Another week has flown by, and it’s time to review and reflect on the top cleantech stories of the week. Here’s a hint: it’s about batteries, batteries, batteries. And also a bit of solar, a bit of fossil fuel war, and a bit of EV stuff. Let’s take a stroll. ... [continued]

The post New BLUETTI Fridge Storage System, EV Battery Innovation Updates — Top Stories of the Week appeared first on CleanTechnica.

PPC Ltd has launched two solar power plants in South Africa, achieving a total capacity of 20 megawatts. These facilities will supply clean energy directly to PPC’s cement manufacturing units, mitigating reliance on Eskom. The initiative will cut carbon emissions by over 50,000 tonnes annually, aligning with sustainability goals and enhancing energy reliability.

The post PPC Commissions 20 MW Solar Plants To Power Cement Operations In South Africa appeared first on SolarQuarter.

The National Electric Energy Agency (ANEEL) has authorized the integration of a co-located energy storage system at the Sol de Brotas 7 photovoltaic plant in Bahia, Brazil. This represents a significant development in Brazil’s energy landscape, enhancing renewable energy management and grid reliability while fostering regulatory modernization for energy storage technologies.

The post ANEEL Grants First Authorization for Co-Located Energy Storage System at Sol de Brotas 7 Solar Plant in Brazil appeared first on SolarQuarter.

Renewable energy platform Resolven has secured refinancing worth ₹450 crore for its 136 MWp operational portfolio spread across Telangana and Karnataka, marking a strategic move to strengthen its financial position […]

The post Resolven Raises ₹450 Cr from NIIF IFL to Refinance 136 MW Renewable Assets, Cuts Financing Costs appeared first on SolarQuarter.

Aurobindo Pharma plans to acquire a 26% stake in Swarnaakshu Solar Power to secure renewable energy for its operations. This investment aims to develop a solar project for internal electricity use, enhancing cost efficiency and sustainability. The deal aligns with India’s regulations for captive power generation and emphasizes the industry's shift toward renewable solutions.

The post Aurobindo Pharma to Acquire 26% Stake in Swarnaakshu Solar Power for Captive Renewable Energy Project appeared first on SolarQuarter.

Union Minister Shripad Yesso Naik inaugurated ECAMEX 2026, emphasizing renewable energy's role in India's future. He urged increased solar energy adoption and domestic manufacturing to meet electricity demands and reduce carbon intensity. The event, uniting industry stakeholders, highlighted collaboration as essential for advancing India’s clean energy goals and strengthening local production capabilities.

The post Shri Shripad Naik Highlights Solar Growth and Domestic Manufacturing at ECAMEX 2026 appeared first on SolarQuarter.

Power Grid Corporation of India Limited has won a bid for an inter-state transmission project to enhance India's power infrastructure. The project aims to integrate 2.7 GW of renewable energy and involves constructing a 400 kV transmission line in Karnataka. It will be managed under the BOOT model, ensuring grid stability and supporting clean energy goals.

The post POWERGRID Wins Tumkur-II Transmission Project To Integrate 2.7 GW Renewable Energy appeared first on SolarQuarter.

Adani Power Limited has secured a long-term contract to supply 2,500 MW of Renewable Energy Round-the-Clock (RE RTC) power to Maharashtra State Electricity Distribution Company Limited for 25 years. This contract, awarded after a successful electronic auction, will enhance the state's renewable energy capacity and supports India's transition to sustainable power sources.

The post Adani Power Secures 2,500 MW RE RTC Supply Deal With MSEDCL appeared first on SolarQuarter.

Citicore Renewable Energy Corporation has energized the 69 MWp Citicore Solar Negros Occidental 2 Solar Power Plant, enhancing the Visayas grid's supply ahead of summer. This project supports the company’s "5GW in 5 years" goal and promotes regional energy security, while also expanding agricultural initiatives under solar panels to boost local food security.

The post Citicore Energizes 69 MWp Solar Power Plant in Negros Occidental to Support Visayas Grid appeared first on SolarQuarter.

Oyster Renewable has partly commissioned its 315.6 MW solar-wind hybrid project in Agar-Malwa, Madhya Pradesh, for Jindal Stainless Limited. This self-developed project combines solar and wind technologies to provide a stable, efficient power supply, enhancing renewable energy adoption and supporting industrial growth in India’s clean energy transition.

The post Oyster Renewable Part-Commissions 315.6 MW Solar-Wind Hybrid Project for Jindal Stainless in Madhya Pradesh appeared first on SolarQuarter.

