One Of World’s Largest Floating Solar PV Power Projects Completed In Singapore
I recall when floating solar PV power plants popped onto the scene at some point in the past decade. On the one hand, the idea was so funny and fanciful that it seemed unrealistic. On the other hand, there appeared to be a lot of benefits to the approach — cooler surfaces (which help with solar panel efficiency, approx. 5–15%), fairly simple installation, no need to compete with other sectors for land use, no concern of shade, large and predictable spaces. The latter hand has indeed been winning out, as the floating solar PV market has been growing larger and larger.
The latest news of a large floating solar PV power project comes out of Singapore, a place that knows the challenges of limited land extremely well. The city-state, home to about 6 million people, launched one of the largest floating solar power plants in the world this week. The project will reportedly cover an area equal to 45 football fields! More specifically, but much harder for me to visualize without the previous comparison, the area covered is 45 hectares (111.2 acres). In total, there are 45,000 solar panels spread across the water. The purpose of this solar power plant floating over some good old H2O? Powering Singapore’s 5 water treatment plants, ironically.
Sembcorp Tengeh Floating Solar Farm. Image courtesy of Sembcorp Industries Ltd. View Terms of Use.
That’s not where the fun of new tech used for good ends. Facility operators will use drones to monitor the PV facility. The solar panels are expected to last 25 years, but I would not be surprised to see them go much longer, especially with effective, smart maintenance.
The floating solar power plant is named Sembcorp Tengeh Floating Solar Farm and is located on the Tengeh Reservoir. The project, built by Sembcorp Floating Solar Singapore, a subsidiary of Sembcorp Industries, offers 60 megawatts (MW) of power capacity. A short video of progress to date was published a couple of days ago at the link above. As cool as the concept of floating solar PV power plants is, and as cool as pictures of a large project are, I don’t think the concept or a few pictures compare to watching a video of a large project (even one that’s just 55 seconds long), so I do recommend clicking that link above and watching the production from The Straits Times/Singapore Press Holdings Limited. (No, we don’t have any association with them or get rewarded if you do. I just think the video is super cool.)
Sembcorp Tengeh Floating Solar Farm. Image courtesy of Sembcorp Industries Ltd. View Terms of Use.
For those concerned about the aquatic life under the innovative power plant, have no fear — extensive environmental analyses were conducted, the project is designed to allow adequate sunlight to go through to the plants and animals underneath, and this type of project has been shown to assimilate well with fish, mermaids, and other sea creatures.
Singapore has been sold on floating solar power. Aside from this large project, the city-state has 4 other floating solar projects under construction. I expect more to be announced in the future as well. Overall, Singapore is aiming to quadruple its solar power use by 2025, and let’s be honest, it’s not flush with deserts or underutilized fields — but it is surrounded by a fair bit of water.
Solar power is growing across the world at a fairly fast clip. However, as with almost all things, there are limitations. There are limitations with resources, trained workers, cash money, and time. Therefore, there is always a question of how best to spend money, where to spend it, and what to do after you’ve spent it. How and where should one — whether a person, company, or city-state — invest in solar power to maximize the result?
Clearly, Singapore has decided that floating solar PV projects make a lot of sense for its needs and resources. For anyone else still weighing options. Or, for that matter, for anyone looking to maximize the output from a solar power project already in the ground, I recommend checking out an upcoming solar webinar we’re hosting. Along with HST and a couple of others, we will be exploring how solar project developers can support a larger pipeline of high-quality utility-scale solar projects with the same amount of time and people. We will also be looking at what can maximize project attraction for potential customers. If this sounds interesting to you, you can register for the webinar (it’s free) here.
Featured image courtesy of Sembcorp Industries Ltd. View Terms of Use.
Metro Detroit is about to get a big boost of fast EV chargers, with more than 40 new ChargePoint ports set to come online across multiple sites owned by the Dabaja Brothers Development Group.
The first ultra-fast charging site just opened in Canton, Michigan. It’s owned and operated by Dabaja Brothers, who plan to follow it with additional ChargePoint-equipped locations in Dearborn and Livonia.
“We started this project because we saw a gap in our community – there was almost nowhere to charge an EV in Canton, and a similar lack of charging across metro Detroit,” said Yousef Dabaja, owner/operator at Dabaja Brothers.
Each metro Detroit site will feature ChargePoint Express Plus fast charging stations, which can deliver up to 500 kW to a single port, can fast-charge two vehicles at the same time, and are compatible with all EVs. The stations feature a proprietary cooling system to deliver peak charging speeds for sustained periods, ensuring that charging speed remains consistent.
The stations operate on the new ChargePoint Platform, which enables operators to monitor performance, adjust pricing, troubleshoot issues, and gain real-time insights to keep chargers running smoothly.
Rick Wilmer, CEO at ChargePoint, said, “This initiative will rapidly infill the ‘fast charging deserts’ across the Detroit area, allowing drivers to quickly recharge their vehicles when and where they need to.”
Read more: ChargePoint just gave its EV charging software a major AI upgrade
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Mercedes-Benz High-Power Charging and Starbucks have officially opened their first DC fast charging hub together, off the I-5 in Red Bluff, California.
The 400 kW Mercedes-Benz chargers are capable of adding up to 300 miles in 10 minutes, depending on the EV, and every stall has both NACS and CCS cables – they’re fully open DC fast chargers.
Mercedes-Benz HPC North America, a joint venture between subsidiaries of Mercedes-Benz Group and renewable energy producer MN8 Energy, first announced in July 2024 that it would install DC fast chargers at Starbucks stores along Interstate 5, the main 1,400-mile north-south interstate highway on the US West Coast from Canada to Mexico. Ultimately, Mercedes plans to install fast chargers at 100 Starbucks stores across the US.
