Utilidata’s Post

VEIR Closes $75M Series B to Deliver Superconducting Solutions for AI Data Centers and High-Capacity Power Lines, Driving Grid Resilience and Global Decarbonization - VEIR announced the closing of a $75 million Series B funding round led by Munich Re Ventures. - New investors included Microsoft's Climate Innovation Fund, National Grid Partners, Piva Capital, and Tyche Partners. - The investment will accelerate VEIR's efforts to commercialize its superconducting solutions for data centers and utilities. - VEIR's superconducting technology can deliver up to 10 times the power of conventional cables while maintaining the same voltage. - This technology addresses increasing power demands from AI models and advanced GPUs in data centers. - VEIR's solutions can help data center operators improve efficiency, server latency, and campus design. - Global energy demand is expected to rise by over 30% in the next two decades, creating challenges for existing transmission systems. - VEIR's superconducting solutions enable transmission lines to carry more power in the same space and facilitate integrating new energy resources into the grid. - The company's innovations are crucial for modernizing the transmission grid to support AI-driven infrastructures and climate resilience. - VEIR's offerings are designed to enhance existing infrastructure while addressing power density needs for data centers and renewable energy expansion. - The company aims to revolutionize power and data infrastructure with its superconducting solutions for sustainable energy delivery. https://lnkd.in/gVdPV4-q

Communication. A unanimously essential tool to solve disagreements, make progress, and create something new. Distributed energy resources should be no different. We must consider a future where our energy assets can communicate more freely, more efficiently, than we can. The Energy Services Interface (ESI) framework paints energy management not as a network of pieces of equipment, but rather as a continuous stream of energy services, utilizing a service-oriented approach independent of the many different heterogeneous devices that might be providing the service. Learn more about our vision for modernized grid infrastructure at: https://lnkd.in/eVz-2pws #DER #opensource #energy #saas #ESI #DOE

Learn more about our partnership with the Joint Office of Energy and Transportation in this new blog post.

we must advance quantum computers because they will exponentially increase computing power while consuming far less energy than massive conventional data centers. They are also necessary for data security because whoever has the most advanced quantum computers will have the most secure data. Also, let's build chip factories space! Wouldn't that be awesome??? 😎 probably 10 years until space based manufacturing is competing with terrestrial manufacturing and then it will rapidly surpass Earth to unfathomable scales by 2050

📢 ENERGY EFFICIENCY WIN! On Earth Day, Google, Los Angeles Trade Technical College, Florida Semiconductor Institute and Vital Integration of Environmental Electronics became the most recent signatories of our Energy Efficiency Scaling for 2 Decades (EES2) initiative, joining other cosigners—made up of leading organizations in government, academia, and high-technology industries—to work together to improve energy efficiency of semiconductors, technologies that we increasingly rely on in our modern world.   Over the last 30 years, energy efficiency improvements in the semiconductor industry have fallen out of pace with the surging global demand for computing and artificial intelligence technologies (think everything from healthcare, to transportation, to massive data centers, to the phone in your pocket!). As a result, semiconductor applications are now the fastest-growing consumers of electricity and could soon account for the largest share of global greenhouse gas (GHG) emissions associated with electricity use. DOE’s Advanced Materials and Manufacturing Technologies Office (AMMTO) aims to reverse that trend. Over the last year, AMMTO and its partner organizations have been developing a semiconductor roadmap, which features a comprehensive strategy for improving the efficiency, sustainability, and competitiveness of the American semiconductor and related products. The roadmap is scheduled for release for public comment in May.   Learn more about this ambitious initiative ⤵️

What is virtualization and how does it apply to Utilities? Listen to Kenneth Rabedeau, Head of Energy NAM, Nokia, as he talks about virtualization and how this can benefit utilities through their energy transition. Watch the video now: https://nokia.ly/40jXk6c #utilities #virtualization #energy

Due to AI driven demand - the data center market to grow at a compound annual growth rate of 11.3% through 2026 High-intensity computing and cooling systems in ONE datacenter require the same amount of electricity needed to power 750,000 homes (or a small city!) TD Cowen report projects "75-100% of incremental U.S. data center load growth will be supported by natural gas #datacenters #powergeneration #renewables #naturalgas #grid #gpu https://lnkd.in/gHJwv_CB

Looking to optimize energy with edge computing? Start here. With the right steps, edge computing can transform your energy management. Here are three practical steps to begin your edge computing journey 👇 1️⃣ Assess your infrastructure Begin by evaluating your current IT and OT systems to identify edge computing opportunities, such as real-time monitoring or remote asset management. Pinpointing where edge computing can integrate with existing assets keeps costs manageable while targeting the most impactful areas. For instance, look at where delays in data processing impact operations the most—like remote wind turbines that need immediate data feedback. 2️⃣ Choose efficient edge devices Select edge devices designed for energy efficiency, capable of processing data locally without heavy power demands. Prioritize standardized devices with low-power modes and easy maintenance for smoother deployment. Options like ARM-based processors can be ideal for their balance of processing power and energy efficiency. 3️⃣ Deploy gradually and monitor results Roll out edge solutions in phases, starting with a pilot project to test energy savings and optimize maintenance schedules. Use the data gathered to refine your approach, focusing on what worked best before scaling up. A small-scale deployment, like real-time monitoring in one solar plant, helps you evaluate edge performance and ROI before expanding. The result? Edge computing can transform energy management, starting with infrastructure assessment, smart device selection, and phased deployment. Which step are you most likely to implement first in your energy strategy? Let’s talk strategy below! #energy #edgecomputing

This is the kind of Grid Tech solution that makes the Software Engineer in me so happy. When I first started getting into Grid Tech and Energy, I was a bit surprised at the stodginess of the system. "What do you mean you can't coordinate energy generating in real time to optimize pricing and capacity across the grid," I naively asked. The fact is that the grid was built for big power generation facilities that are centralized, cumbersome, and expensive to turn on and off, and it operates with a level of instrumentation and understanding of the real time generation and demands that seems primitive to those of us who have written software for the web. But in a world of Distributed Energy Resources (DER's) that all needs to change. With the advent of millions of distributed generators and storage facilities, the grid needs to start to look a lot more like the Internet, with real-time data to coordinate a vast network of resources effectively and efficiently. Nowhere is this disconnect more apparent than in the way utilities and grid operators plan for transmission line capacity. Basically, if you want to put a new solar generation facility on the grid, the utility often has to assume that the system will be generating maximum capacity onto a grid with zero demand - a worst-case scenario that never actually happens. These are "static ratings" of transmission line capacity, and they can project a lot more grid congestion than is actually present. That's because we don't have real-time data about how much energy is actually being generated and consumed in different parts of the grid. And that's the problem that these Dynamic Line Rating (DLR) systems aim to solve. Knowing how much energy is actually running through any given transmission chokepoint on the grid will be critical to making the grid more "Internet-like", ensuring we are building new expensive transmission equipment in the right places, and optimizing the use of the lowest cost energy generation resources to save consumers money. Also, they're installed by drones. https://lnkd.in/e8FtyYb2