The Uttar Pradesh Electricity Regulatory Commission dismissed a petition from UPPCL regarding a solar energy agreement after allowing withdrawal. The case, tied to a Supplementary Power Purchase Agreement with Vibhuti Infraprojects, revealed issues in signing authority. UPPCL plans to correct these issues and resubmit for approval.

The post UPERC Dismisses UPPCL Petition On Solar PPA, Allows Withdrawal For Legal Correction In Uttar Pradesh appeared first on SolarQuarter.

Researchers in Moroco analyzed cybersecurity challenges in smart grids, highlighting AI-driven detection and defense strategies against threats like distributed denial-of-service, false data injection replay, and IoT-based attacks. They recommend multi-layered protections, real-time anomaly detection, secure IoT devices, and staff training to enhance resilience and safeguard power system operations.

Researchers at Morocco's Higher School of Technology, Moulay Ismail University, have conducted a comprehensive analysis of emerging cybersecurity challenges in power systems and detailed recent advances in detection and defense strategies.

Their work emphasizes the growing role of AI in enhancing control, protection, and resilience in modern smart grids. It also classifies cyber threats by origin, impact, and affected system layers to provide a structured understanding and reviews machine learning and optimization-based intrusion detection systems (IDSs) for power systems.

The researchers highlighted that renewable smart grids face diverse cyber threats that can disrupt operations and compromise data. Distributed denial-of-service (DDoS) attacks, for example, flood networks with traffic, blocking legitimate access and delaying control actions, while data integrity attacks manipulate sensor or control data, causing incorrect decisions or blackouts.

Additionally, replay attacks retransmit intercepted data to confuse the system, and false data injection attacks subtly alter real-time data to mimic normal operations while disrupting the grid. Covert attacks inject hidden signals that manipulate system behavior without detection, whereas IoT device-based attacks exploit vulnerabilities in meters or sensors to spread malware, steal data, or launch DoS attacks.

Finally, zero dynamics attacks leverage system models to generate hidden signals that leave output measurements unchanged but affect operations, posing sophisticated stealth threats to smart grid security.

Join us on Apr. 29 for pv magazine Webinar+ | Decoding the first massive cyberattack on Europe’s solar energy infrastructure – The Poland case and lessons learned

The researchers warned that while smart grids have improved energy efficiency and flexibility through advanced communication tools and distributed energy sources, they have also introduced new cyber vulnerabilities. Threats such as phishing, malware, denial-of-service (DoS) attacks, and false data injection (FDI) can disrupt operations, compromise data, and damage infrastructure.

They recommend implementing defense strategies that maintain confidentiality, integrity, and availability, while also incorporating authentication, authorization, privacy, and reliability. Machine learning and data-driven intrusion detection systems can help identify anomalies and detect FDI attacks in real time, particularly in smart grids and industrial control systems such as SCADA, which rely on accurate sensor measurements for state estimation.

The research team also encouraged energy asset owners and grid operators to adopt substation security measures and protocol vulnerability analyses to detect risks at the hardware and network levels. Blockchain, distributed ledgers, and Hilbert-Huang transform methods are highlighted as tools to further strengthen cybersecurity.

IoT devices, including sensors and smart meters, should be secured with strong authentication, safe boot procedures, frequent firmware updates, and standardized security across manufacturers. Sensitive grid data should be protected using techniques such as homomorphic encryption to maintain confidentiality during storage and transmission.

“A multi-tiered security approach that includes firewalls, intrusion detection systems, and network segmentation can enhance grid resilience. Extracting critical elements from vulnerable IoT devices and leveraging redundant control channels ensures operational continuity during attacks,” the researchers stated.

Machine learning and anomaly detection systems should be deployed to enable real-time identification of irregular activities, including FDI and malware propagation. Standardized protocols and rapid incident response measures should also support collaboration among grid operators, IoT manufacturers, and regulators, facilitated by information-sharing platforms.

The researchers emphasize that human-centered attacks, including phishing and social engineering, remain significant threats, but these can be mitigated through regular staff and user training.

The review was presented in “Cybersecurity challenges and defense strategies for next-generation power systems,” published in Cyber-Physical Energy Systems.

A UNSW-led team found that annealing conditions significantly affect stress, strain, and microstructure in copper-plated heterojunction solar cell contacts, with fast annealing increasing microstrain in both copper and indium tin oxide.

