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SUVs have completely taken over the American car market, and at this point, there’s one for just about every kind of driver. You can spend Bentley money on something ultra-luxurious, buy a rugged Toyota built for the trails, or grab a cheap compact crossover that still handles everyday life with ease.

The Linux community is dealing with its second major security risk in as many weeks. Security researcher Hyunwoo Kim has disclosed a new zero-day vulnerability, Dirty Frag, that gives intruders more control over virtually any Linux distribution once they have an initial foothold.

You probably already know Gboard offers a great voice typing experience. What you might not know is that on a Pixel device, Gboard also supports voice editing. You can take a messy voice draft and use commands to make precise edits, formalize it, or rewrite it—all without touching the screen.

At a glance

• We construct geographically grounded, electrically coherent power grid models entirely from publicly available data and release a dataset spanning 48 U.S. states and multi-state interconnections.
• The models support AC optimal power flow (AC‑OPF) analysis, enabling physics-based study of congestion, capacity, and demand siting without restricted data.
• We demonstrate applications including transmission expansion potential, targeted line upgrades, and placement of large datacenter loads.

Microsoft Research is excited to release an open dataset of approximate transmission topology of the U.S. power grid derived from publicly available data.

The ability to study transmission-level power grid behavior is essential for modern power systems research. Analyses of congestion, transmission expansion, demand growth, and system resilience all depend on network models with realistic topology, electrical parameters, and geographic grounding.

In most of the world, including the United States, realistic transmission-level grid data is classified as critical infrastructure information and subject to strict access controls. These restrictions exist for good reasons, but the resulting lack of realistic grid models is increasingly exacerbating the challenges power systems face. Decisions about where new load can be added – and how additional transmission assets can be deployed to support it – are often gated behind lengthy and opaque processes that can take years. For researchers developing new tools and algorithms, access typically requires long approval cycles, strict non-redistribution agreements, or costly commercial licenses.

As a result, many are left choosing between small “toy” networks with dozens of buses, or synthetic models that do not correspond to real infrastructure. This lack of realistic, shareable models is particularly limiting for data-driven and AI-based approaches, which require large volumes of physically plausible grid data for training and evaluation methods for grid analysis and planning.

Against this backdrop, a natural question arises:

Can we meaningfully understand how the U.S. power grid responds to modern stresses – and facilitate the development of actionable solutions for the system – using only open data?

In this work, we introduce an open-data-derived pipeline for constructing large-scale, transmission-level power grid models that realistically approximate existing networks without relying on proprietary or restricted datasets. We provide an open dataset derived from this process, consisting of transmission-level models spanning 48 U.S. states as well as interconnection-scale networks, ranging in size from small systems with as few as 11 buses to the full Eastern Interconnection grid connecting 21,697 buses. The pipeline has been validated across the continental United States, where sufficient open geographic, energy, and demographic data are available, and is designed to generalize to other regions with comparable public data sources. 

Using only publicly accessible datasets, the pipeline produces geographically grounded, electrically coherent transmission models at state, multi-state, and interconnection scales. These models preserve the geographic structure of transmission corridors, substations, and generators inferred from open data, while explicitly accounting for uncertainty where detailed operational parameters are unavailable through transparent feasibility reporting.

Importantly, these are not toy networks or abstract benchmarks. The resulting models support alternating current optimal power flow (AC-OPF) analysis across a wide range of scales, enabling physics-based investigation of questions such as where transmission capacity is physically constrained; where new demand can be absorbed; and how infrastructure changes propagate through realistic network layouts – using only open data.

In this post, we describe the approach at a high level and highlight the system level questions it enables.

How the pipeline works

The pipeline turns publicly available geographic and energy data into transmission-level grid models that are geographically grounded and usable for power flow analysis.

The starting point is OpenStreetMap (opens in new tab), which encodes the physical layout of transmission corridors, substations, and power plants. This geographic skeleton is then augmented with open datasets describing generation capacity, fuel mix, demand, and operational boundaries (including U.S. EIA energy statistics and U.S. Census data), allowing the models to go beyond topology and represent how electricity is produced and consumed.

