{"id":17329,"date":"2023-10-10T01:00:34","date_gmt":"2023-10-10T05:00:34","guid":{"rendered":"https:\/\/www.comtechadvisory.com\/blog\/open-climate-fix-forecasting-on-an-upward-trajectory\/"},"modified":"2023-10-10T01:00:34","modified_gmt":"2023-10-10T05:00:34","slug":"open-climate-fix-forecasting-on-an-upward-trajectory","status":"publish","type":"post","link":"https:\/\/www.comtechadvisory.com\/blog\/open-climate-fix-forecasting-on-an-upward-trajectory\/","title":{"rendered":"Open Climate Fix forecasting on an upward trajectory"},"content":{"rendered":"
\n

Open Climate Fix is a young company based in the UK, specializing in solar production forecasting through the application of AI models with their flagship product, quartz.solar. These forecasts leverage real-time data, and the coverage can span from individual solar farms to aggregations across regions such as the UK National Grid. The primary advantage of these forecasts arises from the integration of multiple data sources, coupled with a sophisticated ML framework. One of the co-founders of the company, Dan Travers, suggested that the high accuracy of their forecasts hinges on a comprehensive data foundation coming from three critical sources: real-time weather forecasts, satellite information, which includes cloud movement data updated every few minutes and real-time data from PV farms. The synergy of these external data sources is what makes their methodology truly distinctive, he says. Blending of weather and satellite data within sophisticated ML models enables to achieve high precision across the complete time horizon form next few hours to the day ahead. This ensures a strong position of Open Climate Fix within a competitive market for forecasting tools, Dan explained to me. \u00a0 This methodology involves a substantial volume of data, which can only be effectively managed within a… continue reading<\/a><\/p>\n

Continue reading Open Climate Fix forecasting on an upward trajectory<\/a>. This article appeared first on CTRM Center<\/a>.<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Open Climate Fix is a young company based in the UK, specializing in solar production forecasting through the application of AI models with their flagship product, quartz.solar. These forecasts leverage real-time data, and the coverage can span from individual solar farms to aggregations across regions such as the UK National Grid. The primary advantage of these forecasts arises from the integration of multiple data sources, coupled with a sophisticated ML framework. One of the co-founders of the company, Dan Travers, suggested that the high accuracy of their forecasts hinges on a comprehensive data foundation coming from three critical sources: real-time weather forecasts, satellite information, which includes cloud movement data updated every few minutes and real-time data from PV farms. The synergy of these external data sources is what makes their methodology truly distinctive, he says. Blending of weather and satellite data within sophisticated ML models enables to achieve high precision across the complete time horizon form next few hours to the day ahead. This ensures a strong position of Open Climate Fix within a competitive market for forecasting tools, Dan explained to me. \u00a0 This methodology involves a substantial volume of data, which can only be effectively managed within a… … continue reading<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[4],"tags":[],"acf":[],"yoast_head":"\nOpen Climate Fix forecasting on an upward trajectory | Commodity Technology Advisory<\/title>\n<meta name=\"description\" content=\"Open Climate Fix is a young company based in the UK, specializing in solar production forecasting through the application of AI models with their flagship\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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