Sensitivity analysis of implicit correlations for photovoltaic module temperature: A review

Coşkun, Can; Toygar, Ugurtan; Sarpdag, Ozgur; Oktay, Zuhal

doi:10.1016/j.jclepro.2017.07.080

Cited by 82 publications

(30 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The presented models were examined and compared with the data obtained experimentally. The results obtained showed the extent of the agreement and the convergence between the calculated and the measured temperature of the eight models [18,19]. The level of uncertainty was investigated by comparing the performance of a simple photovoltaic model with the AC power of three photovoltaic systems when the measurements of the site module temperature and the plane of array irradiance were not available [20].…”

Section: Introductionmentioning

confidence: 96%

ANN for Assessment of Energy Consumption of 4 kW PV Modules over a Year Considering the Impacts of Temperature and Irradiance

2019

View full text Add to dashboard Cite

Solar energy is considered the greatest source of renewable energy. In this paper, a case study was performed for a single-axis solar tracking model to analyze the performance of the solar panels in an office building under varying ambient temperatures and solar radiation over the course of one year (2018). This case study was performed in an office building at the College of Engineering at Shaqra University, Dawadmi, Saudi Arabia. The office building was supplied with electricity for a full year by the designed solar energy system. The study was conducted across the four seasons of the studied year to analyze the performance of a group of solar panels with the total capacity of a 4 kW DC system. The solar radiation, temperature, output DC power, and consumed AC power of the system were measured using wireless sensor networks (for temperature and irradiance measurement) and a signal acquisition system for each hour throughout the whole day. A single-axis solar tracker was designed for each panel (16 solar panels were used) using two light-dependent resistors (LDR) as detecting light sensors, one servo motor, an Arduino Uno, and a 250 W solar panel installed with an array tilt angle of 21 • . Finally, an artificial neural network (ANN) was utilized to estimate energy consumption, according to the dataset of AC load power consumption for each month and the measurement values of the temperature and irradiance. The relative error between the measured and estimated energy was calculated in order to assess the accuracy of the proposed ANN model and update the weights of the training network. The maximum absolute relative error of the proposed system did not exceed 2 × 10 −4 . After assessment of the proposed model, the ANN results showed that the average energy in the region of the case study from a 4 kW DC solar system for one year, considering environmental impact, was around 8431 kWh/year. Sustainability 2019, 11, 6802 2 of 24 to develop previously discovered energy sources to eliminate the damage caused by non-renewable sources and to also compensate for the depletion of non-renewable resources in the future [1,2]. Solar energy has always been a promising source of renewable energy. It continues to attract research into its optimal development and utilization as a result of the good response and remarkable developments in solar energy systems to date. There has been a consistent, significant increase in the number of researchers investigating photovoltaic (PV) solar cells. In recent years, significant and remarkable developments have been observed in solar energy systems, which have led to a significant increase in the renewable energy market, with more solar energy systems being installed [3]. According to the REN21 (2018) Global Status Report, 2017 was a very important year in the field of solar energy, representing the increase of solar energy system installation above any other renewable energy technology. According to this report, at least 98 GW of grid-connected and off-grid solar energy systems were installe...

show abstract

Section: Introductionmentioning

confidence: 96%

ANN for Assessment of Energy Consumption of 4 kW PV Modules over a Year Considering the Impacts of Temperature and Irradiance

2019

View full text Add to dashboard Cite

show abstract

“…The author considered T a in (°C), G sr in (W/m 2 ), and W v in (m/s). The same model is reported by [41].…”

Section: Existing Photovoltaic Module Temperature Modelsmentioning

confidence: 55%

An Improved Empirical Model for Estimation of Temperature Effect on Performance of Photovoltaic Modules

Jatoi

Samo

Jakhrani

2019

International Journal of Photoenergy

View full text Add to dashboard Cite

It is prerequisite to predict the behaviour of photovoltaic (PV) modules in a particular geographical area where the system is to be installed for their better performance and increasing lifetime. For that, models are the easiest and acceptable tools to characterise the behaviour of PV modules in any location. The purpose of this study was to develop an empirical model to predict the influence of temperature on the performance of four different PV module technologies, namely, polycrystalline, monocrystalline, amorphous, and thin film in an outdoor environment. The model has been developed by fitting of one year experimental data using the least squares method. The estimated results of the developed model were validated with real-time data (winter and summer season) and a comparison of other existing model estimates using error analysis with 95% confidence interval. The proposed model estimations confirm that the monocrystalline module performs better in winter and polycrystalline in summer as compared to amorphous and thin film in the study area. During analysis, it is revealed that developed model results are more precise and appropriate among other existing model estimations. It is concluded that the proposed model estimations could be used for the prediction of PV module temperature in similar environmental conditions as that of the study area with more accuracy and confidence. It ultimately helps to develop cost-effective and efficient PV systems.

show abstract

“…The temperature at any point in the PV module is assumed to be constant within this short time interval. The nominal operating cell temperature (NOCT) represents an indication of the PV module temperature and it is supplied by its manufacturer, and this value is acquired according to the parameters provided by the standard reference environment (SRE), which determines the inclination of the module equal to the local latitude, total irradiance (GNOCT) of 800 W/m², ambient temperature (Ta) equal to 20°C, wind speed (Vw) of 1 m/s and zero electric charge [11]. The models are based on the fact that the difference between the module temperature and the ambient temperature is independent of the air temperature, however it is directly proportional to the irradiance if the on-site conditions are fixed.…”

Section: Methodsmentioning

confidence: 99%

Photovoltaic Cell Temperature Estimation for a Grid-Connect Photovoltaic Systems in Curitiba

Yang

Tiepolo

Tonolo

et al. 2019

Braz. arch. biol. technol.

View full text Add to dashboard Cite

equations proposed over the last decades by researchers. This estimation will occur in the municipality of Curitiba, using data from INMET's automatic station, located in the same city. The estimation was calculated hourly, throughout the day for one year. The validation of the estimated results was performed by measuring the cell temperature of a photovoltaic system installed in Curitiba, where it was observed that the equation proposed by Duffie and Beckman (2013) was the one that most approached to the measured value.

show abstract

Sensitivity analysis of implicit correlations for photovoltaic module temperature: A review

Cited by 82 publications

References 16 publications

ANN for Assessment of Energy Consumption of 4 kW PV Modules over a Year Considering the Impacts of Temperature and Irradiance

ANN for Assessment of Energy Consumption of 4 kW PV Modules over a Year Considering the Impacts of Temperature and Irradiance

An Improved Empirical Model for Estimation of Temperature Effect on Performance of Photovoltaic Modules

Photovoltaic Cell Temperature Estimation for a Grid-Connect Photovoltaic Systems in Curitiba

Contact Info

Product

Resources

About