• Title/Summary/Keyword: solar radiation prediction

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지도학습에서 다양한 입력 모델에 의한 초단기 태양광 발전 예측 (Forecasting of Short Term Photovoltaic Generation by Various Input Model in Supervised Learning)

  • 장진혁;신동하;김창복
    • 한국항행학회논문지
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    • 제22권5호
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    • pp.478-484
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    • 2018
  • 본 연구는 기온, 강수량, 풍향, 풍속, 습도, 운량, 일조, 일사 등 시간별 기상 데이터를 이용하여, 일사 및 일조 그리고 태양광 발전예측을 하였다. 지도학습에서 입출력패턴은 예측에서 가장 중요한 요소이지만 인간이 직접 결정해야하기 때문에, 반복적인 실험에 의해 결정해야 한다. 본 연구는 일사 및 일조 예측을 위하여 4가지 모델의 입출력 패턴을 제안하였다. 또한, 예측된 일조 및 일사 데이터와 전라남도 영암 태양광 발전소의 발전량 데이터를 사용하여 태양광 발전량을 예측하였다. 실험결과 일조 및 일사 예측에서 모델 4가 가장 예측결과가 우수했으며, 모델 1에 비해 일조의 RMSE는 1.5배 정도 그리고 일사의 RMSE는 3배 정도 오차가 줄었다. 태양광 발전예측 실험결과 일조 및 일사와 마찬가지로 모델 4가 가장 예측결과가 좋았으며, 모델 1 보다 RMSE가 2.7배 정도 오차가 줄었다.

제주 실시간 일사량의 기계학습 예측 기법 연구 (A Study on Prediction Techniques through Machine Learning of Real-time Solar Radiation in Jeju)

  • 이영미;배주현;박정근
    • 한국환경과학회지
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    • 제26권4호
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    • pp.521-527
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    • 2017
  • Solar radiation forecasts are important for predicting the amount of ice on road and the potential solar energy. In an attempt to improve solar radiation predictability in Jeju, we conducted machine learning with various data mining techniques such as tree models, conditional inference tree, random forest, support vector machines and logistic regression. To validate machine learning models, the results from the simulation was compared with the solar radiation data observed over Jeju observation site. According to the model assesment, it can be seen that the solar radiation prediction using random forest is the most effective method. The error rate proposed by random forest data mining is 17%.

Solar radiation forecasting using boosting decision tree and recurrent neural networks

  • Hyojeoung, Kim;Sujin, Park;Sahm, Kim
    • Communications for Statistical Applications and Methods
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    • 제29권6호
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    • pp.709-719
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    • 2022
  • Recently, as the importance of environmental protection has emerged, interest in new and renewable energy is also increasing worldwide. In particular, the solar energy sector accounts for the highest production rate among new and renewable energy in Korea due to its infinite resources, easy installation and maintenance, and eco-friendly characteristics such as low noise emission levels and less pollutants during power generation. However, although climate prediction is essential since solar power is affected by weather and climate change, solar radiation, which is closely related to solar power, is not currently forecasted by the Korea Meteorological Administration. Solar radiation prediction can be the basis for establishing a reasonable new and renewable energy operation plan, and it is very important because it can be used not only in solar power but also in other fields such as power consumption prediction. Therefore, this study was conducted for the purpose of improving the accuracy of solar radiation. Solar radiation was predicted by a total of three weather variables, temperature, humidity, and cloudiness, and solar radiation outside the atmosphere, and the results were compared using various models. The CatBoost model was best obtained by fitting and comparing the Boosting series (XGB, CatBoost) and RNN series (Simple RNN, LSTM, GRU) models. In addition, the results were further improved through Time series cross-validation.

