some facilities using as much energy as 30,000 homes. This surge is leading to power shortages and increased energy prices. Global Trends: Countries like Saudi Arabia, Ireland, and Malaysia are facing challenges as the energy required for data centers exceeds their renewable energy supply. Tech Companies’ Goals: Major tech companies like Amazon, Google, and Microsoft aim to run their data centers on green energy, but the rapid growth of AI is complicating these plans. Future Projections: By 2034, global energy consumption by data centers is expected to exceed the total annual electricity production of countries like Italy or Australia. https://lnkd.in/g7AYxSnh -data-centers-power-grids/?cmpid=BBD103024_TECH&utm_medium=email&utm_source=newsletter&utm_term=241030&utm_campaign=tech