Impact of temperature and dust deposition on PV panel performance

Hasan, Dawood Salman; Farhan, Mansour S.; Alrikabi, Haider Th.Salim

doi:10.1063/5.0121013

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…As in the preceding case study, When compared to other methods currently in use, the simulation results above make it abundantly obvious that the suggested algorithm performed admirably. When compared to other current methods described in [23][24][25][28][29][30][31], the convergence process time is found to be very fast and promising. In designing the PSS-TCSC Controller, it is clear that PSO-SFLA has outperformed in terms of accuracy, damping performance, minimum overshoot/undershoot response, and minimum settling time for both speed and rotor angle deviation responses.…”

Section: Resultsmentioning

confidence: 92%

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A novel approach for coordinated design of TCSC controller and PSS for improving dynamic stability in power systems

Alwan¹

2023

PEN

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The purpose of this article is to present a novel strategy for the coordinated design of the Thyristor Controlled Series Compensator (TCSC) controller and the Power System Stabilizer (PSS). A time domain objective function that is based on an optimization problem has been defined. This objective function takes into account not only the influence that disturbances have on the mechanical power, but also, and this is more accurately the case, the impact that disturbances have on the reference voltage. When the objective function is minimized, potential disturbances are quickly mitigated, and the deviation of the speed of the generator's rotor is limited; as a result, the system's stability is ultimately improved. Particle Swarm Optimization (PSO) and the Shuffled Frog Leaping Algorithm are both components of a composite strategy that is utilized in the process of determining the optimal controller parameters. (SFLA). An independent controller design as well as a collaborative controller design utilizing PSS and TCSC are developed, which enables a direct evaluation of the functions performed by each. The presentation of the eigenvalue analysis and the findings of the nonlinear simulation can help to provide a better understanding of the efficacy of the outcomes. The findings indicate that the coordinated design is able to successfully damp low-frequency oscillations that are caused by a variety of disturbances, such as changes in the mechanical power input and the setting of the reference voltage, and significantly enhance system stability in power systems that are connected weekly.

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Section: Resultsmentioning

confidence: 92%

“…cooperation [23][24][25][26]. Indeed, the use of an inertia weight was inspired from the Particle Search Optimization (PSO), which utilizes a similar concept [26][27][28][29][30].…”

Section: Improvements On Basic Sflamentioning

confidence: 99%

A novel approach for coordinated design of TCSC controller and PSS for improving dynamic stability in power systems

Alwan¹

2023

PEN

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“…High temperatures can cause the panels to degrade and their performance to deteriorate, reducing the power generation capacity of the system. Solar panels also become less efficient at high temperatures, further lowering the efficiency of energy conversion [20]. Additionally, the overlays will increase the maintenance cost of the PV power generation system [21].…”

Section: Introductionmentioning

confidence: 99%

A Survey of Photovoltaic Panel Overlay and Fault Detection Methods

Yang,

Sun,

Zou

et al. 2024

Energies

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Photovoltaic (PV) panels are prone to experiencing various overlays and faults that can affect their performance and efficiency. The detection of photovoltaic panel overlays and faults is crucial for enhancing the performance and durability of photovoltaic power generation systems. It can minimize energy losses, increase system reliability and lifetime, and lower maintenance costs. Furthermore, it can contribute to the sustainable development of photovoltaic power generation systems, which can reduce our reliance on conventional energy sources and mitigate environmental pollution and greenhouse gas emissions in line with the goals of sustainable energy and environmental protection. In this paper, we provide a comprehensive survey of the existing detection techniques for PV panel overlays and faults from two main aspects. The first aspect is the detection of PV panel overlays, which are mainly caused by dust, snow, or shading. We classify the existing PV panel overlay detection methods into two categories, including image processing and deep learning methods, and analyze their advantages, disadvantages, and influencing factors. We also discuss some other methods for overlay detection that do not process images to detect PV panel overlays. The second aspect is the detection of PV panel faults, which are mainly caused by cracks, hot spots, or partial shading. We categorize existing PV panel fault detection methods into three categories, including electrical parameter detection methods, detection methods based on image processing, and detection methods based on data mining and artificial intelligence, and discusses their advantages and disadvantages.

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