ALEXANDRIA, Va., Jan. 4 -- International Business Machines, Armonk, New York, has been assigned a patent (9,857,778) developed by four co-inventors for "forecasting solar power generation using real-time power data, weather data, and complexity-based similarity factors." The co-inventors are Ildar Khabibrakhmanov, Syosset, New York, Tarun Kumar, Lake Mohegan, New York, Mark A. Lavin, Katonah, New York, and Rui Zhang, Ossining, New York. The abstract states: "Embodiments are directed to a computer-implemented method, computer system, and computer program product of forecasting power generation. The method includes analyzing a set of historical power generation data. Thereafter a set of clusters is determined wherein each cluster of the set of clusters represents power generated during the time period. Then receiving actual power generation data for a portion of the time period. Thereafter, determining which cluster of the set of clusters contains historical power generation data that is most similar to the actual power generation data. Then forecasting power generation for a remainder of the time period, using the historical power generation data of the cluster."
The patent application was filed on Oct. 7, 2016 (15/288,707). The full-text of the patent can be found at http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=9,857,778.PN.&OS=PN/9,857,778&RS=PN/9,857,778
Written by Amal Ahmed; edited by Sudarshan Harpal.