A team of scientists led by Australia's University of New South Wales (UNSW) has studied how stress and strain evolve in copper (Cu)-plated contacts on heterojunction (HJT) solar cells under various annealing conditions. Their work specifically examined how annealing affects the material properties of Cu, indium tin oxide (ITO), and silicon (Si).

“We applied multiple characterization methods to understand how annealing conditions influence stress and strain in Cu-plated HJT cells,” co-author Pei-Chieh Hsiao told pv magazine. “Our results show that Cu contacts on HJT cells need careful assessment to balance adhesion with mechanical integrity.”

Hsiao highlighted the importance of controlling the microscopic structure of copper contacts to limit mechanical stress in HJT solar cells. “Ideally, plated Cu with a low defect density and (100) crystal texture is preferred,” he explained. “This reduces stress in Si after annealing because of a lower Young’s modulus. The preferred texture can be achieved by adjusting the electrolyte or plating parameters, and annealing can then be optimized to minimize thermal strain while preserving the (100) orientation.”

The team began with silicon heterojunction G12 half-cut n-type precursors measuring 210 mm × 105 mm. The cells were coated with a resin-based mask to restrict copper plating, with selective openings created via a collimated light source. Copper was then plated onto the exposed ITO surface using an acid-based electroplating solution at a current density of 42 mA/cm².

The team compared three annealing methods. In self-annealing, samples were stored at room temperature in a low-humidity environment. Fast annealing (same day) was carried out in compressed dry air at 205 ± 5 C for 45 seconds under approximately 15 suns of illumination. Fast annealing (next day) used the same conditions but was performed roughly 24 hours after plating.

“Due to the limitation of low temperature processing of HJT cells, fast annealing was performed at 200 C, which is lower than the grain growth stage at over 250 C,” Hsiao said. “It means that annealing of plated Cu contacts on HJT cells would perform distinctly from that on PERC or TOPCon cells, where higher annealing temperatures are permitted and improved contact adhesion has been demonstrated.”

The team then examined the samples in a series of tests. First, nanoindentation was used to measure the mechanical strength and stiffness of the plated copper. Second, X-ray diffraction (XRD) was used to examine the crystal structure of the copper and the underlying ITO layer. Finally, Raman spectroscopy was used to map the mechanical stress induced by the copper contacts in the silicon, especially near the contact edges.

The analysis showed that no significant differences were found in yield strength or plastic response of plated Cu, which was consistent with the comparable Cu grain size. Moreover, XRD patterns showed fast annealing reduced the Cu lattice parameter and promoted grain growth in the Cu (200) crystallographic orientation, while simultaneously increasing the ITO lattice parameter and full width at half maximum (FWHM).

As a result, microstrains in both Cu and ITO rose under rapid annealing, with the scientists noting that Raman spectroscopy revealed approximately 2 μm-wide regions of high local stress in the silicon along the plated Cu fingers, with stress being lower in self-annealed Cu and higher in fast-annealed Cu.

These results indicate that minimizing defects and promoting a preferential (100) texture in plated Cu can reduce stress transfer to Si and ITO. Maintaining uniform plating conditions and careful surface preparation are also essential for achieving optimal texture and adhesion. Overall, self-annealing is preferred when comparable contact adhesion can be achieved, as it preserves the (100) orientation and minimizes thermal strain.

The research work was described in “Stress and strain analysis of Cu plated contacts on HJT cells under different annealing conditions,” published in Solar Energy Materials and Solar Cells. Scientists from Australia's University of New South Wales and technology company SunDrive Solar have contributed to the research.

In early January, a research team from UNSW and Chinese-Canadian solar module maker Canadian Solar investigated how HJT solar cells are hit by sodium (Na) and moisture degradation under accelerated damp-heat testing and has found that most degradation modes predominantly affect the cells themselves, making cell-level testing the preferred approach.

A month later, another UNSW team assessed the impact of soldering flux on HJT solar cells and found that the composition of this component is key to prevent major cracks and significant peeling.

Spanish researchers found that semi-transparent silicon PV greenhouses boosted tomato fruit weight by 25% while generating 726.8 kWh over two seasons, outperforming cadmium telluride PV and shaded controls. The PV-Si system balanced sunlight, temperature, and energy, showing strong agrivoltaic potential.

Researchers led by Spain’s Murcian Institute for Agricultural and Environmental Research and Development (IMIDA) have evaluated the impact of different agrivoltaic system designs on tomato crops to determine the level of shading that benefits the plants most.

