TY - GEN
T1 - Forecasting I-V characteristic of PV modules considering real operating conditions using numerical method and deep learning
AU - Tuyen, Nguyen Duc
AU - Thinh, Le Viet
AU - Huu, Vu Xuan Son
AU - Fujita, Goro
N1 - Publisher Copyright:
© 2020 IEEE
PY - 2020/11
Y1 - 2020/11
N2 - The current-voltage (I-V) characteristic plays a dominant role in operating a photovoltaic (PV) system as it provides information about the performance of the system. Since the output quality of PV depends mainly on the solar irradiation and cell temperature, modeling the I-V relationship regarding solar irradiation and cell temperature need to be addressed. In this paper, the long short-term memory (LSTM) model is adopted to forecast the solar irradiation and temperature of a PV module. After that, a PV module model called one-diode model is introduced to identify the I-V characteristic of the PV module, which only employs the data forecasted by the LSTM-based model and the manufactured data. Since this method combines the strengths of two techniques, it solves the uncertainty of meteorological data as well as provides an effective method to model the I-V output quality of the PV module.
AB - The current-voltage (I-V) characteristic plays a dominant role in operating a photovoltaic (PV) system as it provides information about the performance of the system. Since the output quality of PV depends mainly on the solar irradiation and cell temperature, modeling the I-V relationship regarding solar irradiation and cell temperature need to be addressed. In this paper, the long short-term memory (LSTM) model is adopted to forecast the solar irradiation and temperature of a PV module. After that, a PV module model called one-diode model is introduced to identify the I-V characteristic of the PV module, which only employs the data forecasted by the LSTM-based model and the manufactured data. Since this method combines the strengths of two techniques, it solves the uncertainty of meteorological data as well as provides an effective method to model the I-V output quality of the PV module.
KW - Deep learning
KW - I-V characteristic
KW - Long short-term memory (LSTM)
KW - One-diode model (ODM)
KW - Photovoltaic module
UR - http://www.scopus.com/inward/record.url?scp=85102779252&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85102779252&partnerID=8YFLogxK
U2 - 10.1109/SGES51519.2020.00102
DO - 10.1109/SGES51519.2020.00102
M3 - Conference contribution
AN - SCOPUS:85102779252
T3 - Proceedings - 2020 International Conference on Smart Grids and Energy Systems, SGES 2020
SP - 544
EP - 549
BT - Proceedings - 2020 International Conference on Smart Grids and Energy Systems, SGES 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 International Conference on Smart Grids and Energy Systems, SGES 2020
Y2 - 23 November 2020 through 26 November 2020
ER -