Latest news with #AMPINEnergyTransition
Economic Times
18 hours ago
- Business
- Economic Times
Suzlon Energy shares rally 3% after fresh 170 MW wind order win
Shares of Suzlon Energy climbed as much as 2.8% on Friday to Rs 64.26 on the BSE after the renewable energy firm announced a fresh 170.1 megawatt (MW) wind power order from AMPIN Energy Transition—its third consecutive deal with the clean energy platform. ADVERTISEMENT In an exchange filing on Friday, Suzlon said, 'We have won a third successive repeat order of 170.1 MW from AMPIN Energy Transition Ltd. to supply 3.15 MW wind turbines for their proposed wind power project to be developed at Kurnool in Andhra Pradesh.' The project will involve the supply of 54 units of Suzlon's advanced S144 wind turbine generators, each with a rated capacity of 3.15 MW, mounted on Hybrid Lattice Towers. The company added that the scope of the project includes the 'supply, installation, and commissioning of the wind turbines,' and will be executed with Suzlon's equipment, along with comprehensive operation and maintenance services post this latest win, Suzlon's total order book from AMPIN now stands at 303 MW. ADVERTISEMENT Suzlon shares have risen 31% over the past year, 11% in the last three months, and 4% over the past month. The stock has remained in focus following a series of block deals earlier this week, where promoters sold 19.8 crore shares worth over Rs 1,300 crore at an average price of Rs 66.05 per the key institutional buyers were Goldman Sachs, Motilal Oswal, Societe Generale, ICICI Prudential, and Bandhan Mutual Fund. As of the March 2025 quarter, mutual funds held a 4.17% stake in Suzlon Energy, while promoter holding stood at just over 13%. ADVERTISEMENT From a technical standpoint, the stock is trading above five of its eight key simple moving averages (SMAs)—including the 30-day, 50-day, 100-day, 150-day, and 200-day SMAs—while remaining below the 5-day, 10-day, and 20-day Relative Strength Index (RSI) currently stands at 44.8. An RSI below 30 is typically considered oversold, while a reading above 70 is viewed as overbought. Meanwhile, the Moving Average Convergence Divergence (MACD) is at 0.9—above the center line but below the signal line—indicating a mixed momentum setup for the stock in the near term. ADVERTISEMENT Also read | HDFC Bank shares in focus as Rs 12,500-crore HDB Financial IPO opens next week (Disclaimer: Recommendations, suggestions, views and opinions given by the experts are their own. These do not represent the views of The Economic Times) (You can now subscribe to our ETMarkets WhatsApp channel)
Time of India
18 hours ago
- Business
- Time of India
Suzlon Energy shares rally 3% after fresh 170 MW wind order win
Suzlon Energy shares rose up to 2.8% after securing a 170.1 MW wind power order from AMPIN Energy Transition—its third consecutive deal with the firm. The order involves supplying 54 advanced turbines for a project in Andhra Pradesh. With this, Suzlon's total order book from AMPIN reaches 303 MW. The stock remains in focus amid recent block deals and mixed technical signals. Tired of too many ads? Remove Ads Tired of too many ads? Remove Ads Stock Gains and Technical Outlook Shares of Suzlon Energy climbed as much as 2.8% on Friday to Rs 64.26 on the BSE after the renewable energy firm announced a fresh 170.1 megawatt (MW) wind power order from AMPIN Energy Transition—its third consecutive deal with the clean energy an exchange filing on Friday, Suzlon said, 'We have won a third successive repeat order of 170.1 MW from AMPIN Energy Transition Ltd. to supply 3.15 MW wind turbines for their proposed wind power project to be developed at Kurnool in Andhra Pradesh.'The project will involve the supply of 54 units of Suzlon's advanced S144 wind turbine generators, each with a rated capacity of 3.15 MW, mounted on Hybrid Lattice company added that the scope of the project includes the 'supply, installation, and commissioning of the wind turbines,' and will be executed with Suzlon's equipment, along with comprehensive operation and maintenance services post this latest win, Suzlon's total order book from AMPIN now stands at 303 shares have risen 31% over the past year, 11% in the last three months, and 4% over the past month. The stock has remained in focus following a series of block deals earlier this week, where promoters sold 19.8 crore shares worth over Rs 1,300 crore at an average price of Rs 66.05 per the key institutional buyers were Goldman Sachs, Motilal Oswal, Societe Generale, ICICI Prudential , and Bandhan Mutual Fund. As of the March 2025 quarter, mutual funds held a 4.17% stake in Suzlon Energy, while promoter holding stood at just over 13%.From a technical standpoint, the stock is trading above five of its eight key simple moving averages (SMAs)—including the 30-day, 50-day, 100-day, 150-day, and 200-day SMAs—while remaining below the 5-day, 10-day, and 20-day Relative Strength Index (RSI) currently stands at 44.8. An RSI below 30 is typically considered oversold, while a reading above 70 is viewed as overbought. Meanwhile, the Moving Average Convergence Divergence (MACD) is at 0.9—above the center line but below the signal line—indicating a mixed momentum setup for the stock in the near term.