“The use of four independent, identical greenhouses enables a robust assessment of their respective impacts on microclimate, crop performance, and energy generation,” the team said. “Specifically, the study aimed to evaluate the agronomic and energy performance of two commercially available semi-transparent PV technologies, with distinct light transmission patterns, in comparison with control and shading-net treatments.”

The researchers tested a semi-transparent monocrystalline silicon (PV-Si) greenhouse and a cadmium telluride thin-film (PV-TF) greenhouse against a control greenhouse and one with a shading net.

The study took place in Murcia, Spain, over two tomato-growing seasons: a 120-day winter-spring season from December 2023 to April 2024, and a 98-day spring-summer season from April to July 2024. Murcia’s semi-arid Mediterranean climate features average summer and winter temperatures of 30 C and 12 C, respectively. In both seasons, the team used polyethylene greenhouses measuring 3.9 m long × 2 m wide × 3.1 m high.

Materials under evaluation were installed on the roof and south façade of each greenhouse. The control greenhouse used only the standard polyethylene film, while the shading-control greenhouse added a shading net to selected zones. One solar greenhouse featured monofacial silicon PV modules with 50% transparency, and the other used cadmium telluride (CdTe) modules, also at 50% transparency. Each solar greenhouse had 18 modules—half on the roof, half on the façade—with nominal powers of 59 W for PV-Si and 40 W for PV-TF.

The microclimatic conditions inside each pilot greenhouse were monitored at two-minute intervals. Measurements included air temperature, relative humidity, solar irradiance, and photosynthetically active radiation,” the team explained. “Additionally, soil temperature and humidity were measured at five-minute intervals at depths ranging from 10 to 60 cm in 10 cm increments.”

The testing showed that the PV-Si technology generated an average daily energy output of 3.92 kWh in winter-spring and 4.07 kWh in spring-summer. PV-TF, meanwhile, produced 2.58 kWh and 2.79 kWh, respectively. Total energy generation across both seasons reached 726.8 kWh for PV-Si and 488.4 kWh for PV-TF.

Daily light integral (DLI), representing total photosynthetically active light received by plants each day, averaged 18.1 mol m⁻² in winter-spring and 25.4 mol m⁻² in spring-summer in the Si greenhouse. In the TF greenhouse, DLI averaged 10.8 mol m⁻² and 17 mol m⁻², respectively.

“During the winter-spring cycle, only the control and PV-Si greenhouses maintained DLI values above the minimum threshold required for optimal crop development,” the researchers reported. “Despite a similar number of fruits, the PV-Si greenhouse produced fruits with a mean weight 25% higher than the control, attributed to more favorable nighttime air temperatures and higher soil moisture.”

In winter-spring, the Si greenhouse yielded 21 fruits with an average weight of 74 g, while the TF greenhouse produced 18 fruits averaging 50 g. During spring-summer, the Si greenhouse produced 30 fruits averaging 93 g, compared with 23 fruits at 79 g in the TF greenhouse.

“Overall, the PV-Si system effectively balanced solar radiation management, thermal regulation, and energy production, demonstrating its potential as a suitable technology for agrivoltaic applications,” the team concluded.

The research findings were presented in “Comparative evaluation of semi-transparent monocrystalline silicon and cadmium telluride photovoltaics for tomato cultivation in Mediterranean agrivoltaic greenhouses,” published in Smart Agricultural Technology. Researchers from Spain’s IMIDA, Miguel Hernández University of Elche, and Italy’s University of Bari Aldo Moro have contributed to the study.

Sungrow says energy storage systems overtook PV inverters as its largest business segment in 2025, as the company posted double-digit revenue and profit growth.

Sungrow said revenue reached CNY 89.184 billion ($12.95 billion) in 2025, up 14.55% year on year, with net profit attributable to shareholders rising 21.97% to CNY 13.461 billion. Energy storage systems generated CNY 37.287 billion in revenue, up 49.39%, accounting for 41.8% of total revenue, while global storage shipments reached 43 GWh. PV inverter revenue totaled CNY 31.136 billion, with global shipments of 198 GW and an estimated 30% market share. Overseas revenue rose 48.7% to CNY 53.992 billion, representing 60.5% of total revenue. The company attributed a more than 50% year-on-year decline in fourth-quarter net profit to a CNY 1.0 billion incentive fund provision and adjustments to overseas project delivery schedules, and said it is advancing plans for a Hong Kong listing to support global expansion.

