A generalized model for short-term forecasting of solar irradiance

Jesus Lago Garcia; Karel De Brabandere; Fjo De Ridder; Bart De Schutter

doi:10.1109/CDC.2018.8618693

A generalized model for short-term forecasting of solar irradiance

Jesus Lago Garcia, Karel De Brabandere, Fjo De Ridder, Bart De Schutter

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

1 Citation (Scopus)

39 Downloads (Pure)

Abstract

In recent years, as the share of solar power in the electrical grid has been increasing, accurate methods for forecasting solar irradiance have become necessary to manage the electrical grid. More specifically, as solar generators are geographically dispersed, it is very important to have general models that can predict solar irradiance without the need of ground data. In this paper, we propose a novel technique that can accomplish that: using satellite images, the proposed model is able to forecast solar irradiance without the need of ground measurements. To illustrate the performance of the proposed model, we consider 15 locations in The Netherlands, and we show that the proposed model is as accurate as local models that are individually trained with ground data.

Original language	English
Title of host publication	Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018)
Place of Publication	Piscataway, NJ, USA
Publisher	IEEE
Pages	3165-3170
ISBN (Print)	978-1-5386-1395-5
DOIs	https://doi.org/10.1109/CDC.2018.8618693
Publication status	Published - 2018
Event	CDC 2018: 57th IEEE Conference on Decision and Control - Miami, United States Duration: 17 Dec 2018 → 19 Dec 2018

Conference

Conference	CDC 2018: 57th IEEE Conference on Decision and Control
Country/Territory	United States
City	Miami
Period	17/12/18 → 19/12/18

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

Predictive models
Data models
Forecasting
Computational modeling
Satellites
Weather forecasting
Numerical models

Access to Document

10.1109/CDC.2018.8618693

08618693Final published version, 380 KB

Cite this

@inproceedings{7067624ab8c1474c9a73ceee922bac85,

title = "A generalized model for short-term forecasting of solar irradiance",

abstract = "In recent years, as the share of solar power in the electrical grid has been increasing, accurate methods for forecasting solar irradiance have become necessary to manage the electrical grid. More specifically, as solar generators are geographically dispersed, it is very important to have general models that can predict solar irradiance without the need of ground data. In this paper, we propose a novel technique that can accomplish that: using satellite images, the proposed model is able to forecast solar irradiance without the need of ground measurements. To illustrate the performance of the proposed model, we consider 15 locations in The Netherlands, and we show that the proposed model is as accurate as local models that are individually trained with ground data.",

keywords = "Predictive models, Data models, Forecasting, Computational modeling, Satellites, Weather forecasting, Numerical models",

author = "{Lago Garcia}, Jesus and {De Brabandere}, Karel and {De Ridder}, Fjo and {De Schutter}, Bart",

note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; CDC 2018: 57th IEEE Conference on Decision and Control ; Conference date: 17-12-2018 Through 19-12-2018",

year = "2018",

doi = "10.1109/CDC.2018.8618693",

language = "English",

isbn = "978-1-5386-1395-5",

pages = "3165--3170",

booktitle = "Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018)",

publisher = "IEEE",

address = "United States",

}

Lago Garcia, J, De Brabandere, K, De Ridder, F & De Schutter, B 2018, A generalized model for short-term forecasting of solar irradiance. in Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018). IEEE, Piscataway, NJ, USA, pp. 3165-3170, CDC 2018: 57th IEEE Conference on Decision and Control, Miami, United States, 17/12/18. https://doi.org/10.1109/CDC.2018.8618693

A generalized model for short-term forecasting of solar irradiance. / Lago Garcia, Jesus; De Brabandere, Karel; De Ridder, Fjo et al.
Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018). Piscataway, NJ, USA: IEEE, 2018. p. 3165-3170.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - A generalized model for short-term forecasting of solar irradiance

AU - Lago Garcia, Jesus

AU - De Brabandere, Karel

AU - De Ridder, Fjo

AU - De Schutter, Bart

N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2018

Y1 - 2018

N2 - In recent years, as the share of solar power in the electrical grid has been increasing, accurate methods for forecasting solar irradiance have become necessary to manage the electrical grid. More specifically, as solar generators are geographically dispersed, it is very important to have general models that can predict solar irradiance without the need of ground data. In this paper, we propose a novel technique that can accomplish that: using satellite images, the proposed model is able to forecast solar irradiance without the need of ground measurements. To illustrate the performance of the proposed model, we consider 15 locations in The Netherlands, and we show that the proposed model is as accurate as local models that are individually trained with ground data.

AB - In recent years, as the share of solar power in the electrical grid has been increasing, accurate methods for forecasting solar irradiance have become necessary to manage the electrical grid. More specifically, as solar generators are geographically dispersed, it is very important to have general models that can predict solar irradiance without the need of ground data. In this paper, we propose a novel technique that can accomplish that: using satellite images, the proposed model is able to forecast solar irradiance without the need of ground measurements. To illustrate the performance of the proposed model, we consider 15 locations in The Netherlands, and we show that the proposed model is as accurate as local models that are individually trained with ground data.

KW - Predictive models

KW - Data models

KW - Forecasting

KW - Computational modeling

KW - Satellites

KW - Weather forecasting

KW - Numerical models

U2 - 10.1109/CDC.2018.8618693

DO - 10.1109/CDC.2018.8618693

M3 - Conference contribution

SN - 978-1-5386-1395-5

SP - 3165

EP - 3170

BT - Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018)

PB - IEEE

CY - Piscataway, NJ, USA

T2 - CDC 2018: 57th IEEE Conference on Decision and Control

Y2 - 17 December 2018 through 19 December 2018

ER -

A generalized model for short-term forecasting of solar irradiance

Abstract

Conference

Bibliographical note

Keywords

Access to Document

Fingerprint

Cite this