Strategic Decisions Group (SDG)’s Post

How do you see AI shaping the future of renewable energy and its impact on our daily lives? What do you think how can we leverage this fast growing technology to enable green transition? #RenewableEnergy #AIRevolution #SustainableFuture

#ICYMI: AES CEO Andrés Gluski joined CNBC to discuss the impact of #AI on the future of #renewableenergy. 🌱⚡️ As AI continues to advance, so does energy demand, increasing by a notable 15% annually for data centers, outpacing the overall growth of 4%. Andrés emphasized, "The only way the United States (energy) demand does not grow, quite frankly, is if suddenly the AI revolution stops." In 2023, we generated enough energy to serve the annual consumption of approximately 22 million people in the places we operate. And that is continuing to grow. With a more than 12 GW backlog, AES is one of the largest renewable energy providers to corporations and specifically to technology companies. 🔗 Watch the interview: https://lnkd.in/eGQ--bcG #AES #EnergyInnovation #SustainableEnergy #EnergyStorage #PowerGrid #AI #TechTrends

How does artificial intelligence (AI) support the integration of renewable energy sources? How can businesses get started with integrating AI into their Net-Zero initiatives? What role does AI play in energy efficiency? All valid questions. In a world where renewable energy integration and grid stability are paramount, AI serves as a driving force behind these critical transformations, so businesses can optimise energy consumption, predict demand patterns, and automate energy management processes. AI’s ability to process vast amounts of data, analyse complex systems, and make intelligent decisions in real-time makes it an invaluable ally in achieving Net-Zero goals. At ARO we aim to answer these questions and more by leveraging innovative AI functionalities, on top of our tech expertise, to guide businesses through this complex landscape, all the way from initial audits to automated carbon reporting and green energy sourcing. Read more here: https://lnkd.in/eqcXhuVd

For renewable generation to take up a larger role in the global energy mix, #artificialintelligence (AI) may be key to achieve the highest efficiencies. Enverus has introduced Enverus Instant Analyst™, a pioneering generative AI tool designed to address the energy data gap. Traditional methods of accessing and interpreting energy data are arduous and resource-intensive. This tool empowers energy companies to gain deep insights into the energy ecosystem, tackle complex questions, and uncover research supporting their strategic objectives. By leveraging this intelligence, companies can optimize their projects and operations for increased efficiency, sustainability, and profitability. Do you want to learn more? 👇

In the renewable energy industry, everyone’s talking about how recent innovations in generative artificial intelligence (AI) could be a key driver of change and progress. With its momentum showing no signs of slowing down, those who aren’t prepared to leverage this technology risk being left behind. As we work to harness AI to accelerate the global energy transition, it’s important to start with an understanding of its capabilities and what is needed to reap its benefits. Join Steve Voss, VP of Advanced Analytics at Power Factors, as he breaks down the impact of AI on renewables and the crucial role of large, trustworthy datasets in our first Ask an Expert video series, "AI Explained." Watch the series here: https://lnkd.in/gURqu4WN #RenewableAI #AIforSustainability #AIforCleanEnergy

Artificial intelligence (AI) innovations are becoming increasingly critical to advancing the energy transition, giving rise to compelling new use cases for managing and automating renewable energy assets. One such example is CGI’s “hybridization model” which uses AI to evaluate, control and recommend actions to optimize the performance of hybrid renewable energy assets and enable timely, strategic operational decisions. Learn more about the key benefits of hybridization https://go.cgi.com/3TnhN4N #artificialintelligence #ai #CGIAI #innovation #energytransition #utilites #renewableenergy

