태양광발전 단기예측모델 개발
The Development of the Short-Term Predict Model for Solar Power Generation
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초록
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.
Abstract
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.
참고문헌 (5)
- Study on the Application of Next-Generation Satellite Data(III), "Kim, Yun Jai", KMA, ~ (2007)
- Chang Gu Kang, "Compare Analysis for Time Series Forecasting Methods", Quarterly National Account, 3(26), pp.80~105 (2006)
- 이성덕, "공간시계열 모형의 칼만필터 추정과 예측", Communications for Statistical Applications and Methods, 18(1), pp.79~87 (2011), 한국통계학회
- 이성덕, "공간시계열 자료에 대한 STARMA 모형과 STBL 모형의 예측력 비교", 응용통계연구, 20(1), pp.91~102 (2007), 한국통계학회