Business Upturn
20 hours ago
- Business
- Business Upturn
Suzlon secures 170.1 MW wind power project from AMPIN Energy in Andhra Pradesh
Suzlon has recently informed exchanges that the company secured its third consecutive wind energy project from AMPIN Energy Transition . The new 170.1 MW project will be developed in Kurnool, Andhra Pradesh, further reinforcing the companies' commitment to decarbonizing India's electricity distribution companies (DISCOMs). This partnership is a major boost to India's renewable energy goals and the Make in India initiative, showcasing the growing synergy between local manufacturing and clean power deployment. Suzlon and AMPIN's continued collaboration reflects a shared vision of accelerating the nation's move to a low-carbon, energy-secure future through innovative, locally produced wind energy solutions. Under the terms of the agreement, Suzlon will deliver 54 of its cutting-edge S144 wind turbine generators (WTGs) , each with a capacity of 3.15 MW. The turbines will be mounted on Hybrid Lattice Towers (HLT) , known for their superior efficiency and cost-effectiveness. The project scope includes comprehensive execution—from equipment supply and installation to commissioning and long-term operations and maintenance services—ensuring end-to-end support for the clean energy venture. JP Chalasani, Chief Executive Officer, Suzlon Group, said, 'India's decarbonization journey will be won or lost at the distribution level. DISCOMs are the critical link between renewable energy generation and everyday consumption—from industries to households. To empower them with reliable, cost‐efficient clean power is not just a goal—it's a national imperative. Together, we're proving that clean energy isn't just viable—it's vital, scalable, and transformative for the power sector.' This strategic partnership not only highlights the scalability of renewable energy infrastructure in India but also underpins efforts to make green power more accessible and affordable for industries across the country. Ahmedabad Plane Crash Aman Shukla is a post-graduate in mass communication . A media enthusiast who has a strong hold on communication ,content writing and copy writing. Aman is currently working as journalist at
United News of India
22-04-2025
- Business
- United News of India
Corporate funding in global solar sector declines YoY, but Indian scenario promising: Mercom
Kolkata, Apr 22 (UNI) Total corporate funding in the global solar sector reached $ 4.8 billion across 39 deals in Q1 2025 — a 41 per cent decline year-over-year (YoY) compared to $ 8.2 billion raised through 42 deals in Q1 2024. However, funding was up 20 per cent quarter-over-quarter (QoQ) from the $4 billion raised in 40 deals in Q4 2024, as per the latest report from Mercom Capital Group, a leading clean energy consulting firm "The drop in funding this quarter reflects growing investor caution in response to policy reversals, tariff shocks, and regulatory uncertainties that have forced companies and investors to reassess their strategies. However, the fundamentals remain strong, and the long-term case for solar energy is intact. We need clarity and policy certainty to restore confidence in the markets. Despite headwinds in the broader funding environment, we did see an uptick in project M&A in Q1," said Raj Prabhu, CEO of Mercom Capital Group. Global VC funding for the solar sector in Q1 2025 came to $1.4 billion in 14 deals, a 237 per cent increase YoY compared to $406 million raised in 13 deals in Q1 2024. Funding increased 40 per cent QoQ compared to the $1 billion raised in 21 deals in Q4 2024. Overall funding scenario in the solar sector also looks promising, when it comes to India. Funding deals in India included VC Funding, Public market funding, Debt Funding, M&A, Project M&A. In this period, AMPIN Energy Transition secured a $50 million equity investment from Siemens Financial Services, Amrut Energy secured Rs 1 billion (nearly $11.49 million) in funding from private equity investors, Solarium Green Energy raised Rs 105.04 crore (nearly $12 million) through its IPO. When it comes to 'Debt Funding', BluPine Energy has secured Rs 17.87 billion (close to $210 million), JSW Energy has raised Rs 12 billion (nearly $137.70 million), SWELECT Group secured Rs 2.9 billion (~$33.39 million), Ecozen has raised over $23 million, Ecofy secured a $12.5 million, Credit Fair raised $5 million (nearly Rs 415 million) from the $75 million (close to Rs 6.22 billion) 'Green Basket Bond' issued by Symbiotics Investments. here have been M&A deals of decent size as well. ONGC NTPC Green (ONGPL), for instance, has signed a share purchase agreement to acquire a 100 per cent equity stake in utility-scale renewable energy platform Ayana Renewable Power for Rs 195 billion (nearly $2.3 billion). Waaree Energies has entered into a share purchase agreement with Enel Green Power Development to acquire 100 per cent of the share capital of Enel Green Power India for Rs 7.92 billion (nearly $91.73 million). Besides, Brookfield Asset Management announced the sale of 1.6 GW portfolio of solar and wind assets in India to Gentari Renewables India for an undisclosed amount, Actis has acquired a 100 per cent stake in Stride Cmate Investments from a fund managed by Macquarie Asset Management. UNI XC SSP
Time of India
21-04-2025
- Business
- Time of India
From solar panels to smart grids: How AI is powering the future of energy operations
