Enhanced Maximum Power Point Techniques for Solar Photovoltaic System under Uniform Insolation and Partial Shading Conditions: A Review

Bhukya, Laxman; Kedika, Narender Reddy; Salkuti, Surender Reddy

doi:10.3390/a15100365

Cited by 65 publications

(16 citation statements)

References 118 publications

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“…The waggle dance's power and length show the opulence of the food source discovered. The waggling movements change from one species to the next [7].…”

Section: Swarm Intelligent Techniquesmentioning

confidence: 99%

“…Changes in radiation could cause the fluctuation effect. The inequality condition, as shown in the equation, represents such changes in radiation (7). If the requirement mentioned above in ( 11) is met, the GMPP search will begin again.…”

Section: Swarm Intelligent Techniquesmentioning

confidence: 99%

“…Various articles in the literature have developed optimization strategies using meta-heuristics algorithms to solve the partial shading issues in PV arrays. Particle swarm optimization (PSO), grey wolf optimization (GWO), ant colony optimization (ACO), artificial bee colony (ABC), cuckoo search (CS), and several optimization algorithms [7], [8] take inspiration from animal and insect behavior in the nature.…”

Section: Introductionmentioning

confidence: 99%

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A state of the art a hybrid intelligent strategies of maximum power point tracking: a systematic contemporary

Shalal,

Aljanabi,

Al-Shamani

et al. 2023

IJPEDS

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Renewable energy sources are among the best substitute sources to fossil fuel due to it is very suitable for mitigating global warming; solar energy is considered the main causes of renewable energy, and solar photovoltaic (PV) generation systems have gained importance worldwide due to several characteristics, including cheap maintenance, low noise, and low fuel costs. However, one of the most difficult challenges facing solar energy systems is changing weather circumstances. The robust control approach stabilizes the PV system's output and maximizes harvested energy. In this study, several maximum power point tracking (MPPT) performances have been presented. Among them, artificial intelligence (AI) based on MPPT methods demonstrates the ability to capture the MPP point. There are several ways to apply AI to MPPT, and this paper presented various intelligent MPPT methods in detail with their benefits and drawbacks and comparison among them to select which technique is suitable and can be used to change weather conditions with<strong> </strong>horse optimization method (HOM) plus neural artificial system (NAS).

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“…The waggle dance's power and length show the opulence of the food source discovered. The waggling movements change from one species to the next [7].…”

Section: Swarm Intelligent Techniquesmentioning

confidence: 99%

Section: Swarm Intelligent Techniquesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A state of the art a hybrid intelligent strategies of maximum power point tracking: a systematic contemporary

Shalal,

Aljanabi,

Al-Shamani

et al. 2023

IJPEDS

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“…Therefore, to enhance the power generation efficiency of the PVMA, an MPPT controller must be used. At present, common and conventional MPPT methods include the constant voltage method (CVM) [4][5][6], the power feedback method (PFM) [7,8] and the perturb and observe method (P&O) [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Global Maximum Power Point Tracking of a Photovoltaic Module Array Based on Modified Cat Swarm Optimization

Chao,

Nguyen

2024

Applied Sciences

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The main purpose of this study was to research and develop maximum power point tracking (MPPT) of a photovoltaic module array (PVMA) with partial module shading and sudden changes in solar irradiance. Modified cat swarm optimization (MCSO) was adopted to track the global maximum power point (GMPP) of the PVMA. Upon a sudden changes in solar irradiance or when certain modules in the PVMA were shaded, the maximum power point (MPP) of the PVMA will change accordingly, and multiple peak values may appear on the power–voltage (P-V) characteristic curve. Therefore, if the tracking pace is constant, the time required to track the MPP might extend, and under certain circumstances, the GMPP might not be tracked, as only the local maximum power point (LMPP) can be tracked. To prevent this problem, a maximum power point tracker based on MCSO is proposed in this paper in order to adjust the tracking pace along with the slope of the P-V characteristic curve and the inertia weight of the iteration formula. The initial voltage for tracking commencement was set to 0.8 times the voltage at the maximum power point of the PVMA under standard test conditions. Firstly, MATLAB 2022a was used to construct the four-series, three-parallel PVMA model under zero shading and partial shading. The feedback of PVMA voltage and current was obtained, where the GMPP was tracked with MCSO. From the simulation results, it was proven that, under different shading percentages and sudden changes in solar irradiance for partial modules in the PVMA, the MCSO proposed in this paper provided better tracking speed, dynamic response, and steady performance compared to the conventional CSO.

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“…On the above basis these, various MPPT approaches turned out and categorized into three main groups [7,8]. The first type of MPPT technique calculates MPP using a priori data rather than continuously monitoring the current and voltage [9,10]. Less voltage and/or current sensors are needed, which is these approach's main benefit.…”

mentioning

confidence: 99%

A New Dragonfly Optimized Fuzzy Logic-based MPPT Technique for Photovoltaic Systems

Singh,

Mangu,

Saho

2023

IJEER

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Photovoltaic (PV) power systems should be operated at the maximum power point (MPP) for best solar energy utilization, which can be achieved using maximum power point tracking (MPPT) techniques. Perturb & Observe (P&O) and Fuzzy logic MPPT approaches were two of the various strategies that were suggested as effective ways to achieve Maximum Power under Continuous Irradiation. When exposed to changes in environmental conditions, these approaches perform poorly dynamically and exhibit substantial steady-state oscillations around the MPP. To overcome this problem, this paper proposes the Dragonfly optimization-based fuzzy logic MPPT approach for maximum power extraction of photovoltaic (PV) systems. The approaches for implementing FL-based MPPTs that are currently available are not adaptable to the operating point, which varies widely in real-world PV systems with operational irradiance and ambient temperature. The proposed MPPT (DAFLC-MPPT) is straightforward, accurate, and offers quicker convergence to the optimal operating point. With consideration of various operating situations at slow and fast changes in solar radiation, the efficacy and viability verifications of the proposed AFL-MPPT approach are validated. The proposed strategy outperforms the standard P&O and fuzzy logic methods.

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Enhanced Maximum Power Point Techniques for Solar Photovoltaic System under Uniform Insolation and Partial Shading Conditions: A Review

Cited by 65 publications

References 118 publications

A state of the art a hybrid intelligent strategies of maximum power point tracking: a systematic contemporary

A state of the art a hybrid intelligent strategies of maximum power point tracking: a systematic contemporary

Global Maximum Power Point Tracking of a Photovoltaic Module Array Based on Modified Cat Swarm Optimization

A New Dragonfly Optimized Fuzzy Logic-based MPPT Technique for Photovoltaic Systems

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