The key test is solvability. In power system analysis, solving optimal power flow (OPF) problems is a practical check on whether a network description is electrically coherent and practically relevant. OPF determines how generation can be dispatched to meet demand while respecting physical constraints such as transmission line capacities, voltage limits, and generator capabilities. Many inferred or synthetic networks fail this test outright: the topology may appear roughly correct, but other important engineering parameters are not. 

Crucially, this approach moves beyond small benchmark or “toy” networks. In particular, we solve AC-OPF across the entire Eastern Interconnection, spanning 36 states and more than 20,000 buses, derived exclusively from public data sources. This demonstrates that open-data-derived models can produce convergent AC-OPF solutions at a continental scale. 

To be clear, these models are not exact replicas of the operational grid, nor are they intended for market forecasting or real-time operational decision making by power balancing authorities. Electrical parameters are estimated from standard engineering references, parallel circuits are approximated rather than exhaustively enumerated, and demand is allocated using public proxies derived from open data.

The goal is to produce structurally and electrically realistic models that preserve geographic structure and scale from individual states to large multi-region systems using only open data. Full methodological details, validation results, and limitations are described in a companion research paper. 

Why this matters for today’s energy challenges

Access to solvable, geographically grounded grid models unlocks questions that have become increasingly urgent as the energy system evolves, driven by large-scale datacenters, AI workloads, renewable generation, and extreme weather events. We illustrate these capabilities with concrete analyses on models derived from our pipeline.

Where can new transmission physically fit?

Before asking how much new capacity the grid needs, planners must first ask where more wires are even possible. Transmission corridors have a physical limit on how many circuits they can carry: each circuit requires three conductors, and most tower structures accommodate one to three circuits (three to nine conductors). Beyond that, adding capacity typically requires acquiring entirely new rights-of-way – which is expensive, legally complex, and often politically infeasible in urban areas. 

Because our models preserve the geographic structure of real transmission corridors from OpenStreetMap, we can count the number of parallel circuits along each path and visualize where the grid is already physically saturated.

Figure 1. Across the contiguous United States (top), the model identifies 31,488 distinct transmission corridors. The overwhelming majority (27,506) carry a single circuit (green), making parallel lines easier. The roughly 4,000 corridors in orange through red already carry two or more parallel circuits, with the densest packing ten circuits (30 conductors) onto a single path. Zooming into California (bottom), the pattern becomes more discernable. The red corridor north of Sacramento and the orange clusters around the Bay Area and LA basin show where the grid is already physically dense, while the long green radials across the Mojave and into Nevada still have room to grow.

Identifying where the grid is physically boxed in, regardless of generation or demand, is not an optimization problem. It is a spatial feasibility question that geographically grounded models are uniquely positioned to answer.

What if we add capacity where it is needed most?

In dense urban areas, adding new traditional transmission lines is often impractical. The combination of tightly packed buildings, roadways, and complex underground infrastructure leaves little room to establish rights-of-way for high-voltage lines. Alternative power‑transmission solutions are sometimes explored to support urban grid expansion. For example, high-temperature superconducting (HTS) cable systems offer an order-of-magnitude higher ampacity for a given cross-section, enabling the transfer of large amounts of power at lower voltages and simplifying permitting requirements.

Short point-to-point superconducting power links have already been demonstrated in U.S. cities: Columbus, Ohio, Albany, New York, Long Island, New York (decommissioned), and Chicago (operational).

To explore what such connections might accomplish, we modeled two hypothetical HTS links in the Massachusetts grid, each connecting a substation northwest of Boston to load centers closer to the city. We then re-solved AC-OPF and compared the results to the unmodified baseline.

