TY - JOUR
T1 - Wind-Driven Optimization Technique for Estimation of Solar Photovoltaic Parameters
AU - Binns, Richard
AU - Derick, Mathew
AU - Chinnappa Naidu, Rani
AU - Muthu, Rajesh
AU - Wang, Yue
AU - Busawon, Krishna
PY - 2018/1/1
Y1 - 2018/1/1
N2 - In order to increase the efficiency of the solar photovoltaic (PV) system, accurate electrical modeling of the system under different environmental conditions is necessary. The double-diode electrical model of solar PV is known to be more accurate than its single diode model counterpart since it takes into account the effect of recombination. However, because of its nonlinear characteristics, the parameters of the double-diode model (DDM) have to be identified using optimization algorithms. In this paper, the wind-driven optimization (WDO) algorithm is proposed as a potential new method for identifying the parameters of a 12-parameter DDM of the solar PV. The accuracy and flexibility of the proposed method are verified using three different sets of data: first, experimental data at the controlled environmental condition; second, data sheet values of different solar PV modules; and third, real-time experimental data at the uncontrolled environmental condition. Additionally, the performance of the WDO is compared with other well-known existing optimization techniques. The obtained results show that the WDO algorithm can provide optimized values with reduced mean absolute error in power and reduced root mean square error for different types of solar PV modules at different environmental conditions. We show that the WDO can be confidently recommended as a reliable optimization algorithm for parameter estimation of solar PV model.
AB - In order to increase the efficiency of the solar photovoltaic (PV) system, accurate electrical modeling of the system under different environmental conditions is necessary. The double-diode electrical model of solar PV is known to be more accurate than its single diode model counterpart since it takes into account the effect of recombination. However, because of its nonlinear characteristics, the parameters of the double-diode model (DDM) have to be identified using optimization algorithms. In this paper, the wind-driven optimization (WDO) algorithm is proposed as a potential new method for identifying the parameters of a 12-parameter DDM of the solar PV. The accuracy and flexibility of the proposed method are verified using three different sets of data: first, experimental data at the controlled environmental condition; second, data sheet values of different solar PV modules; and third, real-time experimental data at the uncontrolled environmental condition. Additionally, the performance of the WDO is compared with other well-known existing optimization techniques. The obtained results show that the WDO algorithm can provide optimized values with reduced mean absolute error in power and reduced root mean square error for different types of solar PV modules at different environmental conditions. We show that the WDO can be confidently recommended as a reliable optimization algorithm for parameter estimation of solar PV model.
KW - Adaptive electrical model
KW - mean absolute error in power (MAEP)
KW - parameter estimation
KW - root mean square error (RMSE)
KW - wind-driven optimization (WDO)
U2 - 10.1109/JPHOTOV.2017.2769000
DO - 10.1109/JPHOTOV.2017.2769000
M3 - Article
VL - 8
SP - 248
EP - 256
JO - IEEE Journal of Photovoltaics
JF - IEEE Journal of Photovoltaics
SN - 2156-3381
IS - 1
ER -