Abstract
This paper presents a comparative study between two maximum power point tracking (MPPT) algorithms, the incremental conductance algorithm (InC) and the fuzzy logic controller (FLC). The two algorithms were applied to a low photovoltaic power conversion system, and they both use different PI controllers and grid synchronization techniques. Moreover, both InC and FLC methods have Clarke and Park Transformation. To some extent, the incremental conductance and fuzzy logic controller approaches are similar, but their control loops are different. Therefore, the InC has classic Proportional Integrative (PI) controllers with simple phase-locked loops (PLL). At the same time, the FLC works with fuzzy logic PI controllers linked with the Second Order Generalized Integrator (SOGI). The proposed techniques examine the solar energy conversion performance of the photovoltaic (PV) system under possible irradiance changes and constant temperature conditions. Finally, a performance comparison has been made between InC and FLC, which demonstrates the effectiveness of the fuzzy controller over the incremental conductance algorithm. FLC turns to convert photovoltaic power easily, decreasing fluctuations, and it offers a quick response to the variation of solar irradiance (shading effect). The simulation results show a superior performance of the controller with fuzzy logic, which helps the inverter convert over 99% of the power generated by the photovoltaic panels. In comparison, the incremental conductance algorithm converts around 80%.
Highlights
Energy is a vital component designed to provide economic development and progress [1]
Jalali Zand and Hsia [7] developed a PV system with maximum power point tracking (MPPT) based on self-predictive incremental conductance (SPInC) and applied a DC–DC boost converter
Basha and Rani [8] explored different converter configurations applied to a PV system using conventional MPPT techniques, such as the perturb and observe method with variable step size (VSS–P&O), modified incremental conductance (MIC) and fractional open-circuit voltage (FOCV)
Summary
Energy is a vital component designed to provide economic development and progress [1]. Jalali Zand and Hsia [7] developed a PV system with MPPT based on self-predictive incremental conductance (SPInC) and applied a DC–DC boost converter According to these authors’ Matlab/Simulink simulation results, the SPInC algorithm outperforms the classical InC, and the output power has a minimal ripple. Basha and Rani [8] explored different converter configurations applied to a PV system using conventional MPPT techniques, such as the perturb and observe method with variable step size (VSS–P&O), modified incremental conductance (MIC) and fractional open-circuit voltage (FOCV) These algorithms perform a comparative analysis under static and dynamic irradiation, considering the characteristics of the algorithm, such as MPP oscillations, tracking speed, and detection parameters.
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