Figure 2. In the baseline (top), one transmission line exceeds its thermal rating (≥100%, dark red) and two more operate above 90%. After adding two HTS links (bottom, dashed lines), every line in the network drops below 90% loading. The energy price falls 42%, from $22.7/MWh to $13.1/MWh, as generation that was previously bottlenecked behind constrained corridors becomes deliverable.

This is precisely the kind of insight that publicly available price data cannot provide. Wholesale electricity prices reflect whether congestion exists, but not how close the system is to congestion nor how power flows change when new assets are added. A line operating at 95% of its thermal limit and one at 50% look identical in market data – until one of them reaches capacity. Physics-based models expose that margin directly, making it possible to evaluate interventions before they are built. 

Where should new demand go?

Rapid growth in electricity demand raises a question that existing market signals answer poorly: where on the network can new consumption be absorbed without triggering congestion?

Wholesale electricity prices reflect marginal generation costs, current congestion patterns in the transmission grid, and transmission losses, which are typically small – but they do not capture how close the system is to its limits. Siting decisions based solely on price therefore miss the physical margin that determines whether new demand can be served without infrastructure upgrades.

To illustrate this, we placed the same hypothetical 500 MW datacenter at two locations in the Maryland grid and re-solved AC-OPF for each (locations were chosen arbitrarily and do not reflect Microsoft’s datacenter portfolio or expansion plans). The two sites are plausible alternatives from a market perspective, with similar population density, comparable electricity prices, and proximity to major load centers:

• Site A (Baltimore area): a substation in the Baltimore metropolitan region, near an existing generation complex and dense transmission infrastructure
• Site B (Washington, DC suburbs): a substation in Montgomery County, serving a similarly dense suburban area within the Washington–Baltimore corridor

Despite these similarities, the physical outcomes differ. Adding the datacenter at Site A pushes a nearby transmission line into thermal overload, while placing the same load at Site B is absorbed by the existing network without violating line limits. The two sites are less than 50 miles apart, yet one would require transmission reinforcement and the other would not.

Figure 3. Placing the datacenter near Baltimore (top) pushes one transmission line into overload (≥100%) and raises the energy price from $24.6/MWh (baseline) to $28.6/MWh (+16.1%). The same load placed near the DC suburbs (bottom) keeps all lines below 95% and raises the price to $26.4/MWh (+7.4%). The Baltimore site yields a price $2.1/MWh higher – a difference that, across the 500 MW load, amounts to roughly $9,100 per hour or ~$80 million per year.

This distinction – largely invisible in price data – emerges directly from a more direct first-principle transmission-level power flow analysis. It highlights why geographically grounded, physics-based models are necessary for demand-siting decisions in a stressed grid.

Looking ahead

This work shows that it is possible to study transmission-level grid behavior at realistic scales without access to restricted infrastructure data. By grounding models in real geography and making uncertainty explicit, open-data-derived grids can support analyses that are difficult or impossible with small benchmarks or purely synthetic networks.

While the examples here focus on the United States, the approach generalizes to other regions where comparable open data is available. More broadly, we see this capability as an enabling layer: a way to improve the study of congestion, feasibility, and system stress – whether for planning studies, scenario analysis, or data-driven methods that require realistic grid structure.

We are releasing an open dataset of grid models spanning 48 U.S. states and six multi-state interconnections, ranging from small systems with tens of buses to continental-scale networks. All models can be solved under AC-OPF, with controlled relaxations applied when necessary to account for uncertainty in open data inputs. These models are solved for both peak and off-peak demand conditions, enabling consistent analysis across a range of operating scenarios.

This post is the first in a two-part series. In the second post, we introduce GridSFM, a learning-based AC-OPF surrogate trained on these grid models. We show how it predicts a full AC operating point in milliseconds, classifies feasibility for fast screening at planning scale, and serves as a warm-start seed that accelerates downstream numerical solvers.

GitHub Hugging Face Opens in a new tab

The post Building realistic electric transmission grid dataset at scale: a pipeline from open dataset appeared first on Microsoft Research.

