Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm

Odat, Alhaj-Saleh A.; Shawaqfah, Moayyad; Al-Momani, Fares; Shboul, Bashar

doi:10.1016/j.dib.2023.109853

Cited by 2 publications

(2 citation statements)

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“…This improves the search results. The thicker tail of the Cauchy distribution is a key characteristic [16]. As a result, its probability distributions are not bounded exponentially.…”

Section: Proposed Cauchy Pso Methodsmentioning

confidence: 99%

“…In order to maximise the power extracted from PV systems that are partially or evenly shaded, a special and effective technique is needed described in [15]. This article describes tracking techniques for photovoltaic (PV) systems that use sequential Monte Carlo (SMC) based algorithms [16]. Aims to enhance MPPT performance in solar systems by the "Fuzzy Logic" control technique in [17].…”

Section: Introductionmentioning

confidence: 99%

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Elaboration of a Cauchy PSO based on MPPT for photovoltaic systems in comparison with classical MPPT techniques in partial shading scenarios.

saha

2024

Preprint

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To different environmental circumstances, the solar cells' output power exhibits a nonlinear current-voltage characteristic. Photovoltaic (PV) systems use Maximum Power Point Tracking (MPPT) to optimise their output power. In this study, a novel MPPT controller is suggested. The MPPT design is approached as an optimisation issue, the solution to which is found by using Cauchy PSO to determine the ideal controller settings. According to simulation data, the suggested method maximises the photovoltaic system's power output under a variety of environmental circumstances. Particle Swarm Optimisation (PSO) and the created Cauchy PSO method work similarly. This method has the benefit of providing the globally best-optimized output at a quicker rate of convergence. It can monitor the MP in variable load scenarios and harsh weather conditions. In addition to having a simpler structure, the suggested technique performs better in terms of rapid convergence than the normal PSO and some of the other methods.

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“…This improves the search results. The thicker tail of the Cauchy distribution is a key characteristic [16]. As a result, its probability distributions are not bounded exponentially.…”

Section: Proposed Cauchy Pso Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Elaboration of a Cauchy PSO based on MPPT for photovoltaic systems in comparison with classical MPPT techniques in partial shading scenarios.

saha

2024

Preprint

View full text Add to dashboard Cite

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A Comprehensive Review on Uncertainty and Risk Modeling Techniques and Their Applications in Power Systems

Afzali,

Hosseini,

Peyghami

2024

Applied Sciences

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The increasing integration of renewable energy sources (RESs) into power systems has introduced new complexities due to the inherent variability and uncertainty of these energy sources. In addition to the uncertainty in RES generation, the demand-side load of power systems is also subject to fluctuations, further complicating system operations. Addressing these challenges requires effective modeling and assessment techniques to quantify and mitigate the risks associated with system uncertainties. This paper evaluates the impact of various uncertainty modeling techniques on power system reliability with wind farm integration. Furthermore, this paper reviews the state of the art of the various uncertainty and risk modeling techniques in power systems. Through a detailed case study, the performance of these techniques in modeling uncertainties of wind speeds is analyzed. Based on the results, the integration of wind turbines improves the system’s overall reliability when there is a reduction in conventional power plants (CPPs)’ generation, which are dispatchable energy sources providing a stable and flexible supply. However, the generation of wind farms is associated with uncertainty. The results show Monte Carlo simulation combined with the K-Means method is consistently a more accurate uncertainty model for wind speeds, closely aligning with real-case scenarios, compared to other methods such as Markov Chain Monte Carlo (MCMC), robust optimization (RO), and information-gap decision theory (IGDT).

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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm

Cited by 2 publications

References 5 publications

Elaboration of a Cauchy PSO based on MPPT for photovoltaic systems in comparison with classical MPPT techniques in partial shading scenarios.

Elaboration of a Cauchy PSO based on MPPT for photovoltaic systems in comparison with classical MPPT techniques in partial shading scenarios.

A Comprehensive Review on Uncertainty and Risk Modeling Techniques and Their Applications in Power Systems

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