Logarithmic PSO-Based Global/Local Maximum Power Point Tracker for Partially Shaded Photovoltaic Systems

Makhloufi, Salim; Mekhilef, Saad

doi:10.1109/jestpe.2021.3073058

Cited by 47 publications

(15 citation statements)

References 45 publications

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“…The PSO method is a metaheuristic approche commonly utilized in the optimization of complex systems. This technique is inspired by the living world [12], [13], it is an evolutionary algorithm that uses an ensemble of candidate solutions to locate the optimal solution to the problem under study.…”

Section: Modeling Of the Particle Swarm Optimization Methodsmentioning

confidence: 99%

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Design of a Particle Swarm Optimized Photovoltaic system during various partial shading conditions

et al. 2022

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This work discusses an enhanced photovoltaic system using the Particle Swarm Optimization algorithm. The proposed method has been evaluated under several scenarios of partial shading, and the results obtained are contrasted with the Perturb and Observe technique. Hence, it has shown its effectiveness in locating the global maximum power point whatever the meteorological conditions, especially in inhomogeneous conditions. This technique makes it possible to enhance the effectiveness of the photovoltaic system studied because it makes it possible to minimize the loss of power in the case of non-homogeneous irradiation conditions.

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Section: Modeling Of the Particle Swarm Optimization Methodsmentioning

confidence: 99%

“…Mathematically, this method can be modeled according to two main factors, the velocity defined by equation ( 5) and the position of the particle defined by ( 6) [13]. The principle of this method is described in Figure 8.…”

Section: Modeling Of the Particle Swarm Optimization Methodsmentioning

confidence: 99%

Design of a Particle Swarm Optimized Photovoltaic system during various partial shading conditions

et al. 2022

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“…1) In view of the shortcomings of centralized trading mode, such as low efficiency and high energy consumption, blockchain technology [14] is introduced to conduct power trading to ensure the security of trading information. 2) In order to improve the economy of power trading, particle swarm optimization [15] is introduced to carry out multi-objective search optimization and find the optimal scheme.…”

Section: Introductionmentioning

confidence: 99%

Blockchain-Based Power Transaction Method for Active Distribution Network

Zeng¹,

Wei²,

Han³

et al. 2023

Energy Engineering

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A blockchain-based power transaction method is proposed for Active Distribution Network (ADN), considering the poor security and high cost of a centralized power trading system. Firstly, the decentralized blockchain structure of the ADN power transaction is built and the transaction information is kept in blocks. Secondly, considering the transaction needs between users and power suppliers in ADN, an energy request mechanism is proposed, and the optimization objective function is designed by integrating cost aware requests and storage aware requests. Finally, the particle swarm optimization algorithm is used for multi-objective optimal search to find the power trading scheme with the minimum power purchase cost of users and the maximum power sold by power suppliers. The experimental demonstration of the proposed method based on the experimental platform shows that when the number of participants is no more than 10, the transaction delay time is 0.2 s, and the transaction cost fluctuates at 200,000 yuan, which is better than other comparison methods.

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“…Reference [18] used improved fusion firefly algorithm (FFA) to track the GMPP under PSCs, which integrated the neighborhood attraction firefly algorithm (NaFA) and simplified firefly algorithm (SFA), and achieved a high efficiency to track the GMPP. Reference [19] presented a logarithmic PSO method, which reduced the power oscillation during the MPPT process and accelerated the convergence. In [20], a modified butterfly optimization algorithm (MBOA) was developed to solve the MPPT problem under PSCs, which distinguished different partial shadow conditions with fast convergence speed.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Pigeon-Inspired Optimization-Based MPPT Method for Photovoltaic Systems Under Complex Partial Shading Conditions

Zhao

Zhang

et al. 2022

IEEE Trans. Ind. Electron.

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This paper proposes a novel maximum power point tracking (MPPT) method based on the variant of the pigeon-inspired optimization (PIO) algorithm for photovoltaic (PV) systems under partial shading conditions (PSCs). The proposed method integrates the hierarchical network behavior of pigeon flock and revises the map and compass operator of the original PIO algorithm to improve optimization efficiency. In addition, the landmark operator is used to perform a small-scale search to achieve fast tracking. Based on the combination of these mechanisms and dual-mode dynamic tracking scheme, the proposed hierarchical pigeon-inspired optimization (HPIO) MPPT method has a powerful search ability to deal with PSCs. To verify the superiority of the proposed HPIO MPPT method, it is compared with other existing advanced MPPT methods in simulation and experiments. Compared with traditional MPPT techniques based on artificial intelligence, the proposed HPIO MPPT method has a higher success rate in tracking GMPP and excellent tracking speed under PSCs. And the HPIO method also shows excellent performance under complex PSC with multiple clusters and load-variation conditions.

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Logarithmic PSO-Based Global/Local Maximum Power Point Tracker for Partially Shaded Photovoltaic Systems

Cited by 47 publications

References 45 publications

Design of a Particle Swarm Optimized Photovoltaic system during various partial shading conditions

Design of a Particle Swarm Optimized Photovoltaic system during various partial shading conditions

Blockchain-Based Power Transaction Method for Active Distribution Network

Hierarchical Pigeon-Inspired Optimization-Based MPPT Method for Photovoltaic Systems Under Complex Partial Shading Conditions

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