Mumbai: As the world races toward cleaner, smarter energy solutions, Indian energy companies are increasingly leaning on artificial intelligence (AI) to drive efficiency, cut costs, and optimise performance. We got in touch with renewable energy industry executives to understand how AI is helping them achieve better results, what kind of benefits they are able to take from it, and what are the real-life use cases of AI that they can share with us. Pooja Patwari, AI-Lead, Chairman's Office, Avaada Group While Avaada is in the early stages of integrating AI, we are laying strong foundations for its transformative role across our business verticals. AI has the potential to significantly enhance decision-making in areas like energy forecasting, predictive maintenance, and project planning. For example, in solar asset management, AI models can predict generation patterns based on weather data and optimise output. Across our green hydrogen roadmap, AI can help model electrolyzer efficiency and market pricing strategies. Though not yet fully deployed, we are actively exploring partnerships and pilots that embed AI into operational workflows, signaling our commitment to smarter, tech-driven growth in the energy sector. AI offers a leap in operational intelligence, enabling faster, data-backed decisions and real-time optimisation. For a company like Avaada operating in high-capex, large-scale infrastructure projects, AI reduces downtime, enhances asset efficiency, and ensures tighter control on costs. In renewables, AI enables granular forecasting—vital for grid balancing and financial modeling. Moreover, as we expand into green hydrogen and ammonia, AI will be pivotal in designing agile, responsive systems that learn and improve over time. In essence, AI is not just a tool for efficiency—it's becoming a strategic pillar for sustainability and competitiveness in clean energy. Within Avaada, AI is being explored for – Solar yield forecasting using satellite and weather data, drone-based inspections integrated with AI for panel anomaly detection, energy trading optimization, particularly relevant as we plan green hydrogen production. Across the broader energy sector, AI is already used in smart grid management to predict load and prevent outages, battery management systems optimizing charge/discharge cycles, AI-powered robotics for hazardous inspections in wind or thermal plants, hydrogen production analytics, and modeling the best production windows based on electricity prices and demand forecasts. Victor Bhattacharya, lead operations and maintenance and asset management - utilities, AMPIN Energy Transition We are redefining renewable energy asset management through the integration of Artificial Intelligence (AI) and Machine Learning (ML), embedding them across all facets of its operations. From solar and wind energy production to hybrid power plant optimisation, AI and ML are central to improving energy yield, equipment reliability, and operational efficiency. By shifting from reactive to predictive maintenance models, automating diagnostics, and leveraging intelligent systems, AMPIN has significantly increased uptime, reduced failure rates, and improved the profitability of its renewable energy projects. Real-Time Data as the Foundation of Smart Operations: Our AI-driven systems are built on a robust foundation of real-time data, collected through an extensive sensor network across its solar and wind assets. These sensors monitor environmental conditions—like solar irradiance, temperature, wind speed, and humidity—as well as electrical parameters such as voltage, current, and grid frequency. This data ecosystem enables AI models to continuously learn from real-time and historical trends, predict equipment behavior, and optimize plant operations dynamically. Predictive Maintenance Using Machine Learning : A cornerstone of our digital strategy is its predictive maintenance framework, powered by supervised and unsupervised ML algorithms. These models detect operational inefficiencies and failure trends before they escalate, based on subtle behavioral patterns. By examining correlations among inverter loading, temperature spikes, and past failure logs, the system flags probable future issues. For example, localised overheating can indicate early signs of inverter or panel issues, prompting timely interventions and preventing widespread downtime. This shift to a proactive maintenance model has significantly reduced the Mean Time Between Failures, improved asset availability, and extended the lifecycle of critical components. Monitoring Key Operational Parameters for Optimisation: Constant surveillance of variables like temperature, voltage fluctuations, and resource availability allows our AI systems to fine-tune operations in real time. These systems model complex interactions—such as how cloud cover affects panel output or wind turbulence impacts turbine efficiency—and adjust control strategies accordingly. Historical fault data further strengthens these models, enabling more context-aware alerts and fewer false alarms, ensuring faster, more effective responses by field teams. Drone-Based Thermographic Inspections: We use AI-powered drones for high-resolution thermographic inspections of solar panels. These drones identify defects such as hotspots, Potential Induced Degradation, and diode failures with speed and precision. The captured images are analysed using advanced pattern recognition algorithms that categorise anomalies by severity and urgency. Geo-tagging and integration with asset registers enable targeted repairs and long-term health tracking of individual modules, moving the organisation from reactive issue resolution to strategic asset management. AI-Enabled Asset Management Platforms: Our proprietary AI platforms serve as centralised intelligence