A regression based hourly day ahead solar irradiance forecasting model by labview using cloud cover data

Oguzhan Ceylan; Michael Starke; Phil Irminger; Ben Ollis; Kevin Tomsovic

doi:10.1109/ELECO.2015.7394592

A regression based hourly day ahead solar irradiance forecasting model by labview using cloud cover data

Oguzhan Ceylan, Michael Starke, Phil Irminger, Ben Ollis, Kevin Tomsovic

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

This paper applies a regression based numerical method for photovoltaic power output hourly forecast. The method uses a historical data composed of irradiance, azimuth, zenith angle and time of day information. In every run of the forecast program, publicly available cloud cover forecast data for the following day is obtained, and by using a numerical regression based method a function is fit. Then by using the publicly available temperature forecast data, forecasted irradiance data, and computed solar position (zenith, azimuth) data, both power output and temperature module output of PV array is computed. Numerical forecast results show that, they are in accordance with the actual data.

Original language	English
Title of host publication	ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	406-410
Number of pages	5
ISBN (Electronic)	9786050107371
DOIs	https://doi.org/10.1109/ELECO.2015.7394592
State	Published - Jan 28 2016
Event	9th International Conference on Electrical and Electronics Engineering, ELECO 2015 - Bursa, Turkey Duration: Nov 26 2015 → Nov 28 2015

Publication series

Name	ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering

Conference

Conference	9th International Conference on Electrical and Electronics Engineering, ELECO 2015
Country/Territory	Turkey
City	Bursa
Period	11/26/15 → 11/28/15

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ELECO.2015.7394592

Cite this

Ceylan, O., Starke, M., Irminger, P., Ollis, B., & Tomsovic, K. (2016). A regression based hourly day ahead solar irradiance forecasting model by labview using cloud cover data. In ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering (pp. 406-410). Article 7394592 (ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ELECO.2015.7394592

Ceylan, Oguzhan ; Starke, Michael ; Irminger, Phil et al. / A regression based hourly day ahead solar irradiance forecasting model by labview using cloud cover data. ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 406-410 (ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering).

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title = "A regression based hourly day ahead solar irradiance forecasting model by labview using cloud cover data",

abstract = "This paper applies a regression based numerical method for photovoltaic power output hourly forecast. The method uses a historical data composed of irradiance, azimuth, zenith angle and time of day information. In every run of the forecast program, publicly available cloud cover forecast data for the following day is obtained, and by using a numerical regression based method a function is fit. Then by using the publicly available temperature forecast data, forecasted irradiance data, and computed solar position (zenith, azimuth) data, both power output and temperature module output of PV array is computed. Numerical forecast results show that, they are in accordance with the actual data.",

author = "Oguzhan Ceylan and Michael Starke and Phil Irminger and Ben Ollis and Kevin Tomsovic",

note = "Publisher Copyright: {\textcopyright} 2015 Chamber of Electrical Engineers of Turkey.; 9th International Conference on Electrical and Electronics Engineering, ELECO 2015 ; Conference date: 26-11-2015 Through 28-11-2015",

year = "2016",

month = jan,

day = "28",

doi = "10.1109/ELECO.2015.7394592",

language = "English",

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Ceylan, O, Starke, M, Irminger, P, Ollis, B & Tomsovic, K 2016, A regression based hourly day ahead solar irradiance forecasting model by labview using cloud cover data. in ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering., 7394592, ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering, Institute of Electrical and Electronics Engineers Inc., pp. 406-410, 9th International Conference on Electrical and Electronics Engineering, ELECO 2015, Bursa, Turkey, 11/26/15. https://doi.org/10.1109/ELECO.2015.7394592

A regression based hourly day ahead solar irradiance forecasting model by labview using cloud cover data. / Ceylan, Oguzhan; Starke, Michael; Irminger, Phil et al.
ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering. Institute of Electrical and Electronics Engineers Inc., 2016. p. 406-410 7394592 (ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A regression based hourly day ahead solar irradiance forecasting model by labview using cloud cover data

AU - Ceylan, Oguzhan

AU - Starke, Michael

AU - Irminger, Phil

AU - Ollis, Ben

AU - Tomsovic, Kevin

PY - 2016/1/28

Y1 - 2016/1/28

N2 - This paper applies a regression based numerical method for photovoltaic power output hourly forecast. The method uses a historical data composed of irradiance, azimuth, zenith angle and time of day information. In every run of the forecast program, publicly available cloud cover forecast data for the following day is obtained, and by using a numerical regression based method a function is fit. Then by using the publicly available temperature forecast data, forecasted irradiance data, and computed solar position (zenith, azimuth) data, both power output and temperature module output of PV array is computed. Numerical forecast results show that, they are in accordance with the actual data.

AB - This paper applies a regression based numerical method for photovoltaic power output hourly forecast. The method uses a historical data composed of irradiance, azimuth, zenith angle and time of day information. In every run of the forecast program, publicly available cloud cover forecast data for the following day is obtained, and by using a numerical regression based method a function is fit. Then by using the publicly available temperature forecast data, forecasted irradiance data, and computed solar position (zenith, azimuth) data, both power output and temperature module output of PV array is computed. Numerical forecast results show that, they are in accordance with the actual data.

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U2 - 10.1109/ELECO.2015.7394592

DO - 10.1109/ELECO.2015.7394592

M3 - Conference contribution

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T3 - ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering

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EP - 410

BT - ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering

PB - Institute of Electrical and Electronics Engineers Inc.

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Ceylan O, Starke M, Irminger P, Ollis B, Tomsovic K. A regression based hourly day ahead solar irradiance forecasting model by labview using cloud cover data. In ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering. Institute of Electrical and Electronics Engineers Inc. 2016. p. 406-410. 7394592. (ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering). doi: 10.1109/ELECO.2015.7394592

A regression based hourly day ahead solar irradiance forecasting model by labview using cloud cover data

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