Currents: AI & Energy Insights - July 2024
Welcome back to Currents, a monthly column from Reimagine Energy dedicated to the latest news at the intersection of AI & Energy. Every last week of the month, I’m sending out an expert-curated summary of the most relevant updates from the sector. The focus is on major industry news, published scientific articles, a recap of the month’s posts from Reimagine Energy, and a dedicated job board.
1. Industry news
Flexidao launched an hourly renewable energy certification scheme pilot in Japan. Flexidao is a Barcelona-based startup that offers an advanced data, software and advisory solution to the electricity market. They will work with Japanese company Jera Cross to provide their customers with real-time visibility into renewable electricity generated.
What I’m thinking: Flexidao’s latest pilot highlights a growing global trend towards more granular tracking and certification of renewable energy. Granular tracking of renewable energy generation serves as a critical foundation for developing AI-driven strategies that can ensure clean energy consumption around the clock. The resulting insights from these programs enable the creation of sophisticated demand-side flexibility mechanisms that can optimize energy use in tandem with renewable generation patterns.
Amazon meets 100% renewable energy goal, while Google is no longer claiming to be carbon neutral. Amazon’s claim is based on an annual matching between energy consumed and clean energy purchased, while the previous neutrality claim from Google was based on carbon offsets.
What I’m thinking: Annual matching is a good start, but in order to claim real carbon neutrality, hourly matching between consumption and clean production is necessary. Given the increasing focus on AI’s energy impact, and heightened scrutiny of companies' scope 3 emissions, the battle for cloud computing supremacy might be won by the organization that manages to provide certified carbon-free computing power at an hourly level. Technologies like those developed by Flexidao could play a crucial role in helping cloud providers achieve true carbon neutrality.
Powerledger launches a blockchain-powered energy trading platform in Austria. The platform will allow prosumers to monitor their energy usage and production, and share surplus energy with others across the country.
What I’m thinking: This project exemplifies how exponential technologies such as blockchain and AI can move beyond buzzwords to deliver real-world value. I’m also a big fan of the community-centric approach. In an increasingly digital world, technology should foster connection rather than isolation. Innovations that bring people together have a higher likelihood of widespread adoption and should be actively encouraged. Ultimately, the most impactful technologies are those that enhance our connections and improve our collective well-being.
Virtual Power Plants from Tesla and Sunrun delivered hundreds of MW of flexibility to the California grid, as scorching heat put it under extra stress during the month of July. These events involved mainly households with installed solar plus storage systems.
What I’m thinking: It’s great to see technology helping us adapt to the challenges posed by climate change. As renewable energy and battery storage capacity expands globally, we'll increasingly witness events like this. However, the current approach of simply turning off devices or coordinating multiple batteries to discharge simultaneously is quite basic. The future of VPPs lies in more sophisticated, continuous, and holistic grid management strategies that can adapt in real-time to changing conditions and optimize for multiple objectives simultaneously. Solving the complexity of this system will be one of the most exciting engineering challenges of the next decade.
2. Scientific publications
A Perspective on Foundation Models for the Electric Power Grid. Many papers have been published over the last couple of years about the use of foundation models for time series. I found this article to be a good overview of their use in the energy sector.
What I’m thinking: In fields like natural language processing and image generation, foundation models have widely demonstrated their value over the past two years. These areas benefit from well-defined, vast, and accessible datasets, as well as clear metrics for evaluating model performance. Additionally, the risk associated with errors in these applications is generally lower compared to the energy sector, where inaccuracies can have severe consequences. The energy sector’s complexity, regulatory environment, and the critical nature of its operations mean that any new technology, including FMs, must undergo rigorous validation and demonstrate unequivocal reliability before widespread adoption. Nevertheless, they are a powerful tool that we should keep experimenting with. Their application in the power sector represents a fascinating potential solution to an incredibly complex engineering problem.
3. Reimagine Energy publications
Check out my latest code tutorial to simulate rooftop solar energy production using Python.
4. AI in Energy job board
This space is dedicated to job posts in the sector that caught my attention during the last month. I have no affiliation with any of them, I’m just looking to help readers connect with relevant jobs in the market.
Senior Data Scientist, Electric Load Forecasting at National Grid
Senior Machine Learning Engineer at Carbon Re
PhD Candidate in Real Implementation of Model Predictive Control for Building Heating at Norwegian University of Science and Technology
Conclusion
With so much going on in the sector it’s not easy to follow everything. If you’re aware of anything that seems relevant and should be included in Currents (job posts, scientific articles, relevant industry events, etc.) please answer to this email or reach out to me on LinkedIn and I’ll be happy to consider them for inclusion!