Solar forecasting using machine learned cloudiness classification
Abstract
Methods and systems for predicting irradiance include learning a classification model using unsupervised learning based on historical irradiance data. The classification model is updated using supervised learning based on an association between known cloudiness states and historical weather data. A cloudiness state is predicted based on forecasted weather data. An irradiance is predicted using a regression model associated with the cloudiness state.
- Inventors:
- Issue Date:
- Research Org.:
- International Business Machines Corp., Armonk, NY (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1892823
- Patent Number(s):
- 11300707
- Application Number:
- 15/226,445
- Assignee:
- International Business Machines Corporation (Armonk, NY)
- Patent Classifications (CPCs):
-
G - PHYSICS G01 - MEASURING G01W - METEOROLOGY
G - PHYSICS G06 - COMPUTING G06N - COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- DOE Contract Number:
- EE0006017
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 08/02/2016
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Hamann, Hendrik F., Khabibrakhmanov, Ildar, Kim, Younghun, and Lu, Siyuan. Solar forecasting using machine learned cloudiness classification. United States: N. p., 2022.
Web.
Hamann, Hendrik F., Khabibrakhmanov, Ildar, Kim, Younghun, & Lu, Siyuan. Solar forecasting using machine learned cloudiness classification. United States.
Hamann, Hendrik F., Khabibrakhmanov, Ildar, Kim, Younghun, and Lu, Siyuan. Tue .
"Solar forecasting using machine learned cloudiness classification". United States. https://www.osti.gov/servlets/purl/1892823.
@article{osti_1892823,
title = {Solar forecasting using machine learned cloudiness classification},
author = {Hamann, Hendrik F. and Khabibrakhmanov, Ildar and Kim, Younghun and Lu, Siyuan},
abstractNote = {Methods and systems for predicting irradiance include learning a classification model using unsupervised learning based on historical irradiance data. The classification model is updated using supervised learning based on an association between known cloudiness states and historical weather data. A cloudiness state is predicted based on forecasted weather data. An irradiance is predicted using a regression model associated with the cloudiness state.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2022},
month = {4}
}
Works referenced in this record:
Method for predicting outputs of photovoltaic devices based on two-dimensional fourier analysis and seasonal auto-regression
patent, January 2015
- Zhang, Weihong; Nikovski, Daniel Nikolaev
- US Patent Document 8,942,959
Multi-Model Blending
patent-application, December 2015
- Hamann, Hendrik F.; Hwang, Youngdeok; van Kessel, Theodore G.
- US Patent Application 14/291,720; 2015/0347922 Al
An analytical comparison of four approaches to modelling the daily variability of solar irradiance using meteorological records
journal, December 2014
- Huang, Jing; Troccoli, Alberto; Coppin, Peter
- Renewable Energy, Vol. 72
Method and System for Solar Power Forecasting
patent-application, September 2018
- Pavlovski, Alexander; Anichkov, Dimitriy; Kostylev, Vladimit
- US Patent Application 15/755,373; 2018/0275314 Al
A Weather-Based Hybrid Method for 1-Day Ahead Hourly Forecasting of PV Power Output
journal, July 2014
- Yang, Hong-Tzer; Huang, Chao-Ming; Huang, Yann-Chang
- IEEE Transactions on Sustainable Energy, Vol. 5, Issue 3
Predicting Solar Irradiance Using Time Series Neural Networks
journal, January 2014
- Alzahrani, A.; Kimball, J. W.; Dagli, C.
- Procedia Computer Science, Vol. 36
Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe
journal, August 2013
- Perez, Richard; Lorenz, Elke; Pelland, Sophie
- Solar Energy, Vol. 94
Solar radiation forecast with machine learning
conference, July 2016
- Shao, Xiaoyan; Lu, Siyuan; Hamann, Hendrik F.
- 2016 23rd International Workshop on Active-Matrix Flatpanel Displays and Devices (AM-FPD)
Operating a solar power generating system
patent, October 2018
- He, Dawei; Alimohammadi, Shahrouz
- US Patent Document 10,103,548
Weather and Satellite Model for Estimating Solar Irradiance
patent-application, June 2013
- Herzig, Michael; Williams, Matthew; Kerrington, Shawn
- US Patent Application 13/623,240; 2013/0166266 Al
A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting
journal, June 2013
- Mathiesen, Patrick; Collier, Craig; Kleissl, Jan
- Solar Energy, Vol. 92
Systems and Methods for Forecasting Solar Power
patent-application, November 2011
- Ropp, Michael; Hummel, Steven G.
- US Patent Application 13/103,629; 2011/0282514 Al
Machine Learning Approach for Analysis and Prediction of Cloud Particle Size and Shape Distribution
patent-application, October 2014
- Hamann, Hendrik F.; Lu, Siyuan
- US Patent Application 13/960,966; 2014/0324352 Al
Predicting Solar Power Generation Using Semi-Supervised Learning
patent-application, October 2017
- Cipriani, James P.; Khabibrakhmanov, Ildar; Kim, Younghun
- US Patent Application 15/083,661; 2017/0286838 Al
New types of simple non-linear models to compute solar global irradiance from cloud cover amount
journal, September 2014
- Badescu, Viorel; Dumitrescu, Alexandru
- Journal of Atmospheric and Solar-Terrestrial Physics, Vol. 117
Long-term solar generation forecasting
conference, May 2016
- Alanazi, Mohana; Alanazi, Abdulaziz; Khodaei, Amin
- 2016 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)
Apparatus and method for predicting solar irradiance variation
patent, December 2014
- Yao, Yi; Tu, Peter Henry; Chang, Ming-Ching
- US Patent Document 8,923,567
System and Methods for Model Based Solar Power Management
patent-application, May 2014
- Meagher, Kevin; Radibratovic, Brian; Chudgar, Raj
- US Patent Application 14/081,487; 2014/0136178 Al
Online 24-h solar power forecasting based on weather type classification using artificial neural network
journal, November 2011
- Chen, Changsong; Duan, Shanxu; Cai, Tao
- Solar Energy, Vol. 85, Issue 11
Methods of Using Generalized Order Differentiation and Integration of Input Variables to Forecast Trends
patent-application, February 2013
- Coimbra, Carlos F. M.
- US Patent Application 13/641,083; 2013/0054662 Al
Computer-implemented system and method for inferring operational specifications of a photovoltaic power generation system
patent, March 2014
- Hoff, Thomas E.
- US Patent Document 8,682,585
Systems and Methods for Simulating Time Phased Solar Irradiance Plots
patent-application, July 2015
- Ferrer, Alberto
- US Patent Application 14/160,867; 2015/0205008 Al