The Perturb and observe (P&o) Maximum Power Point Tracking (MPPT) algorithm in solar Photovoltaics (PV) is popular owing to its simplicity. However, its drawbacks, (i) operating point divergence and (ii) tradeoff ...
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The Perturb and observe (P&o) Maximum Power Point Tracking (MPPT) algorithm in solar Photovoltaics (PV) is popular owing to its simplicity. However, its drawbacks, (i) operating point divergence and (ii) tradeoff between fast convergence and balanced state oscillations decelerate the usage. Most of the developments in the literature toovercome these drawbacks increase complexity. To retain simplicity and also to improve tracking efficiency, this paper proposes a Coarse and fine control algorithm. This proposal has distinct aspects, having three control modes. Mode 1 and 2 enhance fast convergence and mode 3 controls stable state oscillations. The comparative analysis from simulation proves that the proposed technique has fast convergence, reduced balanced state oscillations, better tracking efficiency, and minimum transient power loss than the other techniques.
Position alignment between the transmitter and the receiver is vital for wireless charging system (WCS) because misalignment influences system efficiency, power transfer capability, and magnetic field distribution. Ba...
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Position alignment between the transmitter and the receiver is vital for wireless charging system (WCS) because misalignment influences system efficiency, power transfer capability, and magnetic field distribution. Based on the primary-side electrical parameters, the mutual inductance estimation and perturbation and observation (P&o) algorithms are proposed to achieve the adaptive position alignment for the inductor-capacitor-inductor-series (LCL-S) compensated WCS through the movable transmitter. Based on the relationship between primary-side active power and mutual inductance, the feedback impedance theory and quadrature transformation (QT) algorithms are proposed to estimate the mutual inductance. Combined with the misalignment characteristic of circular magnetic coupler, the position alignment that is achieved by P&o algorithm and estimated mutual inductance. The simulation and experimental results verify the following conclusions: The mutual inductance estimation is suitable for different magnetic coupler and compensation topologies, and the accuracy of the estimated mutual inductance is suitable for practical applications. Compared with traditional active power method, the QT algorithm that calculates is more suitable for WCS that features high operating frequency. Combined with the proposed algorithms, high-system performance and fully automatic charging are ensured by the adaptive position alignment method.
The conventional algorithmof perturb and observe (P&o) is widely applied due to its simplicity, low cost and easy implementation. However, it suffers from instabilities during rapid changes of weather and/or osci...
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The conventional algorithmof perturb and observe (P&o) is widely applied due to its simplicity, low cost and easy implementation. However, it suffers from instabilities during rapid changes of weather and/or oscillation around maximum power point (MPP) at steady state. Instabilities occur due to the incorrect decision taken by the conventional P&o algorithm at the first step change in duty cycle during the rapid change in radiation. The reason for the steady-state oscillation is the continuous perturbation and tradeoff between step sizes and the convergence time. This study presents a modified P&o algorithm toovercome such drawbacks. It uses a constant load technique to help the conventional P&o algorithm for recognising the cause of power change and to enable it in taking the right decision at first step change in duty cycle during rapid change of weather. The proposed algorithm is simulated using a single solar photovoltaic module of 80 W and a DC/DC boost converter. It is validated experimentally and implemented within an embedded microcontroller. The experimental setup presents a proposed model-based design methodology that uses measurements' data for MPP tracking systems' design. It combines hardware-in-the-loop simulation and prototype testing using actual weather measurements. Simulation and experiments show excellent results.
The power-voltage characteristic curve of photovoltaic systems under partially shaded conditions exhibits multiple peaks and renders conventional maximum power point tracking techniques ineffective. This study propose...
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The power-voltage characteristic curve of photovoltaic systems under partially shaded conditions exhibits multiple peaks and renders conventional maximum power point tracking techniques ineffective. This study proposes a hybrid optimisation algorithm incorporating genetic algorithm (GA) in the initial stages of tracking followed by traditional perturb and observe (P&o) algorithm. Although GA and P&o methods do not guarantee convergence to global maximum power point when employed separately, the fusion of the two methods leads to confirmed global convergences with least time. The excellent performance of the combined method is illustrated through extensive simulation and experimental results.
Sluggish tracking for change in solar irradiations is the main demerit of the perturb and observe (P&o) algorithm because of its fixed perturb. Toovercome this, an adaptive tracking algorithm based on Takagi-Suge...
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Sluggish tracking for change in solar irradiations is the main demerit of the perturb and observe (P&o) algorithm because of its fixed perturb. Toovercome this, an adaptive tracking algorithm based on Takagi-Sugeno fuzzy implications is proposed in this study. Input to the fuzzy controller is the error between conductance and incremental conductance which is otherwise zero at the maximum power point. The P&o algorithm and the proposed algorithm along with the recently published adaptive incremental conductance algorithm are examined for their performance efficacy on a photovoltaic (PV) generating system with fabricated as well as real irradiation data. As a case study, all the considered algorithms are validated under partial shading conditions also. The effectiveness of the proposed algorithm is verified for the tracking of the maximum power point of a PV system in steady as well as changing irradiations and the conclusions are supported through some experimental validations.
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