• Journal of the Korean Solar Energy Society
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• v.33 no.4
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• pp.89-93
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• 2013

In recent years, many investigations about photovoltaic power systems have been significantly carried out in the fields of renewable power energy. Such research area generally includes developments of highly efficient solar cells, advanced power conversion systems, and smart monitoring systems. A generic objective of fault detection and diagnosis techniques is to timely recognize unexpected faulty of dynamic systems so that economic demage occurred by such faulty is decreased by means of engineering techniques. This paper presents a novel fault detection approach for photovoltaic power arrays which are electrically connected in series and parallels. In the proposed fault detection scheme, we first measure all of photovoltaic modules located in each array by using electronic sense systems and then compare each measurement in turn to detect location of fault module through statistic computation algorithm. We accomplish real-time experiments to demonstrate our proposed fault detection methodology by using a test-bed system including two 20 watt photovoltaic modules.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.2
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• pp.119-127
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• 2008

In this paper, the modular line-connected photovoltaic PCS (photovoltaic power conditioning system) is proposed. A step-up DC-DC converter using a active-clamp circuit and a dual series-resonant rectifier is proposed to achieve a high efficiency and a high input-output voltage ratio efficiently. An IncCond (incremental conductance) MPPT (maximum power point tracking) algorithm that improves MPPT characteristic is used. The PV module current is estimated without using a DC current sensor. By control a inverter using a linearized output current controller, a unity power factor is achieved. All algorithms and controllers are implemented on a single-chip microcontroller and the superiority of the proposed DC-DC converter and controllers is proved by experiments.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.591-596
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• 2012

Recently, the efficient management system for photovoltaic power plants has been required due to the continuously increasing construction of photovoltaic power plants. In this paper, we propose a cloud-based intelligent management system for many photovoltaic power plants. The proposed system stores the measured data of power plants using Hadoop HBase which is a column-oriented database, and processes the calculations of performance, efficiency, and prediction the amount of power generation by parallel processing based on Map-Reduce model. And, Web-based data visualization module allows the administrator to provide information in various forms.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.6
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• pp.37-47
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• 2008

Photovoltaic power generation is currently being recognized as one of the most popular sources for renewable resources over the country. Although it is also being adapted to rural area for may reasons, it is important to estimate the magnitudes of power outputs with reliable statistical methodologies, while applying historical daily solar energy data, for correct feasibility analysis. In this study, one of the well-known statistical methodologies is employed to define the appropriate probability distributions for monthly power outputs for the selected rural area, county of Seo-san, province of Chungnam. The results imply that the assumption of normal distributions for several months may lead to incorrect decision-making and therefore lead to the unreliable feasibility analysis. Generalized beta and triangular distributions were found to be superior to normal distribution, when describing monthly probability distributions for daily photovoltaic power. Based on the appropriate distributions resulted from this study, Monte Carlo simulation technique was also applied to provide additional flexible information for the relevant decision makers. This study found out new finding that the probability distributions should be considered to make planning of the photovoltaic power system in rural village unit, in order to give reasonable economic analysis to the decision makers.

• International Journal of Advanced Culture Technology
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• v.4 no.1
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• pp.37-50
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• 2016

In recent years, the development and application of green energy resources have attracted more and more /$^*$ 'tention of people. The training room presented here is focused on the terminal applications of a photovoltaic power generation system (PPGS). Through introducing the composition and the general design principles, we aimed at leading the students to master the fundamental skills required for its design, installation and construction. The training room consists of numerous platforms, such as: PPGS, Wind and Photovoltaic Hybrid Power Generation Systems, Wind Power Generation Equipments, Simulative Grid-Connected Power Generation System, Electronic Technology Application of New Energy, etc. This enables the students to obtain their project and professional skills training via assembling, adjusting, maintaining and inspecting, etc., various component parts of the photovoltaic and new energy power generation systems, to further grasp the fundamental and related theoretical knowledge, and to further reinforce their practical and operational skills, so as to improve their problem-analyzing and problem-solving abilities.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.644-649
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• 2001

This paper proposes a soft-switching current -source inverter for photovoltaic power system, which has an H-type switched-capacitor module composed of two semiconductor switches, two diodes, and an L-C resonant circuit. The operation of proposed system was analyzed by a theoretical approach with equivalent circuits and verified by computer simulations with SPICE and experimental works with a hardware prototype. The proposed system could be effectively applied for the power converter of photovoltaic power system interconnected with the power system.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1171-1173
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• 2000

This paper was analyzed the high-frequency harmonics, power conversion rate, results of the system's monitor, and measuring data of the system power output of a 3-phase photovoltaic power system for grid-connection. The photovoltaic power system consists of a 3-phase inverter array, and data acquisition system. The result of an analyzing data of the 50 kW class grid-connected photovoltaic system showed the stable behavior in utility-interactive operation.

• Journal of Integrative Natural Science
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• v.11 no.4
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• pp.204-208
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• 2018

Comparison of different optimizer performance in photovoltaic power modeling using artificial neural deep learning techniques is described in this paper. Six different deep learning optimizers are tested for Long-Short-Term Memory networks in this study. The optimizers are namely Adam, Stochastic Gradient Descent, Root Mean Square Propagation, Adaptive Gradient, and some variants such as Adamax and Nadam. For comparing the optimization techniques, high and low fluctuated photovoltaic power output are examined and the power output is real data obtained from the site at Mokpo university. Using Python Keras version, we have developed the prediction program for the performance evaluation of the optimizations. The prediction error results of each optimizer in both high and low power cases shows that the Adam has better performance compared to the other optimizers.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.183-186
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• 2009

The crystalline silicon solar cell was one of the first to be developed and it is still the most widely used type. The photovoltaic cells will exhibit long-term degradation if the temperature exceed a certain limit. The purpose of this study is to investigate the possible of improving the performance of a photovoltaic cooling system. According to the results of the experiment, the thermal degradation of 44.63degrees was observed by cooling on the surface of photovoltaic cells. It is a decrease of 22.215percent of generating power. It is shown that photovoltaic cooling system is effected on improving the effectiveness of a photovoltaic out of power.

• Journal of the Korean Society for Railway
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• v.20 no.2
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• pp.182-189
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• 2017

Photovoltaic power generation systems make up a large part of the low carbon energy trend. The purpose of this study is to utilize PVsyst, a commercial forecasting program, to forecast research on the design stages of photovoltaic power generation for wider applications of this system in railroads and to consider prospective issues for photovoltaic power plants that are currently being operated. Given this, we will compare the forecast value of generated photovoltaic power, derived from foreign weather forecast information provided by NASA, along with information from Meteonorm, and the forecast values derived from the KMA weather information. By comparing these values with amounts actually generated by KPX, this research aims to secure propriety rights for wider application of photovoltaic power generation systems in railroads, and to contribute to low carbon energy for the new climate of the future.