Mercedes-Benz HPC opened its first North American charging site at Mercedes-Benz USA’s headquarters in Sandy Springs, Georgia, in November 2023 as part of an initial $1 billion charging network investment. As of the end of 2024, Mercedes had deployed over 150 operational fast chargers in the US, but it hasn’t disclosed an official number of how many chargers are currently online.
Andrew Cornelia, CEO of Mercedes-Benz HPC North America, is leaving the company at the end of the month to become global head of electrification & sustainability at Uber.
Read more: Mercedes-Benz is deploying 400 kW US-made EV fast chargers with CCS and NACS cables
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The race for autonomous driving has three fronts: software, hardware, and regulatory. For years, we’ve watched Tesla try to brute-force its way to “Full Self-Driving (FSD)” with its own custom hardware, while the rest of the automotive industry is increasingly lining up behind NVIDIA.
Now that we know Tesla’s new AI5 chip is delayed and won’t be in vehicles until 2027, it’s worth comparing the two most dominant “self-driving” chips today: Tesla’s latest Hardware 4 (AI4) and NVIDIA’s Drive Thor.
Here’s a table comparing the two chips with the best possible specs I could find. greentheonly’s teardown was particularly useful. If you find things you think are not accurate, please don’t hesitate to reach out:
| Feature / Specification | Tesla AI4 (Hardware 4.0) | NVIDIA Drive Thor (AGX / Jetson) |
|---|---|---|
| Developer / Architect | Tesla (in-house) | NVIDIA |
| Manufacturing Process | Samsung 7nm (7LPP class) | TSMC 4N (custom 5nm class) |
| Release Status | In production (shipping since 2023) | In production since 2025 |
| CPU Architecture | ARM Cortex-A72 (legacy) | ARM Neoverse V3AE (server-grade) |
| CPU Core Count | 20 cores (5× clusters of 4 cores) | 14 cores (Jetson T5000 configuration) |
| AI Performance (INT8) | ~100–150 TOPS (dual-SoC system) | 1,000 TOPS (per chip) |
| AI Performance (FP4) | Not supported / not disclosed | 2,000 TFLOPS (per chip) |
| Neural Processing Unit | 3× custom NPU cores per SoC | Blackwell Tensor Cores + Transformer Engine |
| Memory Type | GDDR6 | LPDDR5X |
| Memory Bus Width | 256-bit | 256-bit |
| Memory Bandwidth | ~384 GB/s | ~273 GB/s |
| Memory Capacity | ~16 GB typical system | Up to 128 GB (Jetson Thor) |
| Power Consumption | Est. 80–100 W (system) | 40 W – 130 W (configurable) |
| Camera Support | 5 MP proprietary Tesla cameras | Scalable, supports 8MP+ and GMSL3 |
| Special Features | Dual-SoC redundancy on one board | Native Transformer Engine, NVLink-C2C |
The most striking difference right off the bat is the manufacturing process. NVIDIA is throwing everything at Drive Thor, using TSMC’s cutting-edge 4N process (a custom 5nm-class node). This allows them to pack in the new Blackwell architecture, which is essentially the same tech powering the world’s most advanced AI data centers.
Tesla, on the other hand, pulled a move that might surprise spec-sheet warriors. Teardowns confirm that AI4 is built on Samsung’s 7nm process. This is mature, reliable, and much cheaper than TSMC’s bleeding-edge nodes.
When you look at the compute power, NVIDIA claims a staggering 2,000 TFLOPS for Thor. But there’s a catch. That number uses FP4 (4-bit floating point) precision, a new format designed specifically for the Transformer models used in generative AI.
Tesla’s AI4 is estimated to hit around 100-150 TOPS (INT8) across its dual-SoC redundant system. On paper, it looks like a slaughter, but Tesla made a very specific engineering trade-off that tells us exactly what was bottling up their software: memory bandwidth.
Tesla switched from LPDDR4 in HW3 to GDDR6 in HW4, the same power-hungry memory you find in gaming graphics cards (GPUs). This gives AI4 a massive memory bandwidth of approximately 384 GB/s, compared to Thor’s 273 GB/s (on the single-chip Jetson config) using LPDDR5X.
This suggests Tesla’s vision-only approach, which ingests massive amounts of raw video from high-res cameras, was starving for data.
Based on Elon Musk’s comments that Tesla’s AI5 chip will have 5x the memory bandwidth, it sounds like it might still be Tesla’s bottleneck.
Here is where Tesla’s cost-cutting really shows. AI4 is still running on ARM Cortex-A72 cores, an architecture that is nearly a decade old. They bumped the core count to 20, but it’s still old tech.
NVIDIA Thor, meanwhile, uses the ARM Neoverse V3AE, a server-grade CPU explicitly designed for the modern software-defined vehicle. This allows Thor to run not just the autonomous driving stack, but the entire infotainment system, dashboard, and potentially even an in-car AI assistant, all on one chip.
Thor has found many takers, especially among Tesla EV competitors such as BYD, Zeekr, Lucid, Xiaomi, and many more.
Electrek’s Take
There’s one thing that is not in there: price. I would assume that Tesla wins on that front, and that’s a big part of the project. Tesla developed a chip that didn’t exist, and that it needed.
It was an impressive feat, but it doesn’t make Tesla an incredible leader in silicon for self-driving.
Tesla is maxing out AI4. It now uses both chips, making it less likely to achieve the redundancy levels you need to deliver level 4-5 autonomy.
Meanwhile, we don’t have a solution for HW3 yet and AI5 is apparently not coming to save the day until 2027.
By then, there will likely be millions of vehicles on the road with NVIDIA Thor processors.
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