Key Points from "How AI Accelerates Energy Transition" The document discusses the role of artificial intelligence (AI) in accelerating the energy transition. AI is identified as a crucial technology for optimizing energy production, distribution, and consumption. Key Points: Introduction to Energy Transition: The document introduces the concept of energy transition, highlighting the global shift towards sustainable and renewable energy sources. Emphasis is placed on the need to reduce greenhouse gas emissions and combat climate change. AI's Role in Energy Transition: AI is presented as a powerful tool for transforming the energy sector. It is instrumental in enhancing the efficiency of energy systems and making them more sustainable. Data Analytics and AI: The importance of data analytics in the energy sector is discussed, with AI playing a pivotal role in processing and deriving insights from massive datasets. Grid Optimization: AI is used to optimize energy grids, ensuring that electricity is distributed efficiently and reliably. Smart grids are highlighted as a key application of AI in this context. Renewable Energy Integration: AI technologies help integrate renewable energy sources such as wind and solar into the existing energy infrastructure. This integration enhances the reliability and stability of renewable energy systems. Predictive Maintenance: AI enables predictive maintenance of energy infrastructure, reducing downtime and improving overall performance. It can predict equipment failures before they occur, saving both time and money. Energy Efficiency: AI-driven solutions are essential for improving energy efficiency in buildings, industries, and transportation. Smart energy management systems are discussed as a means to achieve energy savings. Demand Response Programs: AI facilitates demand response programs that encourage consumers to use energy during off-peak hours, reducing strain on the grid. Environmental Benefits: AI-driven energy solutions contribute to reducing carbon emissions and mitigating the impact of climate change. Sustainability and environmental conservation are core themes throughout the document. Challenges and Future Prospects: Challenges related to data privacy, cybersecurity, and AI adoption are acknowledged. The document also explores the potential for AI to drive further innovation in the energy sector. Case Studies and Examples: Real-world case studies and examples illustrate how AI has been successfully implemented in energy transition projects. Overall, "How AI Accelerates Energy Transition" underscores the critical role of artificial intelligence in reshaping the energy landscape towards sustainability, efficiency, and environmental stewardship. #EnergyTransition #AIinEnergy #RenewableEnergy #SmartGrid #DataAnalytics #Sustainability #EnvironmentalImpact #EnergyEfficiency #PredictiveMaintenance #ClimateAction #GreenTech #CleanEnergy #Innovation #CarbonReduction #FutureOfEnergy

The call for innovative energy solutions to meet the surging power demands of AI is more pressing than ever, and geothermal energy emerges as a compelling option. Its consistency and renewability align perfectly with the imperative for carbon-free energy production. As we chart the course toward AI's future, a diversified energy portfolio that includes geothermal sources becomes paramount for both environmental stewardship and responsible AI development. JRG Energy, known for innovative solutions, could play a crucial role in exploring geothermal options, offering a sustainable path forward for powering AI responsibly and mitigating environmental concerns. So, why not Geothermal? It's a question that prompts us to consider and prioritize environmentally friendly alternatives, urging a shift toward energy sources that align with our commitment to a sustainable and responsible AI future. #GeothermalEnergy #JRGEnergy #AIResponsibility #SustainableFuture

Some of the future predictions of AI: In the energy sector, Artificial Intelligence (AI) models will be used to optimize consumption and production ⚡ Such as: 1. Predicted demand: Predictive analytics powered by AI will enable more accurate forecasting of energy demand. This will allow energy providers to anticipate usage patterns, adjust operations in advance, and ensure that they can meet demand without overproducing or underproducing energy. 📈🔋 2. Management of renewable sources: AI will improve the integration and management of renewable energy sources such as solar and wind power. By predicting fluctuations in renewable energy production and adjusting accordingly, AI will help maintain a stable and reliable energy supply. 🌞💨 3. Efficient distribution networks: AI will contribute to the development of more efficient energy distribution networks. By optimizing the flow of energy through the grid and minimizing losses, AI will ensure that energy is delivered to where it is needed most, enhancing the overall reliability and efficiency of the energy system. 🌐⚙️ VS: #linkedinlearning Pinar Demirdag #AI #energy #predictiveanalytics #renewableenergy #techinnovation #sustainablefuture #sustainabilityupdates #sustainability #rhetort

Here is my article on how we use Artificial Intelligence to enable and optimize the hybridization of renewable power plants at CGI: mix wind, photovoltaic and hydro energy sources, throw in battery storage and green hydrogen generation, plan your operation for lower production costs and higher revenues on the energy market.