Abstract
This research proposed a novel global maximum power point tracking (global-MPPT) algorithm. The proposed algorithm eliminates the perturbation and observation (P&O) technique disturbance problem that the power point will be stuck at the local peak power point under a partial shading condition (PSC). The proposed global-MPPT algorithm detects the photovoltaic module (PV-M) environment irradiance level by the relationship between the output power and voltage of the PV-M. In the proposed algorithm, the important parameter w is determined by the PV-M output power and irradiance level, which is also the compensation parameter that corresponds to the relationship of temperature. The proposed global-MPPT algorithm is aimed to predict the best duty cycle of the global-MPPT based on the irradiance level, parameter w, PV-M output voltage, and load, and then achieve the maximum power point (MPP) quickly and accurately. The measurement results under UIC and PSC verify that the proposed global-MPPT technique performs better than the particle swarm optimization (PSO) and P&O techniques. This research contributes to the proposed method that can find the global-MPP in time based on the irradiance level, temperature, and load.
Highlights
Industrial development has affected the Earth’s climate and led to the greenhouse effect
The remainder of this paper is organized as follows: Section 2 describes the particle swarm optimization and perturbation and observation algorithms; the proposed global maximum power point tracking algorithm is presented in detail in Section 3; Section 4 presents the experimental results, while Section 5 includes conclusions and suggests directions for future work
When the slope changes, the perturbation and observation (P&O) algorithm adjusts the duty cycle for performing maximum power point tracking (MPPT) to reach the maximum power point (MPP). This algorithm has the following shortcomings: (1) under the partial shading condition (PSC), the actuating point can become stuck at the local peak power point without escape [37]; (2) at a steady-state irradiance level, the actuating point will vibrate near the MPP [21]; (3) with the rapid change in irradiance levels, the actuating point cannot capture the MPP in time [22]; (4) the actuating point is close to the MPP, and the convergence speed is slow [22]
Summary
Industrial development has affected the Earth’s climate and led to the greenhouse effect. PSC, the proposed global-MPPT algorithm overcomes the problem that the actuating point will be trapped in the local MPP, which causes power loss. PV-M output voltage (Vpv-m ), PV-M output current (Ipv-m ), power converter output voltage (Vo ), and power converter output current (Io ) Through these signals, the proposed globalMPPT algorithm can calculate the duty cycle corresponding to the global MPP, where Vo and Io are to calculate load (Ro ). The remainder of this paper is organized as follows: Section 2 describes the particle swarm optimization and perturbation and observation algorithms; the proposed global maximum power point tracking algorithm is presented in detail in Section 3; Section 4 presents the experimental results, while Section 5 includes conclusions and suggests directions for future work
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