Artificial neural network based simplified one day ahead forecasting of solar photovoltaic power generation
Joint Authors
Khattak, Abraiz
Khan, M. Adam
Munir, Muhammad Asim
Imran, Kashif
Ulasyar, Abasin
Ullah, Nasim
Ul Haq, Azhar
Source
Journal of Engineering Research
Issue
Vol. 10, Issue 1 A (31 Mar. 2022), pp.175-189, 15 p.
Publisher
Kuwait University Academic Publication Council
Publication Date
2022-03-31
Country of Publication
Kuwait
No. of Pages
15
Main Subjects
Abstract EN
The intermittency of solar energy resources possesses a serious challenge in balancing the power generation and load demand.
To enhance the consistency of the system, it is crucial to forecast solar photovoltaic power.
Among numerous techniques, Artificial Neural Network (ANN) is an efficient tool that may help simplify this problem.
In this study, all 63 combinations of six input parameters, i.e., temperature, dew point, wind speed, cloud cover, relative humidity, and pressure, were applied one by one to ANN to forecast 24 hours ahead PV generation.
The power forecast results were obtained based on weather forecast data of 21 days sampled from the recorded forecasted data of 180 days.
To quantify the error between predicted and measured solar PV generation, Root Mean Squared Error (RMSE) was used, and the results of different input combinations were compared on basis of this statistical matrix.
The analysis showed that the generation is best predicted on two combinations : the first is comprising of temperature, dew point, relative humidity, and cloud cover, while the second consists of all six parameters.
And some of the combinations consisting of three parameters also resulted in RMSEs in close proximity of the least error value.
American Psychological Association (APA)
Munir, Muhammad Asim& Khattak, Abraiz& Imran, Kashif& Ulasyar, Abasin& Ullah, Nasim& Ul Haq, Azhar…[et al.]. 2022. Artificial neural network based simplified one day ahead forecasting of solar photovoltaic power generation. Journal of Engineering Research،Vol. 10, no. 1 A, pp.175-189.
https://search.emarefa.net/detail/BIM-1495021
Modern Language Association (MLA)
Munir, Muhammad Asim…[et al.]. Artificial neural network based simplified one day ahead forecasting of solar photovoltaic power generation. Journal of Engineering Research Vol. 10, no. 1 A (Mar. 2022), pp.175-189.
https://search.emarefa.net/detail/BIM-1495021
American Medical Association (AMA)
Munir, Muhammad Asim& Khattak, Abraiz& Imran, Kashif& Ulasyar, Abasin& Ullah, Nasim& Ul Haq, Azhar…[et al.]. Artificial neural network based simplified one day ahead forecasting of solar photovoltaic power generation. Journal of Engineering Research. 2022. Vol. 10, no. 1 A, pp.175-189.
https://search.emarefa.net/detail/BIM-1495021
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 187-189
Record ID
BIM-1495021