• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.1-16
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• 2019

Recently, since responding to meteorological changes depending on increasing greenhouse gas and electricity demand, the importance prediction of photovoltaic power (PV) is rapidly increasing. In particular, the prediction of PV power generation may help to determine a reasonable price of electricity, and solve the problem addressed such as a system stability and electricity production balance. However, since the dynamic changes of meteorological values such as solar radiation, cloudiness, and temperature, and seasonal changes, the accurate long-term PV power prediction is significantly challenging. Therefore, in this paper, we propose PV power prediction model based on deep learning that can be improved the PV power prediction performance by learning to use meteorological and seasonal information. We evaluate the performances using the proposed model compared to seasonal ARIMA (S-ARIMA) model, which is one of the typical time series methods, and ANN model, which is one hidden layer. As the experiment results using real-world dataset, the proposed model shows the best performance. It means that the proposed model shows positive impact on improving the PV power forecast performance.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.1
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• pp.51-56
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• 2014

PV cell modeling is necessary both for software and hardware simulators in analyzing and testing the performance of PV generation systems. Unique I-V curve of a PV cell identifies its own characteristics by electrical equivalent model that is composed of diode constants ($I_o$, $v_t$), photo-generated current ($I_{ph}$), series resistance ($R_s$), and shunt resistance ($R_{sh}$). Photo-generated current can be easily estimated since it is proportional to irradiation level. However, other electrical parameters should be solved from the manufacturer's data sheet that is consisted with three remarkable operating points such as open circuit voltage ($V_{oc}$), short circuit current ($I_{sc}$), and maximum power voltage/current ($V_{MPP}/I_{MPP}$). This paper explains and analyzes mathematical process of a novel PV cell modeling algorithm that was proposed by the authors with the name of "K-algorithm".

• Journal of the Korean Solar Energy Society
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• v.37 no.1
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• pp.81-90
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• 2017

We have analyzed the performance of 58 kWp photovoltaic (PV) power systems installed in Jeddah, Saudi Arabia. Performance ratio (PR) of 3 PV systems with 3 desert-type PV modules using monitoring data for 1 year showed 85.5% on average. Annual degradation rate of 5 individual modules achieved 0.26%, the regression model using monitoring data for the specified interval of one year showed 0.22%. Root mean square error (RMSE) of 6 big data analysis models for power output prediction in May 2016 was analyzed 2.94% using a support vector regression model.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.4
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• pp.246-250
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• 2015

Solar energy will be an increasingly important part of power generation because of its ubiquity abundance, and sustainability. To manage effectively solar energy to power system, it is essential part In this paper, we develop the PV power prediction algorithm using adaptive neuro-fuzzy model considering various input factors such as temperature, solar irradiance, sunshine hours, and cloudiness. To evaluate performance of the proposed model according to input factors, we performed various experiments by using real data.

• ETRI Journal
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• v.42 no.1
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• pp.118-128
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• 2020

A semitransparent photovoltaic-thermal (PV/T) air collector can produce electricity and heat simultaneously. To maximize the thermal and overall efficiency of the semitransparent PV/T air collector, its availability should be maximum; this can be determined through a Markov analysis. In this paper, a Markov model is developed to select an optimized number of semitransparent PV modules in service with five states and two states by considering two parameters, namely failure rate (λ) and repair rate (μ). Three artificial neural network (ANN) models are developed to obtain the minimum cost, minimum temperature, and maximum thermal efficiency of the semitransparent PV/T air collector by setting its type appropriately and optimizing the number of photovoltaic modules and cost. An attempt is also made to achieve maximum thermal and overall efficiency for the semitransparent PV/T air collector by using ANN after obtaining its minimum temperature and available solar radiation.

• Proceedings of the KIEE Conference
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• 2003.10b
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• pp.255-258
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• 2003

Photovoltaic(PV) array, which is generally installed outside, has the possibility to be damaged by high voltage due to lightning. Because the electrical characteristics of PV array have not been fully identified by lightning yet, there is a very important issue whether PV array should be connected with ground or not. In this paper, a basic model of PV array is provided considering the PV cell's barrier capacitance and ground capacitance for analysis of electrical characteristics by lightning using PSCAD/EMTDC.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.114-117
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• 2009

The performance of PV module applying the photovoltaic effects of the semiconductor is affected by temperature. Until now, most of PV module show that the power and efficiency falls at a rate of ${\sim}0.5%/^{\circ}C$ and ${\sim}0.05%/^{\circ}C$ respectively as increase of ambient temperature. In this study, the effect of fins attached to the backside of PV module was investigated through a thermal analysis program and simulation model. The result shows that the inner temperature of PV module with fin falls about $10^{\circ}C$ compare to that of ordinary PV module.

• Proceedings of the KIEE Conference
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• 2004.04a
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• pp.208-211
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• 2004

Photovoltaic(PV) array, which is generally installed outside, has the possibility to be damaged by high voltage due to lightning. Because the electrical characteristics of PV array have not been fully identified by lightning yet, there is a very important issue whether PV array should be connected with ground or not. In this paper, a basic model of PV array is provided considering the PV cell's barrier capacitance and ground capacitance for analysis of electrical characteristics by lightning using PSCAD/EMTDC.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.2
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• pp.27-32
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• 2015

A maximum power point tracking (MPPT) algorithm using fuzzy controller was considered. MPPT method was implemented based on the voltage and reference PV voltage value was obtained from Artificial Neural Network (ANN)-model of PV modules. Therefore, measuring only the PV module voltage is adequate for MPPT operation. Fuzzy controller is used to directly control dc-dc buck converter. The simulation results have been used to verify the effectiveness of the algorithm. The proposed method is compared with conventional PO(perturbation & observation), IC(Incremental Conductance) method. The nonlinearity and adaptiveness of fuzzy controller provided good performance under parameter variations such as solar irradiation.

• 한국신재생에너지학회:학술대회논문집
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• 2006.06a
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• pp.121-124
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• 2006

In the newly developed control method, the current flowing into SPE cell is the only one considerable factor. So, the structure of control circuit becomes simple and the manufacturing cost of the control device decreases. In conventional power comparison MPPT control method however, a voltage and current coming out from PV cell should be feedbacked to chase maximum power point at every moment. Then, the structure of control circuit becomes so complex and the risk of control failure is much higher than the novel MPPT control method. Therefore, PV generation system by a novel MPPT control method is especially operated much more safely in case of a huge system, because the voltage coming out from PV-cell is not needed to be feedbacked. In this paper, the PV-SPR system was actually manufactured based on the simulation model of PSCAD/EMTDC program and the results tested were shown. Authors are sure that it is the most useful method to maximize power from PV to SPE with only a feedback of SPE input current.