Hybrid Global Maximum Power Tracking Method With Partial Shading Detection Technique for PV Systems

Mohammed, Karam Khairullah; Buyamin, Salinda; Shams, Immad; Mekhilef, Saad

doi:10.1109/jestpe.2021.3126941

Cited by 23 publications

(3 citation statements)

References 30 publications

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“…Unlike evaluating the initial best by comparing m powers corresponding to m duty vectors as in ( 12), the improved initial best evaluation method calculates the power across each duty vector element as in (13).…”

Section: E Solution To Md-mpe Through Modified Methodsmentioning

confidence: 99%

Integrated Duty Cycle Control for Multiple Renewable Energy Sources in a Grid Connected System

Pervez

Antoniadis

Ghazzai

et al. 2023

IEEE Open J. Power Electron.

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Due to their abundance, affordability, and clean energy production, Renewable Energy Sources (RESs) have emerged as crucial sources of electricity production. As a result, considerable effort has been made to integrate renewable energy sources into the grid to help it meet energy demands. One of the challenges is the Maximum Power Extraction (MPE), where the maximum power needs to be extracted from each RES. The cost of implementation rises linearly with the number of RESs if the MPE arrangements are being made for each RES individually. Additionally, the MPE through multiple RES systems gets more challenging, especially when several PhotoVoltaic (PV) strings are connected and each PV string receive non-uniform irradiance. This paper proposes an integrated MPE control system for a multi-RES grid-connected system. The proposed solution uses a single microcontroller to maximize power from all sources to overcome the linearly growing cost problem. Moreover, we propose an improved Multi-Dimensional Cuckoo (MDC) algorithm for MPE to tackle the non-uniform irradiation problem with multi-string PV, in contrast to prior works with grid-connected multiple sources. The proposed technique is first put up against the individual MPE control system, and then it is put up against the Jaya algorithm that is documented in the literature for a typical one-dimensional MPE. INDEX TERMS Maximum power extraction (MPE), DC-DC converter, Metaheuristic algorithm, Multidimensional cuckoo algorithm, integrated grid power control

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Section: E Solution To Md-mpe Through Modified Methodsmentioning

confidence: 99%

Integrated Duty Cycle Control for Multiple Renewable Energy Sources in a Grid Connected System

Pervez

Antoniadis

Ghazzai

et al. 2023

IEEE Open J. Power Electron.

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“…At present, many GMPPT algorithms based on metaheuristic techniques have been proposed in the literature. The metaheuristic methods such as squirrel search, 3 most valuable player (MVP), 4 firefly algorithm (FFA), 5 Nelder–Mead simplex (NMS), 6 and modified rat swarm optimization (MRSO), 7 can solve the multi‐peak problem under PSC. However, due to the selection of initial points, tuning of control parameters, and heavy calculation burden, these techniques are difficult to implement.…”

Section: Introductionmentioning

confidence: 99%

An improved 0.8Voc model‐based global maximum power point tracking algorithm for photovoltaic system

Nadeem,

Ahmed Sher,

Faisal Murtaza

et al. 2023

Circuit Theory & Apps

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In this paper, a low‐cost and high‐speed partial shading condition (PSC) detection scheme and global maximum power point tracking (GMPPT) technique are presented. The proposed technique detects the PSC using a low‐cost voltage sensor without setting any threshold parameter. The proposed GMPPT algorithm utilizes the 0.8 model along with the load‐line observation to skip the unwanted interval of – curve. Moreover, in case of dynamic shading, a smart scanning mechanism is used along with the load‐line observation to reduce the voltage iterations which leads to an improvement in tracking speed. The proposed technique is implemented in a Matlab/Simulink environment and compared with the conventional 0.8 method and accurate PSC detection method. The results indicate the following advantages of the proposed algorithm: (1) iteration free and accurate detection of PSC and uniform irradiance condition, (2) enhancement in average tracking time by 67.44% and 69.48%, and (3) improvement in average transient efficiency by 17.36% and 21.25% compared with 0.8 method and accurate PSC detection method. Besides, the experimental results depict that the proposed method enhances the average tracking time by 68.6% and 72.69% and improves the average transient efficiency by 17.62% and 15.06% compared with 0.8 method and accurate PSC detection method, respectively.

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“…In [12], an adaptive PSO mitigates the local convergence of PSO when insolation changes by theoretically approximating the optimum duty ratios at each re-initialization. In [13], the convergence rate is enhanced by combining a full insolation detection technique with the Rat Swarm Optimizer (RSO) algorithm [9]. [14] proposes a differential evolutionary algorithm hybrid with the PSO (PSO-DV) to reduce the probability of converging to the local maxima like in PSO by re-initializing possible solutions after a few iterations.…”

Section: Introductionmentioning

confidence: 99%

A Reduced Search Space Exploration Metaheuristic Algorithm for MPPT

2022

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The necessity for clean and sustainable energy has shifted the energy sector's interest in renewable energy sources. Photovoltaics (PV) is the most popular renewable energy source because the sun is ubiquitous. However, PV's power transfer efficiency varies with different load's electrical characteristics, temperatures on PV panels, and insolation conditions. Based on these factors, Maximum Power Point Tracking (MPPT) is a mechanism formulated as an optimization problem adjusting the PV to deliver the maximum power to the load. Under full insolation conditions, varying solar panel temperatures, and different loads MPPT problem is a convex optimization problem. However, when the PV's surface is partially shaded, multiple power peaks are created in the power versus voltage (P-V) curve making MPPT non-convex. Unfortunately, all optimization strategies for MPPT under partial shading applied in previous works, from traditional techniques to Machine Learning and the recently proposed Natureinspired algorithms, were either computationally expensive or/and led to extensive power losses. To this end, this work presents an algorithm that builds upon metaheuristic optimization algorithms to reduce their complexity further and mitigate the power losses during power tracking. Our experimental results demonstrated that the proposed algorithm converges faster to maximum power point with lower power losses during tracking compared to two very recently proposed MPPT algorithms under partial shading conditions. INDEX TERMSMetaheuristic Algorithms, improved Limited Search Strategy (iLSS), Photovoltaic (PV), Partial Shading (PS), Maximum Power Point Tracking (MPPT).

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Hybrid Global Maximum Power Tracking Method With Partial Shading Detection Technique for PV Systems

Cited by 23 publications

References 30 publications

Integrated Duty Cycle Control for Multiple Renewable Energy Sources in a Grid Connected System

Integrated Duty Cycle Control for Multiple Renewable Energy Sources in a Grid Connected System

An improved 0.8Voc model‐based global maximum power point tracking algorithm for photovoltaic system

A Reduced Search Space Exploration Metaheuristic Algorithm for MPPT

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