Parameter estimation results

The key parameters on the manufacturer datasheet for the BP 380 PV module are given in Table 2.1. Using the three key parameter estimation techniques, identified in Section 2.6, programs have been developed in MATLAB to provide a baseline to use as model parameters for the SDM to model the BP 380 PV module. These estimated parameters are firstly used to validate the simulation model with the experimental data and then the parameters are refined manually to improve the curve-fitting of the model particularly around the key point of interest, the MPP.

The results for the three applied parameter estimation techniques are given Table 2.2.

Table 2.1: BP380 datasheet parameters.

Parameter Value Voc 22.1 V Isc 4.8 A Vmpp 17.6 V Impp 4.55 A Pmpp 80 W Temperature coefficient of Isc (0.065±0.015)%/◦C Temperature coefficient of Voc −(80±10)mV /◦C

Table 2.2: Parameters estimated.

Method One Method Two Method Three

Vt 0.8568 0.8328 - Rs 0.4318 Ω 0.4380 Ω - Rsh 3.554 kΩ 1.083 kΩ - I0 0.0307 nA 14.3 pA 2.48 µA Iph 4.8001 A 4.80 A 4.80 A A 0.9260 0.9 1.65

When the parameters from method one and method two are applied in the simulation model for STC (1000 W/m2_{, 25} ◦_{C) and the equation for the}

ISDM case (method three) are applied on these conditions, the I-V and P-V characteristics given in Figs. 2.6 and 2.7 are obtained. Visually, the I-V and P-V characteristics produced using method one and method two are identical despite the difference in parameter values. The characteristics produced using method three are very different to those for method one and method two particularly around the MPP. Method three predicts a higher MPP power at a higher voltage. It can be seen from looking at the characteristic that method three is a poor fit, as it predicts that the MPP voltage will be about 0.8 V higher than that given in the datasheet. In all subsequent analysis, only method one and method two will be considered.

To assess how well the characteristics produced using method one and method two match, for each voltage the difference in the current and power in the char- acteristics produced using each method are calculated and graphed against the voltage. This is shown in Figs. 2.8 and 2.9, for the current and power difference, respectively.

Figure 2.6: I-V characteristics produced using method one, two and three parameter estimation techniques.

Figure 2.7: P-V characteristics produced using method one, two and three parameter estimation techniques.

Figure 2.8: Error in current between method one and method two characteristics.

To assess the sensitivity of the I-V and P-V characteristics to variations in the parameters, a ± 5% and ±10% variation is applied to each parameter from method one in isolation to illustrate the effects.

The effect of varying the diode ideality factor is shown in Fig. 2.10. It can be seen that decreasing the diode ideality factor moves the MPP to a lower voltage and lower power. Increasing the diode ideality factor increase the power at the MPP and moves the MPP to a higher voltage. The diode ideality factor is also seen to affect the open-circuit voltage.

(a) I-V.

(b) P-V.

Figure 2.10: I-V and P-V characteristic variations for varying diode ideality factor.

The variation of the I-V and P-V characteristics with changing shunt resistance are shown in Fig. 2.11. The characteristics appear identical in all cases indicating that tuning the shunt resistance will not assist in improving the fitting of the model to experimental characteristics.

(a) I-V.

(b) P-V.

Figure 2.12 shows the variation in the I-V and P-V characteristics for varying light generated current. As is expected, because the light generated current is related to the short-circuit current, a change is observed in the short circuit current and the behaviour in the current source region. Additionally, a de- crease in the light generated current results in a decrease in the power at the MPP.

(a) I-V.

(b) P-V.

Figure 2.12: I-V and P-V characteristic variations for varying light generated current.

In Fig. 2.13, the effect of varying the diode saturation current is explored. The results show that the diode saturation current has a very limited effect on the I-V and P-V characteristics.

(a) I-V.

(b) P-V.

(a) I-V.

(b) P-V.

Figure 2.14: I-V and P-V characteristic variations for varying series resistance.

Figure 2.14 shows the effect of varying the series resistance. It can be seen that increasing the series resistance will decrease the power at the MPP slightly. This agrees with the literature, because as a result of cell degradation, the maximum power will decrease with time and the series resistance will increase [74]. The series resistance may increase due to a number of factors including corrosion of the modules and the internal connectors, degradation of the silicon and breaking

NREL assessing the degradation of different types of modules has shown that a degradation of around 0.5%/year occurs, with this resulting in a decrease in short-circuit current and with a clear increase in the series resistance [77].

These results suggest that the diode ideality factor, A, and the series resistance,

Rs are the most suitable parameters to modify to improve the model fit to the

experimental data. The light generated current Iph is also shown to have a

considerable effect on the characteristics, however will be held constant at 4.8001 A throughout the analysis. This enables a correction factor for the irradiance to be defined as the sensor module and test modules may not be exactly aligned during testing.