Laplace has denied market rumors that it had secured a second-phase PV project from Tesla valued at nearly CNY 10 billion, saying no such orders existed and no undisclosed material information was being withheld. The company warned investors against irrational speculation following recent stock gains.

The National Energy Administration (NEA) said China's nationwide PV utilization rate reached 90.8% in January to February, down four percentage points from the 2025 average and approaching the commonly cited 90% curtailment threshold. The decline was attributed to reduced electricity demand during the Lunar New Year holiday period, when lower industrial and commercial activity typically increases solar curtailment.

GCL New Energy said its board has proposed changing the company's English name to Dynasty Digital Holdings Ltd, reflecting a strategic shift toward integrating digital technologies including AI and Web3.0 into its business development.

The China Nonferrous Metals Industry Association (CNMIA) said polysilicon prices are falling sharply, with n-type re-feed and granular silicon both averaging CNY 36,500 per metric ton on April 1, down 9.88% week on week. N-type re-feed polysilicon traded between CNY 35,000 and 37,000 per metric ton (MT), while n-type granular silicon traded between CNY 36,000/MT and 37,000/MT, with both averaging CNY 36,500/MT.

In a new weekly update for pv magazine, Solcast, a DNV company, reports that last month North America saw a stark solar divide, with southern regions like northeastern Mexico, southeastern Texas, and much of California experiencing 20–25% above-average irradiance, while Canada, the Great Lakes, and the northeastern U.S. faced persistent cloudiness and below-normal solar conditions. This contrast was driven by high-pressure systems and a southwestern heat dome in the south versus a polar vortex bringing cold air and storms to the north.

North America experienced a pronounced divide in solar conditions through March, with the southern half of the continent recording widespread increases in solar resource while the north faced persistent cloud and storm activity, according to analysis using the Solcast API.

The strongest gains were centered on northeastern Mexico and southeastern Texas where deviations reached roughly 20–25% above the long-term March average, with much of California also seeing similar increases. Canada, the Great Lakes and the northeastern United States recorded lower-than-normal irradiance as polar air and storm systems dominated conditions. This produced a month in which the usual seasonal contrast between north and south was sharpened, with clearer skies in the south and cloudier conditions in the north compared with the 2007–2025 average.

Much of the southern United States and northern Mexico benefited from a pair of high-pressure systems positioned over the Pacific and Atlantic coasts of North America. These systems stabilised the atmosphere and kept skies clearer than normal across large areas. Southern Mexico and Florida were exceptions to the southern trend, each experiencing slightly below average irradiance where localised cloud cover persisted.

A pronounced heat dome over the southwestern United States further reinforced these conditions, driving temperatures 10–19 C (18-35 F) above seasonal norms and breaking multiple records, as localized areas saw even large increases. These warm conditions, more like summer temperatures than spring, were the result of high atmospheric stability, which also suppressed cloud formation and supported extended periods of clear skies. As a result, California emerged as one of the strongest-performing regions relative to average conditions, with irradiance levels significantly elevated through much of the month. The scale of the heat anomalies was notable, with attribution studies indicating these extremes would be highly unlikely without the influence of climate change.

At the same time, northern parts of the continent experienced a very different pattern as an unstable polar vortex pushed cold polar air into Canada and the northern United States. This brought snowstorms and blizzards across several regions, particularly around the Great Lakes and the Northeast, where irradiance fell far below normal for March. These stormy conditions contributed to the largest percentage drops from average in areas north of the Great Lakes.

The push of polar air extended unusually far south, reaching into Florida and contributing to its slightly below normal irradiance despite the generally sunnier conditions across most of the southern half of North America. Collectively, these factors reinforced the strong contrast between the sunnier southern regions and the cloudier, storm affected conditions across the north.

Solcast produces these figures by tracking clouds and aerosols at 1-2km resolution globally, using satellite data and proprietary AI/ML algorithms. This data is used to drive irradiance models, enabling Solcast to calculate irradiance at high resolution, with typical bias of less than 2%, and also cloud-tracking forecasts. This data is used by more than 350 companies managing over 300 GW of solar assets globally.

The first bid window of Zambia's new Carbon Feed In Premium Program plans to develop 300 MW of solar across projects that are connected to on-site battery energy storage systems. The deadline to submit expressions of interest is May 31.

The Zambian government is inviting applications to its Carbon Feed In Premium Program (CFIP), a new results-based financing mechanism geared towards large-scale, grid-connected solar installations.

