Optimization Methods of MPPT Parameters for PV Systems: Review, Classification, and Comparison

doi:10.35833/MPCE.2019.000379

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Optimization Methods of MPPT Parameters for PV Systems: Review, Classification, and Comparison

DOI:

10.35833/MPCE.2019.000379

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1.Department of Electrical Engineering, University of Isfahan, Isfahan, Iran;2.Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Canada

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Abstract:

To obtain efficient photovoltaic (PV) systems, optimum maximum power point tracking (MPPT) algorithms are inevitable. The efficiency of MPPT algorithms depends on two MPPT parameters, i.e., perturbation amplitude and perturbation period. The optimization of MPPT algorithms affect both the tracking speed and steady-state oscillation. In this paper, optimization methods of MPPT parameters are reviewed and classified into fixed and variable methods. The fixed MPPT parameters are constant during MPPT performance, and a trade-off should be made between the tracking speed and steady-state oscillation. However, the variable MPPT parameters will be changed to improve both the tracking speed and the steady-state oscillations. Moreover, some of them are simulated, compared, and discussed to evaluate the real contributions of the optimization methods to the MPPT efficiency. Furthermore, significant features of the optimization methods, i.e., noise immunity, robustness, and computation effort, are investigated.

图1 Different PV system structures. (a) Single-loop. (b) Multi-loop.Fig.1

图2 ΔD and Tp on duty cycle of IPC leading to optimum efficiency of MPPT.Fig.2

图3 I-V and P-V curves of dynamic and static resistors.Fig.3

图4 PV system consisting of a PV panel, a boost converter, and a resistive load.Fig.4

图5 Effect of ΔD on oscillation amplitude of operation point around MPP.Fig.5

图6 Effect of Tp which is smaller than system settling time on oscillation amplitude of operation point around MPP.Fig.6

图7 Effect of Tp which is greater than system settling time on oscillation amplitude of operation point around MPP.Fig.7

图8 Optimization methods of perturbation amplitude.Fig.8

图9 Dual-stage grid-connected PV system.Fig.9

图10 Choosing optimum ΔD based on power difference between point A and point B.Fig.10

图11 Bifurcation diagram of PV voltage-step size for P&O algorithm.Fig.11

图12 P-D and Io-D curves. (a) P-D curve. (b) Io-D curve.Fig.12

图13 Auxiliary function used for predicting limit of MPP.Fig.13

图15 Block diagram of controller-based method.Fig.15

图16 Optimization methods of perturbation period.Fig.16

图17 Flowchart of non-parametric system identification of PV system.Fig.17

图18 Settling time of PV system versus ΔD.Fig.18

图19 Output power and voltage of PV systems of Table II. (a) Irradiance profile. (b) Method No. 4. (c) Method No. 5. (d) Method No. 6. (e) Method No. 7. (f) Method No. 8. (g) Method No. 9. (h) Method No. 11.Fig.19

图20 Variable ΔD in different methods of Table II. (a) Irradiance profile. (b) Method No. 4. (c) Method No. 5. (d) Method No. 6. (e) Method No. 7. (f) Method No. 8. (g) Method No. 9. (h) Method No. 11.Fig.20

图21 Output power and voltage of PV systems of Table II. (a) Irradiance profile. (b) Method No. 9. (c) Method No. 10. (d) Method No. 11.Fig.21

图22 Tp in different methods of Table II. (a) Irradiance profile. (b) Method No. 9. (c) Method No. 10. (d) Method No. 11.Fig.22

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Received:June 08,2019
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Online: March 22,2021
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