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successive reference outputs form the MPPT and hence deteriorating dynamic
performance [3,4]. Fuzzy Logic Control (FLC) has been used in MPPT, for this
method is appropriate for non-linear control. However, FLC with fixed parame-
ters is inadequate in application where the operating conditions change in a wide
range and the available expert knowledge is not reliable. Adaptive Fuzzy Logic
Control can solve this problem because it can re-adjust the fuzzy parameters
to obtain optimum performance, but the computation cost is much higher than
conventional FLC [5].
In this paper, according to the uniqueness of MPP in specific conditions and
the PV system's non-linear characteristics, the T-G-P model is discussed. The
predictive controller is designed based on the PV energy converter mixed logic
dynamic model using hybrid system theory. At last, the simulation results verify
the validity of the model and the effectiveness of the proposed controller.
U−I And U−P
10
120
maximum power point
8
90
6
60
4
3 0
2
0
25 0
0
0
5
5
10
10
15
15
20
20
25
Array Voltage(V)
Fig. 1. U-I and U-P characteristics of photovoltaic cell
2 Photovoltaic Cell and T-G-P Model
The physical structure of a photovoltaic cell is similar to that of a diode in which
the p-n junction is subjected to sun exposure. When illumination and environ-
ment keep invariable, photovoltaic cell is a non-linear DC power. Photovoltaic
cell's mathematic model could be given as follows [6]:
I O [exp( V + IR
aV T
( V + IR s
R p
I = I PV
)
1]
)
(1)
where I pv is the current generated by the incidence of light; I o is the reverse sat-
uration current; a is the impact factor of the diode(usually 3-5); R s is the series
resistance; R p is the parallel resistance; q is the electron charge, which has con-
stant value of 1 . 6
10 19 C ; T is the temperature of the p-n junction in q ; k is the
Bolzmann constant (1 . 38
×
10 23 J/K ).
×
 
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