ABSTRACT:
Under partial shading conditions, multiple peaks are
observed in the power–voltage (P–V ) characteristic curve of a photovoltaic
(PV) array, and the conventional maximum power point tracking (MPPT) algorithms
may fail to track the global maximum power point (GMPP). Therefore, this paper
proposes a modified incremental conductance (Inc Cond) algorithm that is able
to track the GMPP under partial shading conditions and load variation. A novel
algorithm is introduced to modulate the duty cycle of the dc–dc converter in
order to ensure fast MPPT process. Simulation and hardware implementation are
carried out to evaluate the effectiveness of the proposed algorithm under partial
shading and load variation. The results show that the proposed algorithm is
able to track the GMPP accurately under different types of partial shading
conditions, and the response during variation of load and solar irradiation are
faster than the conventional Inc Cond algorithm. Hence, the effectiveness of the
proposed algorithm under partial shading condition and load variation is
validated in this paper.
KEYWORDS:
1.
DC–DC
converter
2.
Incremental
conductance (Inc Cond)
3.
Maximum power
point tracking (MPPT)
4.
Partial
shading
5.
Photovoltaic
(PV) system.
SOFTWARE: MATLAB/SIMULINK
BLOCK DIAGRAM:
CONCLUSION:
In
this paper, a modified Inc Cond algorithm has been used to track the GMPP for
the PV array under partial shading conditions and also load variation. A novel
algorithm is used to modulate the duty cycle of the converter, and thus, the
tracking speed is improved. The simulation and experimental results showed that
the proposed algorithm is able to track the GMPP accurately and thus reduces
the power losses faced by the conventional algorithm. The experimental results
also showed that the proposed algorithm is able to respond rapidly and accurately
to the variation in the load and the solar irradiation during partial shading
conditions. As a conclusion, the proposed algorithm performed better in
tracking the GMPP under partial shading conditions and load variation, as
compared with the conventional Inc Cond algorithm.
REFERENCES:
[1]
S. Mekhilef, R. Saidur, and A. Safari, “A review on solar energy use in industries,”
Renew. Sustain. Energy Rev., vol. 15, no. 4, pp. 1777–1790, May 2011.
[2]
S. Mekhilef, A. Safari, W. E. S. Mustaffa, R. Saidur, R. Omar, and M. A. A.
Younis, “Solar energy in Malaysia: Current state and prospects,” Renew.
Sustain. Energy Rev., vol. 16, no. 1, pp. 386–396, Jan. 2012.
[3]
K. H. Solangi, M. R. Islam, R. Saidur, N. A. Rahim, and H. Fayaz, “A review on
global solar energy policy,” Renew. Sustain. Energy Rev., vol. 15, no.
4, pp. 2149–2163, May 2011.
[4]
T. Esram and P. L. Chapman, “Comparison of photovoltaic array maximum power
point tracking techniques,” IEEE Trans. Energy Convers., vol. 22, no. 2,
pp. 439–449, Jun. 2007.
[5]
M. A. G. de Brito, L. Galotto, L. P. Sampaio, G. de Azevedo e Melo, and C. A.
Canesin, “Evaluation of the main MPPT techniques for photovoltaic applications,”
IEEE Trans. Ind. Electron., vol. 60, no. 3, pp. 1156–1167, Mar. 2013.
