• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.478-484
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• 2018

This study predicts solar radiation, solar radiation, and solar power generation using hourly weather data such as temperature, precipitation, wind direction, wind speed, humidity, cloudiness, sunshine and solar radiation. I/O pattern in supervised learning is the most important factor in prediction, but it must be determined by repeated experiments because humans have to decide. This study proposed four input and output patterns for solar and sunrise prediction. In addition, we predicted solar power generation using the predicted solar and solar radiation data and power generation data of Youngam solar power plant in Jeollanamdo. As a experiment result, the model 4 showed the best prediction results in the sunshine and solar radiation prediction, and the RMSE of sunshine was 1.5 times and the sunshine RMSE was 3 times less than that of model 1. As a experiment result of solar power generation prediction, the best prediction result was obtained for model 4 as well as sunshine and solar radiation, and the RMSE was reduced by 2.7 times less than that of model 1.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.4
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• pp.568-573
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• 2009

Because of environmental crisis, researchers are seeking and developing a new, clean, safe and renewable energy. Solar cell energy and fuel cell energy have inestimable development potential. The paper introduces hybrid photovoltaic-fuel cell generation systems supplying a remote power load and hybrid system of solar cell and fuel cell considering the advantages of stable and sustainable energy from the economic point of view. Fuel cell power system has been proven a viable technology to back up severe PV power fluctuations under inclement weather conditions. Fuel cell power generation, containing small land us, is able to alleviate the heavy burden for large surface requirement of PV power plants. In addition, the PV-fuel cell hybrid power system shows a very little potential for lifetime $CO_2$ emissions. In this paper shows the I-V characteristics of the solar module which are dependent on the power of the halogen lamp and the I-V characteristics of fuel cells which are connected in parallel. Also, it shows efficiency of the hybrid system.

• Advances in Energy Research
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• v.3 no.1
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• pp.59-70
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• 2015

In India, continuous production of electricity and sweet/potable water from Solar power and desalination plant plays a major role in the industries. Particularly in Copper industry, Solar power adopts Solar field collector combined with thermal storage system and steam Boiler, Turbine & Generator (BTG) for electricity production and desalination plant adopts Reverse osmosis (RO) for sweet/potable water production which cannot be used for long hours of power generation and consistency of energy supply for industrial processes and power generation cannot be ensured. This paper presents an overview of enhanced technology for Solar power and Desalination plant for Copper industry making it continuous production of electricity and sweet/potable water. The conventional technology can be replaced with this proposed technique in the existing and upcoming industries.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.10
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• pp.95-100
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• 2014

To solve the problem of conventional fossil energy, utilization of renewable energy is growing rapidly. Solar energy as an energy source is infinite, and a variety of research is being conducted into its utilization. To change solar energy into electrical energy, we need to build a solar power plant. The efficiency of such a plant is strongly influenced by meteorological factors; that is, its efficiency is determined by solar radiation. However, when analyzing observed generation data, it is clear that the generated amount is changed by various factors such as weather, location and plant efficiency. In this paper, we proposed a solar power generation prediction algorithm using geographical factors such as latitude and elevation. Hence, changes in generated amount caused by the installation environment are calculated by curve fitting. Through applying the method to calculate this generation amount, the difference between real generated amount is analyzed.

• KIEAE Journal
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• v.17 no.1
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• pp.77-82
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• 2017

In power supply systems for urban areas, issues such as a progressive tax have escalated recently. In this regard, photovoltaic power generation, which is appraised as an alternative power generation system, is drawing attention increasingly for its high stability and applicability to existing infrastructure. This study assessed the realistic feasibility of photovoltaic power generation and also analyzed the economic benefits expected when it is linked with green roof, which is likely to promote ecological functions in urban areas, based on the Seoul solar map, RPS, and actual monitoring data. The economics analysis of 30kW photovoltaic power generation applied with the monthly average horizontal solar radiation of six grades in the Seoul solar map showed that positive NPV was up to grade 4, while grade 5 or poorer showed negative NPV and indicated that it is difficult to assure appropriate feasibility. Compared with non-afforestation, when green roof was applied, monthly average power improvement efficiency was 7.2% at highest and 3.7% at lowest based on yearly actual monitoring data. The annual average was 5.3%, and the efficiency was high relatively in summer, including September and November. As for the economic benefits expected when 30kw photovoltaic power generation is combined with green roof based on the average horizontal solar radiation of grade 1 in the Seoul solar map, SP has improved 0.2 years to 7.4 years, and EP has improved 0.5 years to 8.3 years.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.546-548
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• 2019

