Influence of Artificial and Natural Cooling on Performance Parameters of a Solar PV System: A Case Study

Chandra, Sudhir; Yadav, Arvind; Khan, Mohd Abdul Rahim; Pushkarna, Mukesh; Bajaj, Mohit; Sharma, Naveen Kumar

doi:10.1109/access.2021.3058779

Cited by 17 publications

(5 citation statements)

References 20 publications

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“…Our research adds to the discussion on sustainable energy practices, offering valuable insights for managing the challenges of shifting towards renewable and ecologically friendly energy sources. Given the historical development of energy sources, the present difficulties, and the urgent need for sustainable options, our study becomes important and pertinent in tackling modern energy challenges 13 , 14 .…”

Section: Introductionmentioning

confidence: 99%

A multilayer perceptron neural network approach for optimizing solar irradiance forecasting in Central Africa with meteorological insights

Mfetoum,

Ngoh,

Molu

et al. 2024

Sci Rep

Self Cite

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Promoting renewable energy sources, particularly in the solar industry, has the potential to address the energy shortfall in Central Africa. Nevertheless, a difficulty occurs due to the erratic characteristics of solar irradiance data, which is influenced by climatic fluctuations and challenging to regulate. The current investigation focuses on predicting solar irradiance on an inclined surface, taking into consideration the impact of climatic variables such as temperature, wind speed, humidity, and air pressure. The used methodology for this objective is Artificial Neural Network (ANN), and the inquiry is carried out in the metropolitan region of Douala. The data collection device used in this research is the meteorological station located at the IUT of Douala. This station was built as a component of the Douala sustainable city effort, in partnership with the CUD and the IRD. Data was collected at 30-min intervals for a duration of around 2 years, namely from January 17, 2019, to October 30, 2020. The aforementioned data has been saved in a database that underwent pre-processing in Excel and later employed MATLAB for the creation of the artificial neural network model. 80% of the available data was utilized for training the network, 15% was allotted for validation, and the remaining 5% was used for testing. Different combinations of input data were evaluated to ascertain their individual degrees of accuracy. The logistic Sigmoid function, with 50 hidden layer neurons, yielded a correlation coefficient of 98.883% between the observed and estimated sun irradiation. This function is suggested for evaluating the intensities of solar radiation at the place being researched and at other sites that have similar climatic conditions.

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Section: Introductionmentioning

confidence: 99%

A multilayer perceptron neural network approach for optimizing solar irradiance forecasting in Central Africa with meteorological insights

Mfetoum,

Ngoh,

Molu

et al. 2024

Sci Rep

Self Cite

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“…In study [17], the simulation and evaluation of the performance of the interaction between the thermal and electrical losses in the interconnections of the modules and the influence of the tabulation on the power and temperature of modules installed in Qatar and Germany are carried out, comparing the impact of energy and temperature losses under different levels of irradiation and ambient temperature. Chandra et al [18] carry out a technical and economic evaluation to determine that temperature and natural wind cooling significantly affect the performance of the photovoltaic module.…”

Section: Methodsmentioning

confidence: 99%

Influence of ambient temperature in the city of Portoviejo, Ecuador on the energy performance of photovoltaic modules

Epeni-Tombo

Rodríguez-Gámez²,

Castillo³

et al. 2023

IJECE

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<span lang="EN-US">The research analyzes the influence of the average temperature on the performance of specific photovoltaic solar modules under the environmental conditions of the city of Portoviejo, province of Manabí, Ecuador. The research is carried out using the qualitative methodology. Its main objective is to determine the influence of temperature on the energy performance of photovoltaic modules under the region's environmental conditions. Two electrical diagrams with different configurations were designed, which were analyzed and simulated using the MATLAB Simulink software. The results obtained show the direct relationship between the electrical parameters of voltage, current intensity, and power with the temperature value on the surface of the modules. It is concluded that the modules generate a higher value of voltage, electric current intensity, and electric power at a lower temperature, regardless of the level of solar irradiation they receive.</span>

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“…The output of solar energy is a property of the photovoltaic panels' rated capacity, and the PV de-rating factor, a measuring factor, permits the impact of many losses that may cause the PV module's output to be less than what it was originally [26]. The power generated by solar photovoltaics' (SPV) can be visualized as [26] follows: If β a is overlooked in the PV interface grid system, then the power outcome may be conveyed as follows:…”

Section: Photovoltaic Modelingmentioning

confidence: 99%

Horse Herd Optimized Intelligent Controller for Sustainable PV Interface Grid-Connected System: A Qualitative Approach

Ganguly

Biswas

Sain³

et al. 2023

Sustainability

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The need for energy is always increasing as civilization evolves. Renewable energy sources are crucial for meeting energy demands as conventional fuel resources are slowly running out. Researchers are working to extract the most amount of power possible from renewable resources. Numerous resources are in demand, including solar, wind, biomass, tidal, and geothermal resources. Solar energy outperformed all the aforementioned resources in terms of efficiency, cleanliness, and pollution freeness. Intermittency, however, is the resource’s main shortcoming. Maximum power point tracking algorithm (MPPT) integration is required for the system to achieve continuous optimum power by overcoming the feature of intermittency. However, generating electrical energy from solar energy has presented a significant problem in ensuring the output power’s quality within a reasonable range. Total harmonic distortion (THD), a phenomenon, may have an impact on the power quality. Depending on the properties of the load, variables like power factor, voltage sag/swell, frequency, and unbalancing may occur. The quality of power and its criterion exhibits a non-linear connection. The article’s primary objective is to analyze the PV interface grid-linked system’s qualitative and quantitative performance. With respect to varying solar irradiation conditions, partial shading conditions, and solar power quality within the acceptable dimension, a novel intelligent multiple-objective horse herd optimization (HHO)-based adaptive fractional order PID (HHO-AFOPID) controller is used to achieve this goal. Adaptive fractional order PID (AFOPID), conventional FOPID, and PID controllers were used to evaluate the performance of the suggested controller, which was then validated using a commercially available PV panel in MATLAB/Simulink by varying the productivity of non-conventional resources, the inverter’s level of uncertainty, and the potential at the grid’s end. In order to realize the features of the system, sensitivity examination is also carried out for solar energy’s sensitive parameters. The stability analysis of the proposed control topology is also carried out in terms of the integral absolute error (IAE) and integral time absolute error (ITAE). The examination of the sensitivity of variations in solar radiation in kilowatt per square meter per day is based on the total net present cost (TNPC) and levelized cost of energy (LCOE), as optimal dimension and energy cost are both aspects of priority. The suggested control methodology is an approach for the qualitative and quantitative performance analysis of a PV interface grid-oriented system.

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Influence of Artificial and Natural Cooling on Performance Parameters of a Solar PV System: A Case Study

Cited by 17 publications

References 20 publications

A multilayer perceptron neural network approach for optimizing solar irradiance forecasting in Central Africa with meteorological insights

A multilayer perceptron neural network approach for optimizing solar irradiance forecasting in Central Africa with meteorological insights

Influence of ambient temperature in the city of Portoviejo, Ecuador on the energy performance of photovoltaic modules

Horse Herd Optimized Intelligent Controller for Sustainable PV Interface Grid-Connected System: A Qualitative Approach

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