Solar forecasting using machine learned cloudiness classification

Hamann, Hendrik F.; Khabibrakhmanov, Ildar; Kim, Younghun; Lu, Siyuan

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Title: 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:: Hamann, Hendrik F.; Khabibrakhmanov, Ildar; Kim, Younghun; Lu, Siyuan

Issue Date:: Tue Apr 12 00:00:00 EDT 2022

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

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G - PHYSICS G01 - MEASURING G01W - METEOROLOGY
G01W1/10 - Devices for predicting weather conditions
G01W1/12 - Sunshine duration recorders

G - PHYSICS G06 - COMPUTING G06N - COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
G06N20/00 - Machine learning

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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.

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                    Hamann, Hendrik F., Khabibrakhmanov, Ildar, Kim, Younghun, & Lu, Siyuan. Solar forecasting using machine learned cloudiness classification.  United States.

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                    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.

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@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         = {Tue Apr 12 00:00:00 EDT 2022},

  month        = {Tue Apr 12 00:00:00 EDT 2022}

}

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Similar Records

Title: Solar forecasting using machine learned cloudiness classification

Abstract

Citation Formats

Method for predicting outputs of photovoltaic devices based on two-dimensional fourier analysis and seasonal auto-regression patent, January 2015

Multi-Model Blending patent-application, December 2015

An analytical comparison of four approaches to modelling the daily variability of solar irradiance using meteorological records journal, December 2014

Method and System for Solar Power Forecasting patent-application, September 2018

A Weather-Based Hybrid Method for 1-Day Ahead Hourly Forecasting of PV Power Output journal, July 2014

Predicting Solar Irradiance Using Time Series Neural Networks journal, January 2014

Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe journal, August 2013

Solar radiation forecast with machine learning conference, July 2016

Operating a solar power generating system patent, October 2018

Weather and Satellite Model for Estimating Solar Irradiance patent-application, June 2013

A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting journal, June 2013

Systems and Methods for Forecasting Solar Power patent-application, November 2011

Machine Learning Approach for Analysis and Prediction of Cloud Particle Size and Shape Distribution patent-application, October 2014

Predicting Solar Power Generation Using Semi-Supervised Learning patent-application, October 2017

New types of simple non-linear models to compute solar global irradiance from cloud cover amount journal, September 2014

Long-term solar generation forecasting conference, May 2016

Apparatus and method for predicting solar irradiance variation patent, December 2014

System and Methods for Model Based Solar Power Management patent-application, May 2014

Online 24-h solar power forecasting based on weather type classification using artificial neural network journal, November 2011

Methods of Using Generalized Order Differentiation and Integration of Input Variables to Forecast Trends patent-application, February 2013

Computer-implemented system and method for inferring operational specifications of a photovoltaic power generation system patent, March 2014

Systems and Methods for Simulating Time Phased Solar Irradiance Plots patent-application, July 2015

Method for predicting outputs of photovoltaic devices based on two-dimensional fourier analysis and seasonal auto-regression
patent, January 2015

Multi-Model Blending
patent-application, December 2015

An analytical comparison of four approaches to modelling the daily variability of solar irradiance using meteorological records
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Method and System for Solar Power Forecasting
patent-application, September 2018

A Weather-Based Hybrid Method for 1-Day Ahead Hourly Forecasting of PV Power Output
journal, July 2014

Predicting Solar Irradiance Using Time Series Neural Networks
journal, January 2014

Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe
journal, August 2013

Solar radiation forecast with machine learning
conference, July 2016

Operating a solar power generating system
patent, October 2018

Weather and Satellite Model for Estimating Solar Irradiance
patent-application, June 2013

A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting
journal, June 2013

Systems and Methods for Forecasting Solar Power
patent-application, November 2011

Machine Learning Approach for Analysis and Prediction of Cloud Particle Size and Shape Distribution
patent-application, October 2014

Predicting Solar Power Generation Using Semi-Supervised Learning
patent-application, October 2017

New types of simple non-linear models to compute solar global irradiance from cloud cover amount
journal, September 2014

Long-term solar generation forecasting
conference, May 2016

Apparatus and method for predicting solar irradiance variation
patent, December 2014

System and Methods for Model Based Solar Power Management
patent-application, May 2014

Online 24-h solar power forecasting based on weather type classification using artificial neural network
journal, November 2011

Methods of Using Generalized Order Differentiation and Integration of Input Variables to Forecast Trends
patent-application, February 2013

Computer-implemented system and method for inferring operational specifications of a photovoltaic power generation system
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Systems and Methods for Simulating Time Phased Solar Irradiance Plots
patent-application, July 2015