Boost Converter of Maximum Power Point Tracking (MPPT) Using Particle Swarm Optimization (PSO) Method

Khazain, M. A.; Hidayat, Nabil M.; Burhanudin, K.; Abdullah, Ezmin

doi:10.1109/icsgrc53186.2021.9515228

Cited by 6 publications

(2 citation statements)

References 7 publications

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“…If an extempore scenario, such as the initialization requirement in (3), was studied, the technique update is in line with Equs. The Ft indicates the board purpose that must be maximized [17].…”

Section: Swarm Intelligent Techniquesmentioning

confidence: 99%

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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Section: Swarm Intelligent Techniquesmentioning

confidence: 99%

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

View full text Add to dashboard Cite

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“…Soft computing algorithms, on the other hand, possess the ability to identify the GMPP under PSC but are complex in structure, hard to implement, demand huge memory, and require high cost for huge data training. The most known soft-computing algorithms are Particle Swarm Optimization [15], Genetic algorithm [16], Fuzzy Logic Controller [17], Artificial Neural Network [18], and Flower Pollination algorithm [19].…”

Section: Introductionmentioning

confidence: 99%

Strategic Perturb and Observe Algorithm for Partial Shading Conditions

Awan

2022

SSURJET

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Solar photovoltaic (PV) is the cheapest renewable resource of electrical energy. Its dependence on the connected load bounds its production capability. To deliver the determined power, it is required to operate at the maximum power point (MPP) in the characteristic curve of the PV array. Tracking the MPP requires electronic circuits govern by MPP tracking (MPPT) algorithms. The most simple, cheap, and softly implementable MPPT algorithm is “Perturb and Observe (P&O)”. It efficiently performs under uniform weather conditions (UWC) but fails under partial shading conditions (PSC) due to the formation of multiple peaks in the P-V characteristic curve of a PV cell. In this paper, weaknesses of the P&O algorithm are studied and overcome by structural modifications. The proposed structure is named the “strategic P&O algorithm”. Performance of the conventional and proposed algorithms is evaluated at the following standard benchmarks, tracking speed, tracking time, efficiency, and ability to track the GMPP under PSC. Results have shown that the proposed SP&O algorithm has outperformed the conventional P&O algorithm under numerous weather conditions. Simulations are performed in MATLAB/Simulink.

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Hybrid maximum power point tracking control method for photovoltaic power generation systems

2023

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Boost Converter of Maximum Power Point Tracking (MPPT) Using Particle Swarm Optimization (PSO) Method

Cited by 6 publications

References 7 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

Strategic Perturb and Observe Algorithm for Partial Shading Conditions

Hybrid maximum power point tracking control method for photovoltaic power generation systems

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