9 kW 출력용 태양열 스털링엔진 발전시스템의 설계와 성능예측 (Design and Performance Prediction of Power System in a Solar Stirling Engine for 9 kW Output)

  • 배명환;강상율
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2003년도 춘계학술대회
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    • pp.2198-2204
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    • 2003
  • In order to make a match of the insufficient direct solar radiation, in this study, the target output is lowered to 9 kW smaller than 25 kW in former studies. It is also necessary to match the collector/receiver with engine/generator systems to accomplish the power level of a system. The simulation analyses of a dish solar power system with stirling engine are totally carried out to predict the system performance with the designed values. In addition, an influence of direct solar radiation on system performance and operation control is discussed in simulation. It is found that the diameter of concentrator could be made small to 8 m regardless of slope errors with 2.5 and 5.0 mrad radiation, and the operation range of mean pressure control. is wide even if the direct solar radiation is a quit low.

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혼돈이론을 이용한 일적산 일사량의 예측 (Prediction of Daily Solar Irradiation Based on Chaos Theory)

  • 조성인;배영민;윤진일;박은우;황헌
    • Journal of Biosystems Engineering
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    • 제25권2호
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    • pp.123-130
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    • 2000
  • A forcasting scheme for daily solar irradiance on agricultural field sis proposed by application of chaos theory to a long term observation data. It was conducted by reconstruction of phase space, attractor analysis, and Lyapunov analysis. Using the methodology , it was determined whether evolution of the five climatic data such as daily air temperature , water temperature , relative humidity, solar radiation, and wind speed are chaotic or not. The climatic data were collected for three years by an automated weather station at Hwasung-gun, Kyonggi-province. The results showed that the evolution of solar radiation was chaotic , and could be predicted. The prediction of the evolution of the solar radiation data was executed by using ' local optimal linear reconstruction ' algorithm . The RMS value of the predicting for the solar radiation evolution was 4.32 MJ/$m^2$ day. Therefore, it was feasible to predict the daily solar radiation based on the chaos theory.

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건물의 일사에너지 예측을 위한 경사면 일사량 측정과 예측모델과의 비교분석 연구 (Comparative Analysis of Measurements and Total Solar Irradiance Models on Inclined Surface for Building Solar Energy Prediction)

  • 윤갑천;전종욱;김강수
    • 한국태양에너지학회 논문집
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    • 제32권6호
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    • pp.44-52
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    • 2012
  • In all building's energy simulation applications, solar radiation must be calculated on inclined surfaces. Various solar radiation models based on measured data of specific region were used in building simulation programs. Therefore, we should choose the appropriate solar radiation model for Seoul. The purpose of this study is to compare four solar radiation models on inclined surfaces that are widely used in building energy simulations. In this case, it can be said the appropriate model in Seoul is the Isotropic model.

기상 예보 데이터와 일사 예측 모델식을 활용한 실시간 에너지 수요예측 (Real-time Energy Demand Prediction Method Using Weather Forecasting Data and Solar Model)

  • 곽영훈;천세환;장철용;허정호
    • 설비공학논문집
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    • 제25권6호
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    • pp.310-316
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    • 2013
  • This study was designed to investigate a method for short-term, real-time energy demand prediction, to cope with changing loads for the effective operation and management of buildings. Through a case study, a novel methodology for real-time energy demand prediction with the use of weather forecasting data was suggested. To perform the input and output operations of weather data, and to calculate solar radiation and EnergyPlus, the BCVTB (Building Control Virtual Test Bed) was designed. Through the BCVTB, energy demand prediction for the next 24 hours was carried out, based on 4 real-time weather data and 2 solar radiation calculations. The weather parameters used in a model equation to calculate solar radiation were sourced from the weather data of the KMA (Korea Meteorological Administration). Depending on the local weather forecast data, the results showed their corresponding predicted values. Thus, this methodology was successfully applicable to anywhere that local weather forecast data is available.

