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    How SmartHelio’s Predictive Analytics Is Driving Solar Plants’ Profitability?

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    How fast can you track that your solar system is underperforming? Can you tell the root cause of the underperformance instantly? Imagine if somehow we are able to detect the smallest of deviations and plan accordingly to act, before the system goes down, this would be amazing. This is predictive analytics! If you can cut short your losses at 0.05%, why follow a system where 1% loss is forgiven for climatic uncertainty? And all of this, when O&M costs are rising, PPA costs are shrinking and pressure of profitability is surmounting. 

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    Performance issues are grabbing investors’ attention 

    Multiple O&M problems like surfacing of installation issues, wiring problems, equipment efficiency drops, supply chain issues, rising prices of steel, aluminum and copper etc are driving solar developers and O&M providers towards advanced asset performance management (APM) solutions. Over the past few years, the importance of O&M has also penetrated the financial sector and investors have started to demand confidence that their investment would be safe for the long-term. This has further enabled fast development and deployment of advanced APM solutions. 

    Real-time fault detection for largest Spanish IPP.

    How SmartHelio envisions automation in asset management?

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    Automation ensures faster delivery and cost optimization. The solar industry has adopted automation in manufacturing, cleaning, site surveys and more. SmartHelio is working towardsits vision of a fully automated asset management solution including automation of O&M activities.

    Keeping asset managers and O&M teams at the center, SmartHelio has developed a real-time predictive analytics solution which diagnoses & predicts faults, raises tickets with detailed action plans and tracks important business KPIs like O&M cost savings and increase in revenue due to proactive maintenance interventions. Our team coming from the best R&D institutes in Europe such as Fraunhofer, EPFL, ETH Zurich etc are the brains behind this disruptive technology. 

    How SmartHelio’s predictive analytics is driving down O&M expenses?

    Cleaning being a big chunk of day to day O&M expenses, we have built a dynamic cleaning scheduler which provides cleaning schedules upto string level. These schedules could easily be used as inputs for cleaning robots. Our data driven cleaning schedules have been able to bring down cleaning costs by 20%. Credit for such advanced cost reduction techniques goes to the introduction of digital twin models for solar plant, deep-tech pattern recognition and signal processing.

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    Digital twin models take into account the physical parameters of the plant and site specific measurements which helps build an ideal performance benchmark, detect and predict anomalies in real-time. With our solution, we have been successfully able to predict IGBT issues in inverters, fuses blowing in string combiners, aggravation of panel-level issues using our IoT sensors and many more. The uniqueness of our digital twin models is that it is built using the knowledge of physics behind various faults. On top of our near accurate benchmarking, pattern recognition and signal processing techniques are the backbone for anomalies detection in our solution. These models are built with 10+ years of R&D and have been validated with our global clientele.

    Is SmartHelio solution tailored to the Indian solar industry problems? 

    India, being a tropical country, has its own set of challenges in maintaining solar assets due to the weather conditions. After doing a comprehensive study on various use cases coming directly from leading Indian solar developers, we built a grid-tied test facility in New Delhi where we conduct experimental research on the factors leading to performance issues. Our experienced team of data scientists, having expertise in solar PV systems, introduce various faults in the system to test and validate our algorithms in detecting and predicting anomalies, and accurately identifying the root cause of the fault(s). 

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    This year, at the REI Expo, we will be showcasing our real-time predictive analytics solution and we are inviting solar companies to visit our test facility in New Delhi. We want our partners to experience how we have developed our solution and how it can drive automation in their day-to-day activities for maximum O&M cost savings.

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