In-field monitoring of eight photovoltaic plants: degradation rate along seven years of continuous operation

Carullo, Alessio; Castellana, Antonella; Vallan, Alberto; Ciocia, Alessandro; Spertino, Filippo

doi:10.21014/acta_imeko.v7i4.599

Cited by 12 publications

(6 citation statements)

References 11 publications

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“…These panels are also referred to as 'many-crystal' or 'multi-crystalline' silicon. Since there are many crystals in each cell, the electrons have less freedom to move; this results in lower efficiency than that typical of the mono-Si panels [42].…”

Section: Discussionmentioning

confidence: 99%

Sensors-based mobile robot for harsh environments: functionalities, energy consumption analysis and characterization

et al. 2021

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Mobile robots and rovers play an important role in many industrial applications. Under certain constraints, they are suitable in harsh environments and conditions in which protracted human activity is not safe or permitted. In many circumstances, mechanical aspects and electrical consumption need to be optimized for autonomous and wheeled mobile robots. The paper illustrates the design of a semi-custom wheeled mobile robot with high-efficiency mono- or polycrystalline photovoltaic panel on the roof that supports the lithium ion batteries during particular tasks (e.g. navigating rough terrain, obstacles or steep paths) to extend the robot’s autonomy. An electronic controller was designed, and data acquisition related to power consumption performed using a specific experimental setup. The robot can detect parameters such as temperature, humidity, concentrations of toxic gas species and the presence of flames, making it particularly suitable for contaminated environments or industrial plants. For this aim, the mobile robot was equipped with a wide range of commercial sensors and a Global Positioning System receiver to track its position. In addition, using an HC-06 Bluetooth transceiver, the robot receives commands and instructions, and sends the acquired data to the developed IoTool smartphone application, where they are displayed to be analysed by user.

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Section: Discussionmentioning

confidence: 99%

Sensors-based mobile robot for harsh environments: functionalities, energy consumption analysis and characterization

et al. 2021

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“…The renormalization is less fundamental when performing a space comparison during a given period because it is supposed that nearby wind turbines are subjected to reasonably similar conditions. Regarding this point, the literature also provides more complex renormalization methods [10,24] based on statistical analysis or design specifications in order to compensate for the absence of a ground-truth reference.…”

Section: Scada Data Analysismentioning

confidence: 99%

Advanced Methods for Wind Turbine Performance Analysis Based on SCADA Data and CFD Simulations

et al. 2023

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Deep comprehension of wind farm performance is a complicated task due to the multivariate dependence of wind turbine power on environmental variables and working parameters and to the intrinsic limitations in the quality of SCADA-collected measurements. Given this, the objective of this study is to propose an integrated approach based on SCADA data and Computational Fluid Dynamics simulations, which is aimed at wind farm performance analysis. The selected test case is a wind farm situated in southern Italy, where two wind turbines had an apparent underperformance. The concept of a space–time comparison at the wind farm level is leveraged by analyzing the operation curves of the wind turbines and by comparing the simulated average wind field against the measured one, where each wind turbine is treated like a virtual meteorological mast. The employed formulation for the CFD simulations is Reynolds-Average Navier–Stokes (RANS). In this work, it is shown that, based on the above approach, it has been possible to identify an anemometer bias at a wind turbine, which has subsequently been fixed. The results of this work affirm that a deep comprehension of wind farm performance requires a non-trivial space–time comparison, of which CFD simulations can be a fundamental part.

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“…The easiest way is the use of a resistive load with variable resistance; nevertheless, this method has a long duration because a resistance linearly varies from zero to infinity in order to scan the points of the I-V curve of the generator [22]. On the contrary, the tests are easily and rapidly performed by the transient charge of a capacitive load [23,24]. An external capacitor, initially discharged, is charged by the PV array from short-circuit to open-circuit conditions.…”

Section: I-v Curve Characterizationmentioning

confidence: 99%

“…Considering the analysis in references [86][87][88], Rout is calculated as follows For this purpose, it is necessary to find R out . The operation of the PV is still in the current source region assuming that it has voltage V 1 and current I 1 , and using Equation (24), R out is calculated. The next step is to find the values of I 2 and V 2 in Equation (23).…”

Section: Application Of Submodule Integrated Mppt With Fault Diagnosismentioning

confidence: 99%

Detection of Typical Defects in Silicon Photovoltaic Modules and Application for Plants with Distributed MPPT Configuration

et al. 2019

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During their operational life, photovoltaic (PV) modules may exhibit various defects for poor sorting of electrical performance during manufacturing, mishandling during transportation and installation, and severe thermo-mechanical stresses. Electroluminescence testing and infrared thermographic imaging are the most common tests for checking these defects, but they are only economically viable for large PV plants. The defects are also manifested as abnormal electrical properties of the affected PV modules. For defect diagnosis, the appropriate parameters on their I-V curves are open circuit voltage, photo-generated current, series resistance, and the shunt resistance. The health of PV modules can be assessed by calculating these values and comparing them with the reference parameters. If these defects are diagnosed in time, the power loss is avoided and safety hazards are mitigated. This paper first presents a review of common defects in PV modules and then a review of the methods used to find the above-mentioned parameters during the normal PV operation. A simple approach to determine the resistances of the equivalent circuit is discussed. Finally, through a modification in an ordinary maximum power point tracking (MPPT) algorithm, information about the state of health of PV modules is obtained. This method is effective, especially if applied to submodule-integrated MPPT architectures.

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In-field monitoring of eight photovoltaic plants: degradation rate along seven years of continuous operation

Cited by 12 publications

References 11 publications

Sensors-based mobile robot for harsh environments: functionalities, energy consumption analysis and characterization

Sensors-based mobile robot for harsh environments: functionalities, energy consumption analysis and characterization

Advanced Methods for Wind Turbine Performance Analysis Based on SCADA Data and CFD Simulations

Detection of Typical Defects in Silicon Photovoltaic Modules and Application for Plants with Distributed MPPT Configuration

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