다층 상세 태양복사 모델에 의한 단층 태양복사 모델의 보정 (Correction of One-layer Solar Radiation Model by Multi-layer Line-by-line Solar Radiation Model)

  • 지준범;이원학;조일성;이규태
    • 대기
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    • 제21권2호
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    • pp.151-162
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    • 2011
  • One-layer solar radiation(GWNU; Gangneung-Wonju National University) model is developed in order to resolve the lack of vertical observations and fast calculation with high resolution. GWNU model is based on IQBAL(Iqbal, 1983) and NREL(National Renewable Energy Laboratory) methods and corrected by precise multi-layer LBL(Line-by-line) model. Input data were used 42 atmospheric profiles from Garand et al.(2001) for calculation of global radiation by the Multi-layer and one-layer solar radiation models. GWNU model has error of about -0.10% compared with LBL model while IQBAL and NREL models have errors of about -3.92 and -2.57%, respectively. Global solar radiation was calculated by corrected GWNU solar model with satellites(MODIS, OMI and MTSAT-1R), RDPS model prediction data in Korea peninsula in 2009, and the results were compared to surface solar radiation observed by 22 KMA solar sites. All models have correlation($R^2$) of 0.91 with the observed hourly solar radiation, and root mean square errors of IQBAL, NREL and GWNU models are 69.16, 69.74 and $67.53W/m^2$, respectively.

한반도에서 해상도 변화에 따른 지표면 일사량의 시공간 분포 (Temporal and Spatial Distributions of the Surface Solar Radiation by Spatial Resolutions on Korea Peninsula)

  • 이규태;조일성;지준범;최영진
    • 신재생에너지
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    • 제7권1호
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    • pp.22-28
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    • 2011
  • The surface solar radiations were calculated and analyzed with spatial resolutions (4 km and 1 km) using by GWNU (Gangneung-Wonju National University) solar radiation model. The GWNU solar radiation model is used various data such as aerosol optical thickness, ozone amount, total precipitable water and cloud factor are retrieved from Moderate Resolution Imaging Spectrometer (MODIS), Ozone Monitoring Instrument (OMI), MTSAT-1R satellite data and output of the Regional Data Assimilation Prediction System(RDAPS) model by Korea Meteorological Administration (KMA), respectively. The differences of spatial resolutions were analyzed with input data (especially, cloud factor from MTSAT-1R satellite). And the Maximum solar radiation by GWNU model were found in Andong, Daegu and Jinju regions and these results were corresponded with the MTSAT-1R cloud factor.

표준기상데이터 작성을 위한 국내 기후특성을 고려한 일사량 예측 모델 적합성 평가 (Applicability of the Solar Irradiation Model in Preparation of Typical Weather Data Considering Domestic Climate Conditions)

  • 심지수;송두삼
    • 설비공학논문집
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    • 제28권12호
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    • pp.467-476
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    • 2016
  • As the energy saving issues become one of the important global agenda, the building simulation method is generally used to predict the inside energy usage to establish the power-saving strategies. To foretell an accurate energy usage of a building, proper and typical weather data are needed. For this reason, typical weather data are fundamental in building energy simulations and among the meteorological factors, the solar irradiation is the most important element. Therefore, preparing solar irradiation is a basic factor. However, there are few places where the horizontal solar radiation in domestic weather stations can be measured, so the prediction of the solar radiation is needed to arrive at typical weather data. In this paper, four solar radiation prediction models were analyzed in terms of their applicability for domestic weather conditions. A total of 12 regions were analyzed to compare the differences of solar irradiation between measurements and the prediction results. The applicability of the solar irradiation prediction model for a certain region was determined by the comparisons. The results were that the Zhang and Huang model showed the highest accuracy (Rad 0.87~0.80) in most of the analyzed regions. The Kasten model which utilizes a simple regression equation exhibited the second-highest accuracy. The Angstrom-Prescott model is easily used, also by employing a plain regression equation Lastly, the Winslow model which is known for predicting global horizontal solar irradiation at any climate regions uses a daily integration equation and showed a low accuracy regarding the domestic climate conditions in Korea.