• Journal of Korea Multimedia Society
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• v.25 no.11
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• pp.1572-1581
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• 2022

Energy conversion to renewable energy is being promoted to solve the recently serious environmental pollution problem. Solar energy is one of the promising natural renewable energy sources. Compared to other energy sources, it is receiving great attention because it has less ecological impact and is sustainable. It is important to predict power generation at a future time in order to maximize the output of solar energy and ensure the stability and variability of power. In this paper, solar power generation data and sensor data were used. Using the PCC(Pearson Correlation Coefficient) analysis method, factors with a large correlation with power generation were derived and applied to the GAM(Generalized Additive Model). And the prediction accuracy of the power generation prediction model was judged. It aims to derive efficient solar power generation in the future and improve power generation performance.

• Journal of the Korean Solar Energy Society
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• v.39 no.3
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• pp.59-66
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• 2019

New and renewable energy forecasts are key technology to reduce the annual operating cost of new and renewable facilities, and accuracy of forecasts is paramount. In this study, we intend to build a model for the prediction of short-term solar power generation for 1 hour to 3 hours. To this end, this study applied two time series technique, ARIMA model without considering seasonality and SARIMA model with considering seasonality, comparing which technique has better predictive accuracy. Comparing predicted errors by MAE measures of solar power generation for 1 hour to 3 hours at four locations, the solar power forecast model using ARIMA was better in terms of predictive accuracy than the solar power forecast model using SARIMA. On the other hand, a comparison of predicted error by RMSE measures resulted in a solar power forecast model using SARIMA being better in terms of predictive accuracy than a solar power forecast model using ARIMA.

• Journal of Internet of Things and Convergence
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• v.8 no.3
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• pp.55-61
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• 2022

In order to reduce greenhouse gases, the main culprit of global warming, the United Nations signed the Climate Change Convention in 1992. Korea is also pursuing a policy to expand the supply of renewable energy to reduce greenhouse gas emissions. The expansion of renewable energy development using solar power led to the expansion of wind power and solar power generation. The expansion of renewable energy development, which is greatly affected by weather conditions, is creating difficulties in managing the supply and demand of the power system. To solve this problem, the power brokerage market was introduced. Therefore, in order to participate in the power brokerage market, it is necessary to predict the amount of power generation. In this paper, the prediction system was used to analyze the Yonchuk solar power plant. As a result of applying solar insolation from on-site (Model 1) and the Korea Meteorological Administration (Model 2), it was confirmed that accuracy of Model 2 was 3% higher. As a result of comparative analysis of the DNN and RNN models, it was confirmed that the prediction accuracy of the DNN model improved by 1.72%.

• Journal of the Korean Solar Energy Society
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• v.33 no.6
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• pp.62-69
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• 2013

In this paper, Korea Institute of Energy Research, building integrated renewable energy monitoring system that utilizes solar power generation forecast data forecast model is proposed. Renewable energy integration of real-time monitoring system based on monitoring data were building a database and the database of the weather conditions and to study the correlation structure was tailoring. The weather forecast cloud cover data, generation data, and solar radiation data, a data mining and time series analysis using the method developed models to forecast solar power. The development of solar power in order to forecast model of weather forecast data it is important to secure. To this end, in three hours, including a three-day forecast today Meteorological data were used from the KMA(korea Meteorological Administration) site offers. In order to verify the accuracy of the predicted solar circle for each prediction and the actual environment can be applied to generation and were analyzed.

• Advances in Energy Research
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• v.5 no.2
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• pp.179-205
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• 2017

This research presents an in-depth analysis of location planning of the solar-hydrogen power plants for electricity production in different cities situated in Kerman province of Iran. Ten cities were analyzed in order to select the most suitable location for the construction of a solar-hydrogen power plant utilizing photovoltaic panels. Data envelopment analysis (DEA) methodology was applied to prioritize cities for installing the solar-hydrogen power plant so that one candidate location was selected for each city. Different criteria including population, distance to main road, flood risk, wind speed, sunshine hours, air temperature, humidity, horizontal solar irradiation, dust, and land costare used for the analysis. From the analysis, it is found that among the candidates' cities, the site of Lalezar is ranked as the first priority for the solar-hydrogen system development. A measure of validity is obtained when results of the DEA method are compared with the results of the technique for ordering preference by similarity to ideal solution (TOPSIS). Applying TOPSIS model, it was found that city of Lalezar ranked first, and Rafsanjan gained last priority for installing the solar-hydrogen power plants. Cities of Baft, Sirjan, Kerman, Shahrbabak, Kahnouj, Shahdad, Bam, and Jiroft ranked second to ninth, respectively. The validity of the DEA model is compared with the results of TOPSIS and it is demonstrated that the two methods produced similar results. The solar-hydrogen power plant is considered for installation in the city of Lalezar. It is demonstrated that installation of the proposed solar-hydrogen system in Lalezar can lead to yearly yield of 129 ton-H2 which covers 4.3% of total annual energy demands of the city.

• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.113-116
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• 2004

Output power of a photovoltaic system changes continuously as it strongly depends on the weather condition(isolation and temperature). Therefore, it is necessary the theoretical model realizes the electrical output characteristics of solar cell. Of several theoretical models for real solar cell, both parametric model and interpolation model are used widely. In this paper, we have propose a improved model of solar cell using its output characteristics that can be extended to calculate the rear solar cell characteristics at various temperatures and insolation. And more, the theoretical research of several models of solar cell using simulation analysis.

• Journal of the Korean Solar Energy Society
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• v.39 no.3
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• pp.81-89
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• 2019

Long-term solar irradiance data are required for reliable performance evaluation and feasibility analysis of solar photovoltaic systems. However, measurement data of the global horizontal irradiance (GHI) are only available for major cities in Korea. Neither the direct normal irradiance (DNI) nor the diffuse horizontal irradiance (DHI) are available, which are also needed to calculate the irradiance on the tilted surface of PV array. It is a simple approach to take advantage of the decomposition model that extracts DNI and DHI from GHI. In this study, we investigate variations of solar PV power estimation due to the choice of decomposition model. The GHI data from Korea Meteorological Administration (KMA) were used and different sets of typical meteorological year (TMY) data using some well-known decomposition models were generated. Then, power outputs with the different TMY data were calculated, and a variation of 3.7% was estimated due to the choice of decomposition model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.593-600
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• 2016

The solar array regulator for low earth orbit satellites controls a operating point of solar array for suppling electric power to the battery and the other units. Because the control object is reversed, the new approach for large and small signal analysis is needed despite using buck-converter for power stage. In this paper, the steady state analysis of solar array regulator is performed in continuous conduction mode and discontinuous conduction mode, and the border condition for each mode is established. Also, the small signal model of solar array regulator is established in discontinuous conduction mode. Experiments are carried on in worst condition which the solar array regulator can face with discontinuous conduction mode. The results show that the solar array regulator is in stable.

• Journal of The Korean Astronomical Society
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• v.54 no.1
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• pp.9-16
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• 2021

The Ozone Dynamics Investigation Nano-Satellite (ODIN) is a CubeSat design proposed by Chungnam National University as contribution to the CubeSat Competition 2019 sponsored by the Korean Aerospace Research Institute (KARI). The main objectives of ODIN are (1) to observe the polar ozone column density (latitude range of 60° to 80° in both hemispheres) and (2) to investigate the chemical dynamics between stratospheric ozone and ozone depleting substances (ODSs) through spectroscopy of the terrestrial atmosphere. For the operation of ODIN, a highly efficient power system designed for the specific orbit is required. We present the conceptual structural design of ODIN and an analysis of power generation in a sun synchronous orbit (SSO) using two different configurations of 3U solar panels (a deployed model and a non-deployed model). The deployed solar panel model generates 189.7 W through one day which consists of 14 orbit cycles, while the non-deployed solar panel model generates 152.6 W. Both models generate enough power for ODIN and the calculation suggests that the deployed solar panel model can generate slightly more power than the non-deployed solar panel model in a single orbit cycle. We eventually selected the non-deployed solar panel model for our design because of its robustness against vibration during the launch sequence and the capability of stable power generation through a whole day cycle.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.243-248
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• 2014

Recently, solar energy is expanding to combination of computing in real time by tracking the position of the sun to estimate the angle of inclination and make up freshly correcting a part of the solar radiation. Solar power is need that reliably linked technology to power generation system renewable energy in order to efficient power production that is difficult to output predict based on the position of the sun rise. In this paper, we analysis of prediction model for solar power generation to estimate the predictive value of solar power generation in the development of real-time weather data. Photovoltaic power generation input the correction factor such as temperature, module characteristics by the solar generator module and the location of the local angle of inclination to analyze the predictive power generation algorithm for the prediction calculation to predict the final generation. In addition, the proposed model in real-time national weather service forecast for medium-term and real-time observations used as input data to perform the short-term prediction models.