Subaru’s rough 2026 isn’t slowing down. After posting sales declines through the first quarter, April’s numbers show the Japanese automaker is still struggling to regain momentum. Nearly every major model in the lineup is down year-over-year, and the brand has now sold almost 30,000 fewer vehicles in 2026 than it had at this point last year.

Award season may not be a year-round celebration, but that doesn't mean your watch list cannot get in on the celebrations every day. Netflix's catalog of award-winning films, shows, and documentaries gives you several options to pick from when you sit down for a cozy watch.

MiniDisc is one of the most under-appreciated audio formats of all time. It combined the digital benefits of a CD with the mix tape abilities of a cassette in a pocketable package.

When it comes to PCs, few things can ruin your day as much as when things just don't work. PC-related problems lead to hours of troubleshooting, frantic googling, and frustrated muttering under your breath. I've been there.

Using Google Maps for navigation is great. It combines live traffic updates, changing routes, and voice commands all from my phone. However, the heavy demands of constant GPS pings, ongoing data streaming, and a bright screen drain even large batteries very quickly. However, you can make a quick change to a minor setting to see a major benefit.

While I enjoy a good superhero show, I adore those that are satirical in nature. Nothing beats a good laugh. Luckily, Amazon Prime Video is home to several acclaimed satirical superhero series, and they each function in hearty ways that deconstruct the genre piece by piece.

Intel has reportedly reached a deal to manufacture Apple chips just days after rumors emerged of ongoing talks, and the consequences could be profound even if you're an avid Windows PC user.

Disney is apparently looking to create the only app Disney fans will ever need for the rest of their lives.

Bloomberg reported that new Disney CEO Josh D'Amaro wants to create a sort of "super app" that would blend the streaming functionality of Disney+ with other apps meant for real-life experiences, like Disney Cruise Line Navigator. The idea would be to put Disney's very important theme park, resort, and cruise line businesses in front of more eyeballs than usual, though at this stage, it's not entirely clear if this would mostly manifest as advertisements or a deeper layer of app functionality.

SEE ALSO: The best Disney+ deals and bundles in April 2026

“Disney+ becomes the primary relationship between Disney and its fans, the place where everything comes together,” D'Amaro said in an earnings call this week.

There are pros and cons to this, just like anything else.

On one hand, if you're a real Disney-head, it would probably be more convenient to use the same app to watch The Mandalorian and book a trip to Orlando than the way things currently work. On the other hand, there are probably a lot of people (myself included) who like to occasionally watch things on Disney+, but don't have any real interest in Disney's cruise line or theme parks. For that audience, this could get a little annoying or unwieldy.

At any rate, it sounds like this is still a very early plan, so it might take a while to happen, or it might not happen at all. Maybe by the time it comes around, the vibe around cruise ships will be better than it is right now.

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Own an old Moto Android phone but don’t plan to give it away or sell it? Instead of keeping it in some dim, dusty drawer and pulling it out every few months to check whether its battery has turned into a spicy pillow, you can repurpose it into something useful and keep using it on a daily basis.

That extra Ethernet port on the back of your motherboard is one of the most underrated bits of hardware on a modern PC. Most people glance at it once during the build, plug a cable into the other one, and forget it exists for the rest of the system's life. I did just the same thing, never caring for it much.

By the end of the week, I totally get the appeal of just turning your brain off and watching a mindless episode of Too Hot to Handle. But sometimes the most restorative weekends come by adding a bit of real-life perspective to your gray matter, with a good documentary. Luckily, HBO Max has some of the best quality ones around, and I've got a few suggestions below.

The luxury compact SUV segment looks different today than it did in 2003. When the BMW X3 first arrived, it essentially defined the category by proving an SUV (or crossover) could handle like a sporty sedan. The X3 has been a benchmark for over two decades, but the market is shifting. Buyers are moving away from luxury for luxury's sake and are, instead, looking for a vehicle that prioritizes everyday functionality and long-term value.