The program, implemented by the country’s Ministry of Green Economy and Environment and Ministry of Energy, is open to both national and international independent power producers, national power utility ZESCO and its subsidiaries.

A call for proposals states that the first CFIP window will focus on procuring 300 MW of new solar projects.

Participation criteria adds that only solar projects with planned installed capacities between 30 MW and 100 MW are eligible. Projects should also encompass a battery energy storage system located on site with a capacity of at least half an hour.

Projects supported by the program must be connected to the national grid, with ZESCO acting as the primary offtaker via a power purchase agreement.

An online CFIP information event will take place on April 14, ahead of a deadline for applicants to submit their expressions of interest by May 31.

Funding for the CFIP has been made available through a bilateral agreement between Zambia and Norway, with Norway set to pay for the verified emissions reductions generated by the projects delivered under the program.

The Africa Solar Industry Association (AFSIA) has identified 912.4 MW of operational solar in Zambia across 142 projects, according to its project database.

Last May, ZESCO completed the 100 MW Chisamba solar farm in southern Zambia, the country's largest operational project to date. At the time, the company said it plans to add a second 100 MW at the site. Work is also underway on a separate 100 MW solar project towards the east of the country.

California-based Terabase Energy is scaling up its automated solar construction platform and expanding its engineering software ecosystem to improve project delivery and performance modeling.

From pv magazine USA

California-based engineering and construction technology firm Terabase Energy says its new Terafab V2 automated solar array construction system has completed field testing and is ready for commercial service. The Terafab process solar panel and tracker torque tube assemblies onsite and deploys them on prepositioned tracker mounts using AI-assisted robotics.

In addition, Terafab has established a partnership with California-based energy consulting firm PowerUQ to integrate the latter’s uncertainty analysis software with the former’s PlantPredict solar modeling tools. The developments represent significant investments in solar plant technology at a time when new large-capacity power projects face shifting economic incentives.

The core of the upgraded Terafab factory system is an outdoor assembly and inspection center that is erected on active construction sites. The current version of the factory is optimized for First Solar Series 7 panels and Nextpower trackers.

Palleted panels are paired with steel tubes and in the field and run through an automated inspection line that performs quality control. Defects are caught in real time. Robotic arms load approved assemblies from the line onto unmanned rovers that drive them out to their appointed locations in the array field for manual placement.

Matt Campbell, CEO and co-founder of Terabase Energy told pv magazine USA that he has been working for ways to streamline solar construction since his days at SunPower a decade and a half ago. Earlier efforts involved prefabricating tracking module assemblies in the factory and shipping them to the site, but the weight and dimension limits imposed too many compromises on the process.

“We decided, ‘Hey, let’s do prefab, but we’re going to do it on-site because of the shipping density problem.’ But then we inherit these other problems,” Campbell said. “It’s hard to do outdoor robotics. Plus, we essentially take a factory assembly operation and set it up on site, where we have to fight through rain, hail, wind, tornadoes, dust, ants, bees, snakes, badgers, rats. Literally.”

Terabase’s research and development efforts have resulted in factory line that is hardened against the elements and nature’s creatures. Palleted modules and tracker frame components are shipped to the construction site. One robot unpacks them and moves module and torque tube assemblies through the inspection and loading point. Campbell says Terafab V2 has a two-minute cycle time that could ideally place 20 MW per week per line if running continuously. Campbell says there are two deployable factories available now with a third to be ready by the end of the year. He expects 10 factories to be available in the second quarter of 2027.

Terabase has used the first version of the Terafab system to install 40 MW of tracking solar over across multiple commercial projects in the U.S. With the addition of AI-assisted management software and automated robotics, the company expects to install hundreds more megawatts of solar in 2026.

“The new version is more compact than the original, so you can you can move it in four hours,” he said. “It’s pretty nimble and has a higher level of automation. The factory is twice as fast, and you can run multiple lines per site. My goal is to install a gigawatt in 10 weeks. The way you could do that is if we send four or five Terafabs to a site and run them 24 hours. We could do that.”

With the current version of the system, workers manually unload the panel-tube assemblies from the rovers and install them onto mounts, which have been pre-placed. Terabase says a future version of the system, due in 2027, will automate the process of fitting assemblies onto tracker mounts. Campbell said versions of Terafab capable of handling panels using silicon modules and other tracker components are forthcoming.

