Abstract
Maximum power point tracking (MPPT) is a technique employed for with variable-power sources, such as solar, wind, and ocean, to maximize energy extraction under all conditions. The commonly used perturb and observe (P&O) and incremental conductance (INC) methods have advantages such as ease of implementation, but they also have the challenge of selecting the most optimized perturbation step or increment size while considering the trade-off between convergence time and oscillation. To address these issues, an MPPT solution for grid-connected photovoltaic (PV) systems is proposed that combines the golden section search (GSS), P&O, and INC methods to simultaneously achieve faster convergence and smaller oscillation, converging to the MPP by repeatedly narrowing the width of the interval at the rate of the golden ratio. The proposed MPPT technique was applied to a PV system consisting of a PV array, boost chopper, and inverter. Simulation and experimental results verify the feasibility and effectiveness of the proposed MPPT technique, by which the system is able to locate the MPP in 36 ms and regain a drifting MPP in approximately 30 ms under transient performance. The overall MPPT efficiency is 98.99%.
Highlights
Maximum power point tracking (MPPT) is a technique employed for with variable-power sources, such as solar, wind, and ocean, to maximize energy extraction under all conditions
Regarding the drawbacks of the perturb and observe (P&O) and incremental conductance (INC) algorithms and the complexity of existing intelligent control algorithms, this paper proposes a multi-stage MPPT algorithm that includes a golden section search (GSS) method as a straightforward optimization approach targeting small-scale PV systems
The GSS-based multi-stage MPPT strategy is applied to the boost chopper stage, where the output voltage of the PV array is controlled by a proportional-integral (PI) controller to trace the reference generated by the MPPT controller
Summary
The U.S Energy Information Administration (EIA) estimates that photovoltaic (PV) generation increased from approximately 5 million kW·h in 1984 to approximately 107 billion kW·h in 2019 [1]. Regarding the drawbacks of the P&O and INC algorithms and the complexity of existing intelligent control algorithms, this paper proposes a multi-stage MPPT algorithm that includes a golden section search (GSS) method as a straightforward optimization approach targeting small-scale PV systems. In this method, an initial interval is first selected in the PV voltage range, which brackets the MPP. The proposed multi-stage MPPT involves P&O in the first stage and GSS in the second stage, and the INC technique is used to verify the located MPP in the third stage, as Shuang Xu et al.: Single-phase Grid-connected PV System with Golden Section Search-based MPPT Algorithm 27 the system must know if the MPP has drifted when the conditions change.
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