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건물의 단기부하 예측을 위한 기상예측 모델 개발

Development of Weather Forecast Models for a Short-term Building Load Prediction

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참고문헌

키워드

주제분류기타공학

초록

In this work, we propose weather prediction models to estimate hourly outdoor temperatures and solar irradiance in the next day using forecasting information. Hourly weather data predicted by the proposed models are useful for setting system operating strategies for the next day. The outside temperature prediction model considers 3-hourly temperatures forecasted by Korea Meteorological Administration. Hourly data are obtained by a simple interpolation scheme. The solar irradiance prediction is achieved by constructing a dataset with the observed cloudiness and correspondent solar irradiance during the last two weeks and then by matching the forecasted cloud factor for the next day with the solar irradiance values in the dataset. To verify the usefulness of the weather prediction models in predicting a short-term building load, the predicted data are inputted to a TRNSYS building model, and results are compared with a reference case. Results show that the test case can meet the acceptance error level defined by the ASHRAE guideline showing 8.8% in CVRMSE in spite of some inaccurate predictions for hourly weather data.

Abstract

In this work, we propose weather prediction models to estimate hourly outdoor temperatures and solar irradiance in the next day using forecasting information. Hourly weather data predicted by the proposed models are useful for setting system operating strategies for the next day. The outside temperature prediction model considers 3-hourly temperatures forecasted by Korea Meteorological Administration. Hourly data are obtained by a simple interpolation scheme. The solar irradiance prediction is achieved by constructing a dataset with the observed cloudiness and correspondent solar irradiance during the last two weeks and then by matching the forecasted cloud factor for the next day with the solar irradiance values in the dataset. To verify the usefulness of the weather prediction models in predicting a short-term building load, the predicted data are inputted to a TRNSYS building model, and results are compared with a reference case. Results show that the test case can meet the acceptance error level defined by the ASHRAE guideline showing 8.8% in CVRMSE in spite of some inaccurate predictions for hourly weather data.

참고문헌 (12)

  1. IEA, "Building Optimization and Fault Diagnosis Source Book" (1996)
  2. 황진원, "건물 중앙냉방시스템의 에너지절감을 위한 최적운전 방안에 관한 실험적 연구", 한국산학기술학회논문지, 14(9), pp.4610~4615 (2013), 한국산학기술학회[DOI]
  3. Shaheen, N. I., "A simple methodology to predict local temperature and humidity", ASHRAE Transaction, pp.463~469 (1997)
  4. Han, D. Y., "Study on Air Handling Unit Control Algorithms by Using Building Load Prediction", The Society of Air-Conditioning and Refrigerating Engineers of Korea, pp.1451~1456 (2002)
  5. Kawashima, M., "Optimizing System Control With Load Prediction by Neural Networks for an Ice-Storage System", ASHRAE Transactioins (1996)
  6. Han, D. Y., "On-line building load prediction algorithm", Society of Air Conditioning and Refrigerating Engineers, pp.405~410 (1999)
  7. "DOE-2, Building Optimization and Fault Diagnosis Source Book", DOE, ~ (1996)
  8. Kwak, Y. H., "A Case Study for Real-time Energy Demand Prediction Using Virtual Test-Bed", Korean Institute of Architectural Sustainable Environment and Building System 2011 Conference, pp.191~194 (2011)
  9. Joe, D. K., "Estimating Solar Radiation for Arbitrary Areas Using Empirical Forecasting Models", The Korean Solar Energy Society, 20(3), pp.21~30 (2000)
  10. 전병기, "수평면 전일사를 이용한 창 투과 일사량 계산 방법", 설비공학 논문집, 29(4), pp.159~166 (2017), 대한설비공학회[DOI]
  11. "ISO 13790, Energy performance of buidlings - calculation of energy use for space heating and cooling", International Organization for Standardization, ISO, ~ (2008)
  12. ASHRAE, "Measurement Sof energy and demand saving" (2012)

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