{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/statistical-clear-sky-fitting-algorithm","title":"Statistical Clear Sky Fitting Algorithm","arxiv_id":"1907.08279","date":"2019-07-18","proceeding":null,"authors":[],"abstract":"We present an algorithm that estimates a clear sky performance signal from\nthe measured power of a PV system. The algorithm uses only observed power\noutput, and assumes no knowledge of weather, irradiance data, or system\nconfiguration metadata. This is a novel approach to understanding the clear sky\nbehavior of an installed PV system, that does not rely on traditional\natmospheric and geometric modeling techniques.","url_abs":"http://arxiv.org/abs/1907.08279v1","url_pdf":"http://arxiv.org/pdf/1907.08279v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"statistical-clear-sky-fitting-algorithm","repo_url":"https://github.com/bmeyers/StatisticalClearSky","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"statistical-clear-sky-fitting-algorithm","repo_url":"https://github.com/slacgismo/StatisticalClearSky","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}