Due to environmental problems, fossil fuel and nuclear power generation are declining and solar power generation is increasing. DC are of a solar power plant is accidents caused by accidents, causing damage to property and people. This study prevents DC are accidents of solar power modules. It is expected that the IoT will be used to quickly alert the manager and greatly contribute to fire prevention.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.5
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• pp.683-689
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• 2012

Photovoltaic(PV) system is one of power generation systems. Solar light in PV system is like the fuel of the car. The quantity of electricity generation, therefore, is fully dependent on the available quantity of solar light on the system of each site. If a utility can predict the solar power generation on a planned site, it may be possible to set up an appropriate PV system there. It may be also possible to objectively evaluate the performances of existing solar systems. Based on the theories of astronomy and meteorology, in this paper, Perez model is simulated to estimate the available quantity of solar lights on the prevailed photovoltaic systems. Consequently the conditions for optimal power generation of each PV system can be analyzed. And the maximum quantity of power generation of each system can be also estimated by applying assumed efficiency of PV system. Perez model is simulated in this paper, and the result is compared with the data of the same model of Meteonorm. Simulated site is Daejeon, Korea with typical meteorological year(TMY) data of 1991~2010.

• Journal of the Korean Society of Industry Convergence
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• v.13 no.2
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• pp.69-75
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• 2010

This paper describes the design and implementation of hybrid sun tracking solar power generation system designed by combining astronomical data with optical tracking mechanism. The advantages of proposed power generation system are small amounts of calculation for tracking operations and enhancement of 40% of power generation at best. This system is able to track toward optimal position for maximum sun-lights under scattered lights due to clouds. The performance of implemented power generation system is confirmed by field experiments.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.859-866
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• 2021

Agricultural Photovoltaic power generation is a new model that installs solar power generation facilities on top of farmland. Through this, it is possible to increase farm household income by producing crops and electricity at the same time. Recently, various attempts have been made to utilize agricultural solar power generation. Agricultural photovoltaic power generation has a disadvantage in that maintenance is relatively difficult because it is installed on a relatively high structure unlike conventional photovoltaic power generation. To solve these problems, intelligent and efficient operation and diagnostic functions are required. In this paper, we discuss the design and implementation of a prediction and diagnosis system to collect and store the power output of agricultural solar power generation facilities and implement an intelligent prediction model. The proposed system predicts the amount of power generation based on the amount of solar power generation and environmental sensor data, determines whether there is an abnormality in the facility, calculates the aging degree of the facility and provides it to the user.

• Journal of the Korean Solar Energy Society
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• v.38 no.1
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• pp.37-44
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• 2018

Solar panels are modules made up of many cells, like the N-type monosilicon, P-type monosilicon, P-type multisilicon, amorphous thin-film silicon, and CIGS solar cells. An efficient photovoltaic (PV) power is important to use to determine what kind of cell types are used because residential solar systems receive attention. In this study, we used 3-type solar panels - such as N-type monosilicon, P-type monosilicon, and CIGS solar cells - to investigate what kind of solar panel on a house or building performs the best. PV systems were composed of 3-type solar panels on the roof with each ~1.8 kW nominal power. N-type monosilicon solar panel resulted in the best power generation when monitored. Capacity Utilization Factor (CUF) and Performance Ratio (PR) of the N-type Si solar panel were 14.6% and 75% respectively. In comparison, N-type monosilicon and CIGS solar panels showed higher performance in power generation than P-type monosilicon solar power with increasing solar irradiance.