Terafab V2 was financed largely through a $130 million series C investment round led by Softbank last year. Campbell said the investment has enabled the company to pursue research and development on a number of initiatives designed to bring down the cost and time required to install large-scale solar.

“Well, the original goal of the company is in the name, ‘Terawatt Baseload Energy,’” Campbell said. “When we started the company, I asked, ‘What do we need for solar to be a terawatt-scale source of baseload energy?’ And the conclusion was, we need to be able to build it 10 times faster for half the cost.”

Another example of this investment in new technology can be found on the company’s engineering and analysis side of the business, with PlantPredict’s integration agreement with PowerUQ. The integration enables a solar productivity analysis in PlantPredict to be loaded into PowerUQ for an uncertainty quantification analysis to forecast plant performance over time taking additional factors into account.

David Spieldenner, director of PlantPredict sales at Terabase, told pv magazine USA that his company’s software represents an expansion of desktop photovoltaic analysis tools such as PVSyst by using cloud computing to enable more extensive analyses. Access to high-end computing enables PlantPredict to use parallel processing across many data centers to produce very granular results.

“We unlock the power of the cloud to do very advanced 3-D sub-hourly simulations,” he said.

Chetan Chaudhari, co-founder and CEO of PowerUQ, told pv magazine USA that while PlanPredict is a very high-fidelity, accurate physics model with its shading engine and different model chains that it considers while calculating energy production, its focus has mainly been on first year energy generation. Historically this has been worked, he added, because most of the plant value came from project’s tax credits and the high power purchase agreement rates it could command.

“But now that that’s kind of going away” Chaudhari said. “There are a lot more market pressures. We are seeing more news about the underperformance of these solar assets over their lifespans. This is the time for the industry to move away from just looking at the first-year generation and basing all the financial calculations on that. We need to be able to think about the project as a 20-year, 30-year asset that you’re investing billions of dollars in.”

The function of PowerUQ is to analyze factors that introduce variability into plant output models and evaluate the risks these impose on the project. Examples of such uncertainty are the performance of components over time, curtailment policies of utilities that dampen production, and the impact of El Niño weather events. A PowerUQ analysis of a PlantPredict model could show a range of probabilities for output scenarios and the risk levels associated with them.

“As we’re moving forward, we want to make sure people don’t get results that they don’t trust,” Spieldenner said. “PowerUQ is going to help people better understand the implications of the deeper results they are getting out of PlantPredict.”

The German manufacturer said its new back-contact solar panel has a power conversion efficiency of up to 23.52%.

From pv magazine Germany

German module manufacturer Bauer Solar is expanding its product portfolio with a new back-contact panel.

Initially, it will launch a full-black glass-glass version with an output of 480 W. It is built on 108 bifacial half-cells and measure 1,800 mm × 1,134 mm × 30 mm, with a listed weight of 24.8 kg. The module power conversion efficiency is 23.52%.

The company said that both the front and rear glass panes are 2 mm thick and feature anti-reflective coatings. The frame is made of anodized black aluminum alloy. The modules are rated for operating temperatures from –40 C to 85 C and a maximum system voltage of 1,500 V. They can reportedly withstand static loads up to 5,400 Pa and carry a hail resistance rating of HW3. Certifications include fire protection class A.

Bauer Solar is offering a 30-year product and performance warranty on the new modules. The linear performance warranty guarantees a minimum output of 88.85 % of the original capacity after 30 years. The company also plans to increase the output of its back-contact modules to 500 W later this year with the “Pure” and “Performance” variants.

Alongside back-contact modules, Bauer Solar will continue to focus on its TOPCon technology. This portfolio will be expanded this summer with the “Pure” and “Black” variants, which will reach an output of 465 W. While the company did not disclose pricing, it emphasized that the modules are aimed at the residential rooftop solar market as “an economical solution with an optimal price-performance ratio.”

An international reserch team developed two deep learning-based IDS models to enhance cybersecurity in SCADA systems. The hybrid approach reportedly improves detection of complex and novel cyber threats with high accuracy, adaptability, and efficiency, outperforming traditional methods across multiple datasets.

A Saudi-British research team has develeped two new deep learning-based intrusion detection systems (IDSs) that can reportedly improve the cybersecurity of SCADA networks.

In large-scale solar power plants, SCADA systems play a vital role by overseeing energy generation, monitoring the performance of solar panels, optimizing output, identifying potential faults, and maintaining smooth overall operations. In essence, they act as the central system that converts raw solar data into practical control decisions, ensuring the plant operates safely, efficiently, and profitably.

