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http://dx.doi.org/10.14400/JDC.2014.12.3.243

Analysis of prediction model for solar power generation  

Song, Jae-Ju (한전 전력연구원)
Jeong, Yoon-Su (목원대학교 정보통신공학과)
Lee, Sang-Ho (충북대학교 전자정보대학 소프트웨어학과)
Publication Information
Journal of Digital Convergence / v.12, no.3, 2014 , pp. 243-248 More about this Journal
Abstract
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.
Keywords
Solar energy; estimating information system;
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