Upgrading Solar Farms With New Technology

I am happy to share that the latest paper based on my PhD thesis at MIT was recently published in the Journal "Small" for micro-nano applications (Impact Factor: 13). Credits to my co-author Fabian Dickhardt and advisor Kripa Varanasi. Dust accumulation on solar panels is the single biggest problem that large-scale solar farms are facing. Removing dust using water-based cleaning is expensive and unsustainable. One of my earlier papers published in Science Advances showed that dust repulsion via charge induction is an efficient way to clean solar panels without consuming a single drop of water. However, it was still challenging to remove particles of ≈30 μm and smaller because the Van der Waals force of adhesion dominates the electrostatic force of repulsion. In the current paper titled "Enhanced Electrostatic Dust Removal from Solar Panels Using Transparent Conductive Nano-Textured Surfaces," we propose nano-textured, transparent, electrically conductive glass surfaces to significantly enhance electrostatic dust removal for particles smaller than ≈30 μm. Nano-textured surfaces reduce the force of adhesion by up to 2 orders of magnitude compared to un-textured surfaces from 460nN to 8.6 nN. The reduced adhesion on nano-textured surfaces results in significantly better dust removal of small particles compared to non-textured or micro-textured surfaces, reducing the surface coverage from 35% to 10%. We fabricate transparent, electrically conductive, nano-textured glass that can be retrofitted on solar panel surfaces using copper nano-mask-based scalable nano-fabrication technique and shows that 90% of lost power output for particles smaller than ≈10 μm can be recovered. We are hoping that this work takes us one step closer to the sustainable operation of solar farms. Large-scale field trials are still going on before we deploy this technology or a modified version of this on full-scale solar farms. You can read the paper here: https://lnkd.in/gUEqMZ4M MIT had published a 3-minute video on my work on their YouTube channel. You can check that here: https://lnkd.in/gGYNJa8D

Turbines are offline longer than expected. Solar strings are underperforming, but it's hard to locate the issue. Rising O&M costs are eating into margins. Safety incidents from risky inspections. These aren’t “operational headaches” — they’re profit leaks. And most of them come from how we inspect. The Traditional Model (Pain / Loss Aversion) • Rope access, cherry-pickers, helicopters, boots on the ground. • Costly: labor + equipment rentals stack up quickly. • Slow: 1–2 turbines/day or weeks to cover a solar farm. • Risky: technicians exposed to heights, heat, and accidents. • Blind spots: issues are often missed until they become revenue-draining failures. 👉 Every extra day a turbine is down = thousands in lost generation. 👉 Every safety incident = higher insurance + regulatory headaches. 👉 Every missed defect = compounding performance loss. The Drone Model (Relief + Opportunity) • Speed: 4 turbines/day vs 1–2. Large solar farms mapped in hours, not weeks. • Cost: up to 70% reduction in inspection costs. • Safety: fewer people at height or in confined spaces. • Data Quality: thermal + RGB + LiDAR → early fault detection, predictive maintenance. • Business Impact: faster repairs, less downtime, higher energy yield. Translation for decision-makers: • Lower O&M line item + avoided revenue loss. • Streamlined, repeatable inspections that scale. • Actionable insights, not just raw images. • “Every day you rely on traditional inspections, you’re leaving megawatts (and revenue) on the table.” • “NREL validated drone-based thermography as a proven method to directly tie defects to performance loss.” • “Utilities and IPPs adopting drone inspections are reporting 30–60% O&M savings and faster ROI.”   • “Start with one pilot project → measure cost + downtime savings → scale to fleet.” Clean energy is about efficiency and sustainability. Yet if we’re still using inspection methods from 1995, we’re paying 2025 prices for 1995 performance. Drones aren’t just new tech, they’re about protecting revenue, reducing risk, and scaling clean energy faster. If your next quarterly O&M review showed a 40% cost reduction and 50% less downtime, how would that change your project pipeline? 👉 If so, send me a DM to explore your project. #cleanenergy #drones #renewables #assetmanagement #OandM #predictivemaintenance

How one solar tech leap equals millions in savings—and a smarter energy future. U.S. power demand is surging—up 16% in just 5 years—and solar must scale smarter to keep up. 💡 This chart says it all (swipe video ⬇️): By upgrading from standard silicon panels (21.5% efficiency) to tandem perovskite-silicon (27% efficiency), developers unlock: 🔹 +26% more output (from 300 MW to 377 MW) 🔹 –$152/kW in installed cost savings 🔹 –$24/kW in lifetime operating costs Let’s put that in real-world terms: For a typical 100 MW utility-scale solar farm, that’s $15.2 million saved up front. Add another $2.4 million in long-term O&M savings over 20 years. All without using a single extra acre of land. That’s enough to: ✔️ Repower older plants and stay under budget ✔️ Accelerate ROI for developers ✔️ Expand solar access in tight or urbanized regions ✔️ Reduce strain on interconnection queues and land acquisition At We Recycle Solar, we’re working at the intersection of this transformation—helping repower aging assets with next-gen modules and recycle the legacy ones to close the loop. This is how we scale clean power—faster, cheaper, smarter. U.S. Department of Energy (DOE) National Renewable Energy Laboratory Caelux®

