{"id":4338,"date":"2023-07-04T14:52:30","date_gmt":"2023-07-04T09:22:30","guid":{"rendered":"https:\/\/smarthelio.com\/?p=4338"},"modified":"2023-09-12T16:42:07","modified_gmt":"2023-09-12T11:12:07","slug":"predictive-analytics-for-solar-assets-maintenance","status":"publish","type":"post","link":"https:\/\/smarthelio.com\/predictive-analytics-for-solar-assets-maintenance\/","title":{"rendered":"Demystifying predictive analytics and preventive maintenance in the solar industry"},"content":{"rendered":"
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T<\/span>he<\/span> rise of predictive analytics and preventive maintenance in the solar industry has gained significant <\/span>attention in recent years<\/span>. Indeed, i<\/span>n a rapidly expanding industry, with the US solar market projected to grow by 20% and Europe’s solar capacity estimated to double by 2030, the urgent need for digitalization and predictive analytics becomes <\/span>evident<\/span> to effectively manage and ensure <\/span>optimal<\/span> performance of solar installations at scale.<\/span> <\/span><\/strong><\/p>\n However, amidst th<\/span>is constantly increasing <\/span>buzz<\/span><\/span>,<\/span><\/span><\/span> which <\/span>recently <\/span>reach<\/span>ed<\/span> a new <\/span>high<\/span> at Intersolar <\/span>Europe <\/span>2023<\/span>, there are misconceptions that <\/span>should <\/span>be addressed to <\/span>truly understand<\/span> the essence of these terms<\/span> and ensure we are all talking about the same thing<\/span>. <\/span><\/span>At<\/span> SmartHeli<\/span>o<\/span>, we are committed to<\/span> providin<\/span>g<\/span> accurat<\/span>e<\/span> and actionable insights to help solar industry stakeholders de-risk investments, maximize performance, and reduce costs.<\/span> Staying true to o<\/span>ur mission, i<\/span>n<\/span> this article we<\/span> will demystify predictive analytics and preventive maintenance and shed light on t<\/span>heir true <\/span>meaning.<\/span><\/span>\u00a0<\/span><\/p>\n Predictive analytics in the solar industry <\/span>is <\/span>not only <\/span>leveraging<\/span> historical <\/span>labelled<\/span> data and advanced algorithms to forecast <\/span>production<\/span> and predict <\/span>major <\/span>component<\/span> failures like <\/span>inverters<\/span>. <\/span>It also includes the understanding of the early signs of <\/span>underp<\/span>erformance<\/span> based on<\/span> system<\/span> behaviour<\/span> anomalies.<\/span> Predictive analytics encompasses the analysis of a fault<\/span>\u2019<\/span>s <\/span>behaviour<\/span> with time<\/span> and projected losses associated with it which helps in<\/span> prioritizing <\/span>the <\/span>proactive actions to be ta<\/span>ken.<\/span> <\/strong><\/span><\/p>\n By <\/span>analysing<\/span> past data, <\/span>understanding the real-time <\/span>electrical<\/span> patterns <\/span>in<\/span> combination with<\/span> weather patterns, solar irradiation, and system parameters, predictive analytics <\/strong><\/span>can <\/span>enable<\/span> the identification of potential issues before they cause significant <\/span>performance loss and <\/span>possible equipment<\/span> failures<\/span><\/strong>. <\/span>SmartHelio<\/span>\u2019s<\/span> Autopilot platform <\/span>uses<\/span> physics-informed AI<\/span>, <\/span>combining<\/span> M<\/span>achine <\/span>L<\/span>earning techniques with domain <\/span>expertise<\/span>,<\/span> to deliver reliable and <\/span>accurate<\/span> predictions and insights.<\/span><\/span>\u00a0<\/span><\/p>\n \u201cWhereas physics-based models are very good on post failure analysis, with more Machine Learning knowledge in our data warehouse we will then be able to recognise very small deviations at an early stage to have prediction on where your next fault may probably happen\u201d<\/span><\/i><\/p>\n \u2013 David Ebner, Project Engineer at VERBUND<\/strong><\/p>\n<\/blockquote>\n<\/h2>\n
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Understanding Predictive Analytics<\/span><\/span>\u00a0<\/span><\/strong><\/h2>\n
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