The weekend is the best time to actually sit down and mess with your Linux setup. This time, I have for you a selection of three apps that are aimed at improving your quality of life and using Linux that much more convenient. Each app solves a different kind of friction you've probably just accepted as part of your workflow.

SAVE 20 CENTS PER GALLON: Amazon Prime members can save up to 20 cents a gallon at BP and Amoco on Fridays. Here’s how to claim your fuel discount.

Opens in a new window Credit: Amazon Save up to 20 cents a gallon at BP and Amoco on Fridays   Learn More

It's easy to forget all the benefits you get with Amazon Prime. Like, I somehow always forget that prescription and gas discounts are included with a membership. And, as the proud owner of a V-8 GMC Sierra, that's the kind of information I need to keep in the "relevant" file. I've literally seen regular gas (not even premium) as high as $4.30 per gallon in North Carolina, which is ridiculous. So, whenever there's a way to make filling up this truck even slightly cheaper, I'm all over it.

SEE ALSO: Amazon Prime members can save $5 on their next Grubhub delivery of $15 — here's how

If you have Amazon Prime and you aren't using its fuel discount yet, you're basically throwing money away. By linking your Prime account to BP's "earnify" app (which is completely free to set up), you get a flat 10 cents off per gallon every single time you fill up at a participating BP, Amoco, ampm, or Thorntons location. There's no cap on how many gallons you can buy, and it works on all fuel grades. You don't even have to open the app at the pump — you just punch in your phone number, and it automatically applies the discount. (One less app to deal with, hallelujah.)

Even better, Amazon's running a "Fuel Up Friday" promo right now through May 29 that doubles the savings. If you time your fill-ups for Fridays, you get 20 cents off per gallon (valid once every Friday during the promo window).

ShinyHunters apparently isn't done with edutech giant Instructure.

The now-infamous hacking and extortion collective known as ShinyHunters has once again breached Instructure, the education technology company best known for its popular Learning Management System (LMS) application Canvas. ShinyHunters originally breached Instructure's systems just over a week ago, stealing data connected with nearly 9,000 schools worldwide.

According to a report from TechCrunch, this week, ShinyHunters hackers defaced Canvas login pages for several schools that use the coursework and messaging platform.

TechCrunch says that it saw at least three school login pages compromised with a message via an injected HTML file from ShinyHunters threatening to publicly release stolen data on May 12 unless Instructure agrees to “negotiate a settlement."

SEE ALSO: ShinyHunters breached 'GTA 6' developer Rockstar Games in ransomware attack

Instructure confirmed that it had been breached by the same bad actors responsible for the previously reported breach into the company. This marks a second breach into Instructure, though into a different part of its infrastructure this time.

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Instructure took Canvas offline temporarily while it investigated the second breach. The company says that it found that the hackers "exploited an issue related to our Free-For-Teacher accounts." The company has since temporarily shut down these accounts and restored Canvas access for its users.

Earlier this month, ShinyHunters claimed responsibility for a breach that Instructure later confirmed. According to ShinyHunters, the stolen data linked to the original breach is associated with 275 million Instructure users and affects 8,809 schools worldwide. The stolen data belongs to students, teachers, and school staff who use Instructure's products and contains users' names, email addresses, student IDs, and private messages exchanged on the Canvas platform.

The request from ShinyHunters to "negotiate a settlement" has become par the course for the group, which actively seeks to profit from its excursions.

Over the past year, ShinyHunters have claimed responsibility for data breaches at companies such as Panera Bread, Crunchyroll, Bumble, ADT, and Rockstar Games, among others.

One of the biggest advantages of turning a laptop into a NAS is that you get to fully reuse its internals, including the built-in battery. In the event of a power outage, that battery can keep the system running until electricity returns, effectively serving as a mini-UPS. This allows zero downtime and no need to reset or reconfigure anything, which is especially useful if your NAS is in a hard-to-reach spot like mine.