Robots are starting to reshape the installation of solar panels. Chinese company Leapting recently rolled out its AI-controlled robot in Australia for its first commercial deployment — installing 10,000 panels at Neoen’s Culcairn solar farm in NSW. It makes a lot of sense. The largest solar farms have over a million panels, each weighing around 30 kg and requiring 3-4 people to handle. This translates to an installation rate of about 100 panels per 8-hour day. By comparison, Leapting says its robot can install 3-5x as many, at an average rate of 60 modules an hour. As well as the sheer scale of the work involved, large scale solar farms are often located in remote areas with harsh construction environments and strong sunlight, not to mention the heat in countries like Australia. Leapting hopes the use of robots will help address worker shortages and reduce the amount of downtime due to injury. The robot itself consists of a 2.5m high robotic arm mounted on a self-guided and self-propelled crawler. It has its own navigation system, uses visual recognition to adapt to different terrain, and multimodal sensors ensure each panel goes in the right place. Next up, Leapting will deploy this robot and several others to another solar farm in Australia, where together they will install half a million panels. And Leapting isn’t alone — many other companies are exploring the use of robots to speed up solar module installations. Expect to see a lot more of this in the coming years. Video credit: Leapting #energy #renewables #energytransition

☀️💡 A Clean Win for Solar Energy: Robots Are Doing the Dirty Work! 🤖🌍 Dust blocks sunlight. Less sunlight = less power. In massive solar farms, cleaning panels by hand wastes water, time, and money. Now there’s a smarter solution: solar-powered robotic cleaners that keep panels spotless—no water, no humans, no downtime. 🛠️ How It Works: These AI-powered bots glide across the panels daily, removing dust and debris. They're powered by solar energy and work day or night, automatically. 🌱 Why It Matters: ✅ Saves water (critical in dry regions) ✅ Reduces maintenance costs ✅ Boosts power output ✅ Uses zero fossil fuels ✅ Works without manual labor ⚡ Cleaner panels = more electricity + longer lifespan. It’s not just smart—it’s sustainable. 💬 Would you trust robots to maintain your solar panels? Let’s talk tech that makes clean energy even cleaner. Drop your thoughts below! 👇 ➕ Follow me if you love breakthroughs in renewable tech and climate-smart solutions! 🚀 #SolarTech #CleanInnovation #GreenRobots #SmartEnergy #SolarPower #AutomationInEnergy #WaterlessCleaning #EcoSmart #SustainableSolutions #TechForThePlanet #FutureIsBright #RenewableEnergy

While many continue to talk about AI, we are already deploying it at scale and across industries, from deep tech and manufacturing to industrial optimization and consumer applications. One of our latest real-world implementations: an AI-powered solution to boost solar power plant efficiency is much more than a technical upgrade—it’s a strategic leap for energy companies, OEMs, and investors focused on scaling the next generation of sustainable infrastructure. This AI-driven approach not only maximizes power utilization but also enhances system predictability and maintenance. Traditionally, solar power systems relied on basic P&O algorithms to manage efficiency. Now, by integrating real-time AI algorithms into Infineon Technologies’ PSOC™ Edge platform, we can: • Maintain optimal energy output under shifting conditions (irradiance, temperature, etc.) • Dynamically tune converter duty cycles for maximum power point (MPP) tracking • Reduce energy waste, enhance predictive maintenance, and boost ROI Here’s how it works: https://bit.ly/42Iqb4R #AIFirst #Energy #RenewableEnergy #SolarEnergy #EngineeringTheBetterFuture

-- Why O&M Managers Need AI and Drone Technology for Solar Farms -- 𝗪𝗛𝗬 𝗔𝗜? 𝗪𝗛𝗬 𝗗𝗥𝗢𝗡𝗘𝗦? Solar farms are massive, complex, and constantly under threat from soiling. Relying on manual inspections or basic monitoring systems can only take you so far. If you’re serious about recovering lost revenue and maximizing efficiency, you need precision insights powered by the best technology. 𝗛𝗘𝗥𝗘’𝗦 𝗪𝗛𝗬 𝗪𝗘 𝗖𝗛𝗢𝗦𝗘 𝗔𝗜 + 𝗗𝗥𝗢𝗡𝗘𝗦: 🚁 Why Drones? 1️⃣ Full Coverage in Hours Manual inspections take days—or even weeks. Drones scan entire arrays in a fraction of the time, delivering faster, more accurate results. 2️⃣ Non-Disruptive Surveys Our drones collect data while your panels stay online, ensuring no downtime or revenue losses during inspections. 3️⃣ High-Resolution Imaging Equipped with thermal cameras, drones detect temperature anomalies (hotspots) caused by soiling. RGB cameras capture visible debris like bird droppings, pollen, and dust, leaving nothing to guesswork. 🤖 Why AI? 1️⃣ Precision Analytics AI doesn’t just see soiling—it measures its impact. We calculate energy losses down to the panel level and predict how much revenue you’ll recover by acting. 2️⃣ Pattern Detection AI identifies trends in soiling buildup over time, helping you understand your site’s unique challenges and prepare for them. 3️⃣ Tailored Cleaning Triggers Instead of static cleaning schedules, AI tells you when soiling has reached a critical point—ensuring cleaning is done only when and where it’s truly needed. 𝗧𝗛𝗘 𝗗𝗜𝗙𝗙𝗘𝗥𝗘𝗡𝗖𝗘 𝗧𝗛𝗜𝗦 𝗠𝗔𝗞𝗘𝗦 𝗧𝗢 𝗢&𝗠 𝗠𝗔𝗡𝗔𝗚𝗘𝗥𝗦 ↬ Fewer Unknowns: Data-driven insights eliminate guesswork, so you can make informed decisions. ↬ Higher ROI: Cleaning at the right time maximizes energy recovery and justifies every maintenance dollar. ↬ Confidence for Asset Owners: Detailed reports show the ROI of your actions, building trust and transparency. Ha - you know how they say "Better Ingredients...Better Pizza...Papa Johns"? 𝗖𝗟𝗘𝗔𝗡𝗘𝗥 𝗗𝗔𝗧𝗔. 𝗕𝗘𝗧𝗧𝗘𝗥 𝗗𝗘𝗖𝗜𝗦𝗜𝗢𝗡𝗦. Solar Survey Ai.