Performance degradation issues of PV solar power plant

Begum, S. Nathira; Banu, R. S. D. Wahida; Ahammed, G. F. Ali; Rajashekarappa,

doi:10.1109/iceeccot.2017.8284518

Cited by 50 publications

(3 citation statements)

References 5 publications

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“…4 shows a declining trend of the solar PV output of the 2-year period after its installation. A negative slope regression line confirms the theory of the degradation of solar PV system over time [ 32 ]. The estimated slope of the trend line of −244.37 reveals that the output production of the solar PV system reduces steadily by an average of 244.37 kWh per month.…”

Section: Resultssupporting

confidence: 77%

Machine learning forecasting of solar PV production using single and hybrid models over different time horizons

Asiedu,

Nyarko,

Boahen

et al. 2024

Heliyon

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Section: Resultssupporting

confidence: 77%

Machine learning forecasting of solar PV production using single and hybrid models over different time horizons

Asiedu,

Nyarko,

Boahen

et al. 2024

Heliyon

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“…The proposed system shows better result and this has a drawback that this mechanism only detects the trains having this GPS and GSM systems. Shahida et al [7] analyzed the performance degradation issues regarding PV(Photovoltaic ) solar plant. This paper discussed the failure of the solar plants in real time environment.…”

Section: Literature Reviewmentioning

confidence: 99%

Automatic Railway Level Crossing System with Embedded Precision Solar Panel using IoT

Raj¹,

Kumar²,

Kumar³

2019

IJRTE

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Indian Railways is one of the public transportation modes in the country. It is the largest interconnected rail routes which carry many numbers of people from one end to another end. In this, various level crossings are operated on the rail routes and some of the level crossing gates are operated manually. This process is carried out by getting the information from the previous station once the train left the station. In this process, lots of mishaps are occurring due to human interventions and also there is no safety for road users. This issue can be overcome by making the same process in an automated manner. Hence, in this research work, a new automated level crossing model is proposed using the technology “Internet of Things” (IoT). This model will provide

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“…However, grid parity can only be reached by providing the full functionality of energy plants and by reducing maintenance costs [8,9]. According to smart operation and maintenance approaches, effective monitoring systems are needed to timely detect any malfunction event and yield loss [10], thus (i) reducing production issues and (ii) allowing an accurate evaluation of failures.…”

Section: Introductionmentioning

confidence: 99%

Using EMPHASIS for the Thermography-Based Fault Detection in Photovoltaic Plants

et al. 2021

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In this paper, an Efficient Method for PHotovoltaic Arrays Study through Infrared Scanning (EMPHASIS) is presented; it is a fast, simple, and trustworthy cell-level diagnosis method for commercial photovoltaic (PV) panels. EMPHASIS processes temperature maps experimentally obtained through IR cameras and is based on a power balance equation. Along with the identification of malfunction events, EMPHASIS offers an innovative feature, i.e., it estimates the electrical powers generated (or dissipated) by the individual cells. A procedure to evaluate the accuracy of the EMPHASIS predictions is proposed, which relies on detailed three-dimensional (3-D) numerical simulations to emulate realistic temperature maps of PV panels under any working condition. Malfunctioning panels were replicated in the numerical environment and the corresponding temperature maps were fed to EMPHASIS. Excellent results were achieved in both the cell- and panel-level power predictions. More specifically, the estimation of the power production of a PV panel with a shunted cell demonstrated an error lower than 1%. In cases of strong nonuniformities as a PV panel in hotspot, an estimation error in the range of 9–16% was quantified.

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Performance degradation issues of PV solar power plant

Cited by 50 publications

References 5 publications

Machine learning forecasting of solar PV production using single and hybrid models over different time horizons

Machine learning forecasting of solar PV production using single and hybrid models over different time horizons

Automatic Railway Level Crossing System with Embedded Precision Solar Panel using IoT

Using EMPHASIS for the Thermography-Based Fault Detection in Photovoltaic Plants

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