Invention Grant
- Patent Title: Solar power forecasting using mixture of probabilistic principal component analyzers
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Application No.: US15320899Application Date: 2015-06-29
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Publication No.: US10386544B2Publication Date: 2019-08-20
- Inventor: Chao Yuan , Amit Chakraborty , Holger Hackstein
- Applicant: Siemens Aktiengesellschaft
- Applicant Address: DE München
- Assignee: SIEMENS AKTIENGESELLSCHAFT
- Current Assignee: SIEMENS AKTIENGESELLSCHAFT
- Current Assignee Address: DE München
- International Application: PCT/US2015/038240 WO 20150629
- International Announcement: WO2016/003861 WO 20160107
- Main IPC: G01W1/10
- IPC: G01W1/10 ; G06Q10/04 ; G06N7/00 ; G01W1/12 ; G06F17/18 ; G06Q50/06

Abstract:
A method for solar forecasting includes receiving a plurality of solar energy data as a function of time of day at a first time, forecasting from the solar energy data a mode, where the mode is a sunny day, a cloudy day, or an overcast day, and the forecast predicts the mode for a next solar energy datum, receiving the next solar energy datum, updating a probability distribution function (pdf) of the next solar energy datum given the mode, updating a pdf of the mode for the next solar energy datum from the updated pdf of the new solar energy datum given the mode, forecasting a plurality of future unobserved solar energy data from the updated pdf of the mode, where the plurality of future unobserved solar energy data and the plurality of solar energy data have a Gaussian distribution for a given mode determined from training data.
Public/Granted literature
- US20170205537A1 SOLAR POWER FORECASTING USING MIXTURE OF PROBABILISTIC PRINCIPAL COMPONENT ANALYZERS Public/Granted day:2017-07-20
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