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Journal ArticleDOI

A Fixed Zone Perturb and Observe MPPT Technique for A Standalone Distributed PV System

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TLDR
The FZPO technique requires a PV panel’s information only at the initial design stage but not during real-time tracking, making the implementation possible using only low-cost processors, and the implementation and design of the proposed controller are presented.
Abstract
This paper proposes a fixed zone perturb & observe (FZPO) technique to achieve an improved steady-state efficiency as well as a fast and drift-free maximum power point tracking (MPPT) for photovoltaic (PV) systems without any additional sensors. In this technique, the PV array’s power-voltage curves are divided into multiple zones with unique zone boundary voltages for different irradiance conditions. This technique employs a combination of adaptive and fixed step-sizes to improve the performance, where the adaptive step-size is calculated from simple mathematical equations, resulting in a reduced computational burden. Besides, natural drift-free tracking is achieved without any additional sampling or computation, overcoming existing techniques’ limitations. The FZPO technique requires a PV panel’s information only at the initial design stage but not during real-time tracking, making the implementation possible using only low-cost processors. This paper presents the implementation and design of the proposed controller. The FZPO technique’s performance is validated through a comprehensive set of hardware experiments on a buck-boost full-bridge converter under various irradiance conditions per the EN50530 standard. For a step-change in irradiance, the FZPO technique is experimentally verified to be 42% and 20% more efficient than the conventional and VSS techniques, respectively. During the irradiance varying conditions using the FZPO technique, the peak power loss is one-sixth compared to the conventional and VSS techniques. Practical field-related considerations such as PV panel temperature effects are further investigated through experiments.

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Citations
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Journal ArticleDOI

Experimental Analysis of hill-climbing MPPT algorithms under low irradiance levels

TL;DR: In this paper, the perturbation step-sizes of hill-climbing MPPT algorithms under a wide range of irradiance conditions were determined and a general expression to determine the optimum digitized step-size for duty-based perturb and observe algorithm under low irradiance condition was defined.
Journal ArticleDOI

Performances of the adaptive conventional maximum power point tracking algorithms for solar photovoltaic system

TL;DR: In this article , the design features and operating procedures of six popular conventional MPPT methods are discussed and corresponding modifications of the conventional MPP methods are analyzed and reviewed, and a comprehensive comparative analysis of the twenty-eight adaptive MPPT algorithms is performed based on the tracking time, steady-state oscillations, conversion efficiency, algorithm complexity, implementation cost, capability to perform on the partial shading conditions, etc.
Journal ArticleDOI

A Framework of Reduced Sensor Rooftop SPV System Using Parabolic Curve Fitting MPPT Technology for Household Consumers

TL;DR: In this paper , a novel Parabolic Curve-fitting based Hill Climbing (PCHC) MPPT (Maximum Power Point Tracking) algorithm is developed to extract maximum power from solar photovoltaic (PV) panels under dynamic environmental conditions for household consumers.
Journal ArticleDOI

Improved salp swarm algorithm based on particle swarm optimization for maximum power point tracking of optimal photovoltaic systems

TL;DR: In this article , an improved salp swarm algorithm based on particle swarm optimization for maximum power point tracking of optimal photovoltaic systems is investigated, where the effect of PV partial shading conditions, uniform and fast-tracking irradiance, duty cycle, frequency, temperature changes, and load types are adequately examined for better performance study of the proposed technique.
Journal ArticleDOI

A Framework of Reduced Sensor Rooftop SPV System Using Parabolic Curve Fitting MPPT Technology for Household Consumers

TL;DR: In this paper , a novel Parabolic Curve-fitting based Hill Climbing (PCHC) MPPT (Maximum Power Point Tracking) algorithm is developed to extract maximum power from solar photovoltaic (PV) panels under dynamic environmental conditions for household consumers.
References
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Journal ArticleDOI

Modified Perturb and Observe MPPT Algorithm for Drift Avoidance in Photovoltaic Systems

TL;DR: Simulation and experimental results showed that the proposed algorithm accurately tracks the maximum power and avoids the drift in fast changing weather conditions.
Journal ArticleDOI

A new algorithm for rapid tracking of approximate maximum power point in photovoltaic systems

TL;DR: A fast tracking algorithm, where an initial approximation of maximum power point is (MPP) quickly achieved using a variable step-size, which significantly improves the efficiency during the tracking phase as compared to a conventional algorithm.
Journal ArticleDOI

Artificial neural network-polar coordinated fuzzy controller based maximum power point tracking control under partially shaded conditions

TL;DR: In this article, a novel maximum power point tracking (MPPT) system is proposed for partially shaded PV array using artificial neural network (ANN) and fuzzy logic with polar information controller.
Journal ArticleDOI

An Overall Distribution Particle Swarm Optimization MPPT Algorithm for Photovoltaic System Under Partial Shading

TL;DR: A novel overall distribution MPPT algorithm to rapidly search the area near the global maximum power points, which is further integrated with the particle swarm optimization (PSO) MPPT algorithms to improve the accuracy of MPPT.
Journal ArticleDOI

High-Performance Algorithms for Drift Avoidance and Fast Tracking in Solar MPPT System

TL;DR: In this article, a variable-step-length algorithm is proposed to eliminate the tradeoff between tracking and dynamic performance of the perturb and observe (P&O) algorithm, where the drift is minimized by evaluating the entire trend in a power versus voltage curve.
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