Research led by scientists from China University of Petroleum (East China) has developed a new maximum power point tracking (MPPT) technique for PV systems under complex partial shading conditions.
The new APO-MPC technique combines adapted perturb and observe with model predictive control. The team developed the approach in MATLAB/Simulink and validated it through real-time hardware implementation.
The algorithm was implemented and tested under various climate profiles such as uniform irradiance conditions (UIC), simple PSCs (SPSCs), CPSCs, and field atmospheric datasets, said the researchers. The algorithm was then evaluated and compared alongside other MPPT techniques such as PO, APO, IC, FLC, GWO, and MPC using experimental validation based on criteria such as convergence speed, global maximum power point (GMPP) tracking, computational complexity, efficiency, oscillations, and overall performance.
In the APO phase of the algorithm, the system calculates the number of shaded modules and estimates the possible number of power peaks. It then uses a variable step size and determines the reference current. The MPC phase follows, using a predictive model of the boost converter to forecast the next output current. It does so by solving an optimization problem and then updating the duty cycle.
Using MATLAB/Simulink, the group connected six photovoltaic modules in a string. Bypass diodes were installed with each module, and a blocking diode was added to prevent reverse current flow. The MPPT control scheme adjusts the duty cycle to optimize the switching state of the DC-DC boost converter for stepping up the input voltage. Voltage ripples generated by the converter are mitigated using passive components.
The system was tested in MATLAB/Simulink under three UIC, SPSCs, and CPSC patterns, and later under seasonal irradiance data from Lahore, Punjab, Pakistan. In all cases, the system was compared to various other MPPT techniques in the literature, including PO, APO, IC, MIC, IIC, and CMPC. In the final step, an experimental setup was exposed to various irradiance scenarios.
The outcomes demonstrate that the APO-MPC excels in GMPP tracking across various weather conditions, achieving an average tracking efficiency of 99.46% under all shading effects, the researchers said. Compared to other techniques, it shows fast convergence within 0.19 s, improved settling time of 0.24 s, reduced steady-state oscillations (SSOs) of 0.30 W, and a 2% to 13% improvement in power generation. On the hardware setup, it achieved an average tracking efficiency of 97.14% at 0.23 s with a more stable output power, exhibiting SSOs around 0.33 W.
The researchers said the proposed approach outperforms all other techniques, presenting the shortest rise time, lowest computational time, minimal power oscillations, and the highest tracking efficiency while effectively tracking the GMPP to ensure optimal power extraction under diverse weather conditions. Thus, the algorithm effectively resolves issues like power oscillations, low tracking efficiency, and falling into local maximum power points (LMPPs) under SPSCs and CPSC.
They presented their results in Performance validation of global MPPT for efficient power extraction through PV system under complex partial shading effects, which was recently published in Scientific Reports. Scientists from China University of Petroleum (East China),
South Africas University of Johannesburg, Indias Saveetha Institute of Medical and Technical Sciences, Chitkara University, Jordans Applied Science Private University, Canadas Universit� de Moncton, Gabons International Institute of Technology and Management (IITG), and Saudi Arabias University of Hail have conducted the study.
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