The scientists explaind that current cybersecurity frameworks are often inadequate for SCADA systems because they cannot fully cope with the complexity and constantly evolving nature of modern cyber threats. Most existing approaches rely on signature-based detection, which depends on prior knowledge of attack patterns and therefore fails to detect zero-day exploits or novel intrusion techniques.

To address this limitation, the researchers considered deep learning methods, as these techniques allows to process large volumes of data, identify complex patterns, and enable more proactive threat detection.

“Such capability of handling and analyzing big data is particularly useful during scenarios when SCADA systems are generating huge streams of real-time data, including sensor readings, control commands, and other system logs,” they explained. “Furthermore, deep learning methods, especially convolutional neural networks (CNNs) and recurrent neural networks (RNNs), have shown outstanding performances in the detection of complex attack scenarios with sequential or spatial patterns in data.”

The proposed approach integrates two new IDSs, named the Spike Encoding Adaptive Regulation Kernel (SPARK) and the Scented Alpine Descent (SAD) algorithm. By leveraging their complementary strengths, the method reportedly improves spike-threshold accuracy while enhancing adaptability and robustness under dynamic conditions.

The SPARK model introduces adaptive spike encoding by dynamically adjusting thresholds based on input signal characteristics. It uses advanced statistical methods to respond to variations in neural input, improving sensitivity to changes in intensity and frequency. By integrating both temporal and spatial features, SPARK enhances information encoding, especially for complex datasets. Unlike traditional fixed-threshold methods, it provides context-aware thresholding, improving accuracy and reliability.

The SAD algorithm complements SPARK by offering an optimization strategy inspired by olfactory navigation, which is the process by which animals and organisms use odor cues to locate food, mates, or home, and Lévy flight behavior, which is a strategy obeserved in many animal species to randomly search for a target in an unknown environment. This purportedly enables efficient exploration of solution spaces and avoids local minima, ensuring optimal threshold selection.

The hybrid approach can dynamically adjust and optimize spike thresholds simultaneously, surpassing conventional static or isolated approaches, according to scientists, which noted that the SPARK model is well-suited for SCADA and IoT systems due to its scalability, real-time adaptability, and efficient data handling. Additionally, its lightweight design reduces computational overhead and false positives, making it effective for resource-constrained environments.

“SAD is complementary to SPARK in the sense that it focuses on improving the detection accuracy while maintaining computational efficiency,” the researchers emphasized. “SAD's anomaly scoring mechanism can be integrated into this framework to add another layer of detection, which can run parallel with SPARK. In effect, integrating the deep learning models into the scoring mechanism means that SAD would enable a much more fine-grained analysis of attack patterns with little noticeable impact on performance for the SCADA system in question.”

The researchers used multiple benchmark datasets are used to evaluate SCADA intrusion detection performance, including the Secure Water Treatment (SWaT) testbed, Gas Pipeline, WUSTL-IIoT, and Electra. These datasets capture diverse industrial environments, attack types, and operational conditions, enabling comprehensive testing. They also include time-series sensor data, actuator commands, and labeled attack scenarios such as denial-of-service (DoS), distributed denial-of-service (DDoS), malware, and injection attacks.

The diversity of datasets ensured accurate modeling of both normal behavior and complex anomalies in SCADA and IIoT systems, according to the research team. Standardized preprocessing, training, and evaluation procedures also enabled comparison across all tested models. Cross-validation and controlled training conditions, meanwhile, reportedly prevented bias and ensured reliable generalization results. Visualization tools such as histograms, loss curves, and confusion matrices provided insights into model behavior and anomaly detection.

The SPARK model was found to consistently demonstrate “superior” performance, achieving high accuracy, precision, and recall across datasets. It outperformed traditional machine learning and deep learning approaches in detecting diverse intrusion types.

“The findings underline, in summary, that the SPARK and SAD models are basically the final frontier in modern intrusion detection,” the scientists said. “Distinctly designed to provide improved detection capabilities and operational efficiency, the two designs also chart a way into more resilient and intelligent security solutions for modern industrial controlled systems (ICSs) and Internet-of-Things (IoT) networks.”

The novel IDSs have been presented in “SPARK and SAD: Leading-edge deep learning frameworks for robust and effective intrusion detection in SCADA systems,” published in the International Journal of Critical Infrastructure Protection. The research team comprised academics form the Leeds Beckett University in the United Kingdom and King Abdulaziz University in Saudi Arabia.