systems, processing vast datasets from its assets to deliver real-time insights. These platforms offer anomaly detection, energy loss analytics, and optimization of maintenance schedules, all through automated, self-learning processes. By highlighting underperforming modules or turbines and prescribing corrective actions, the platform allows O&M teams to address issues swiftly. This drastically reduces performance losses and supports data-driven decision-making at all levels of the organization. Executive Dashboards for Performance & Compliance: We have developed intuitive executive dashboards tailored to various stakeholders. Engineers can monitor real-time performance metrics, while leadership teams gain access to high-level summaries of energy generation, regulatory compliance, and financial KPIs. These dashboards also automate compliance reporting, including daily generation reports, DSM logs, and energy forecasts. This automation ensures regulatory alignment and reduces manual workload. AI-Powered Weather Forecasting for DSM Optimisation: Accurate forecasting is crucial under India's Deviation Settlement Mechanism, where financial penalties apply to inaccurate scheduling. AMPIN's AI models utilize satellite data, local sensors, and meteorological trends to forecast irradiance and wind conditions with high accuracy. Day-ahead and intra-day forecasts improve scheduling precision, reducing deviation penalties and enhancing grid stability. This predictive capability supports both financial sustainability and operational resilience. Robotic Cleaning Systems for Solar Panels: Maintaining solar module cleanliness is vital for sustained performance. We deploy AI-powered robotic cleaners that assess dust accumulation, plan optimal cleaning routes, and operate with minimal water consumption. These robots adapt their paths and frequency based on panel tilt and weather forecasts, ensuring cost-effective, sustainable cleaning. In wind energy, drone-enabled inspection and cleaning systems similarly ensure turbine blades are efficient and defect-free, reducing downtime and improving aerodynamic efficiency. Crane less Wind Turbine Installation: To overcome logistical challenges in remote or rugged terrains, we have adopted craneless wind turbine installation. This approach utilises modular lifting and assembly systems instead of large cranes, reducing emissions, costs, and deployment time. This innovation supports faster project execution, minimizes environmental impact, and aligns with AMPIN's sustainability goals. Hybrid Plant Management with ML Controllers: Our hybrid energy systems — comprising solar, wind, and storage — require precise coordination. Hybrid Power Plant Controllers with embedded ML algorithms manage energy dispatch, storage usage, and grid compliance. These controllers adapt over time using reinforcement learning, responding to seasonal changes and grid demands. The result is improved energy balancing, reduced battery wear, and enhanced reliability of hybrid systems. AI-Driven Solar Trackers: We have implemented intelligent solar tracking systems with AI-based control cards that adjust module angles based on real-time sun position and weather data. These systems boost solar capture and minimize mechanical wear by optimising tilt based on environmental inputs. This leads to measurable improvements in daily and annual energy generation, better plant ROI, and longer system lifespan. Our integration of AI and ML has transformed the operational paradigm of its renewable assets. From automated cleaning and forecasting to intelligent maintenance and hybrid coordination, smart technologies are at the heart of delivering higher energy yields, lower O&M costs, and superior grid compliance. Kumar Shivam, area sales manager, AXITEC Energy India At Axitec, we are embracing AI and advanced imaging technologies to transform our manufacturing processes, with a strong focus on quality control and customer transparency. We've integrated a network of high-resolution visual and infrared cameras across the production line, coupled with sensors and AI-powered inspection systems. These AI models are being trained using thousands of labeled images to automatically detect faults during the production and testing phases. This system is reducing reliance on manual inspections and enabling more consistent, real-time decision-making. Remote Inline Inspection: Customers can now verify their modules in real time from anywhere through AI-powered image and data feeds—making the inspection process faster, remote, and more transparent. Human Error Elimination: AI minimizes subjectivity and inconsistency, especially during EL inspections. Comprehensive Fault Detection: AI can detect micro-cracks, cell mismatch, soldering issues, and other anomalies that would be difficult or time-consuming to catch manually. Optimised Product Quality: AI-driven systems help improve both visual and electrical quality standards, leading to better-performing and more reliable solar modules. Enhanced Electrical Verification: AI also supports analysis of I-V curves during flash testing, improving precision in performance validation. At our manufacturing facility: AI + EL Imaging: Detects issues like micro-cracks, grayscale mismatches (cell current imbalance), poor ribbon soldering, and cell-to-cell gap deviations. Flash Test Optimization: AI automates I-V curve analysis to ensure modules meet electrical efficiency and safety benchmarks. Remote Quality Inspection for Customers: Through live video and AI-generated reports, customers can inspect their order inline—without needing to be physically present.
