지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2023.10
- 수록면
- 43 - 59 (17page)
이용수
초록· 키워드
오류제보하기
Prediction of solar irradiance that influences the building load and production of new and renewable energy is crucial in the predictive control of buildings. However, most solar irradiance prediction models are developed using weather data measured over a long term in the target region. This study proposed a solar irradiance prediction model based on a hybrid layer that combined a long short-term memory layer and a bi-directional long short-term memory layer. Next, the solar irradiance of the following day was predicted using only the hourly irradiance measured on site one day before the prediction day using a model trained with the weather data of another region. The proposed solar irradiance prediction model showed an RMSE of 69.5 W/m2, a level suitable for the predictive control of buildings. Moreover, although training data from a different region was used, the performance of the proposed model was similar to that of a model trained with long-term data measured in the target region.
목차
Abstract
1. 서론
2. LSTM networks
3. Hybrid LSTM model for predicting solar irradiance
4. 결과
5. 결론
REFERENCES
참고문헌 (43)
참고문헌 신청
Ferreira, P. M., Ruano, A. E., Silva, S., and Conceicao, E. Z. E., Neural Networks Based Predictive Control for Thermal Comfort and Energy Savings in Public Buildings, Energy and Buildings, Vol. 55, pp. 238-251, 2012.
Huang, H., Chen, L., and Hu, E., A New Model Predictive Control Scheme for Energy and Cost Savings in Commercial Buildings: An Airport Terminal Building Case Study, Building and Environment, Vol. 89, pp. 203-216, 2015.
Kusiak, A., Li, M., and Tang, F., Modeling and Optimization of HVAC Energy Consumption, Applied Energy, Vol. 87, No. 10, pp. 3092-3102, 2010.
Nagpal, H., Avramidis, I. I., Capitanescu, F., and Heiselberg, P., Optimal Energy Management in Smart Sustainable Buildings–A Chance-constrained Model Predictive Control Approach, Energy and Buildings, Vol. 248, 111163, 2021.
Nguyen, T. T., Yoo, H. J., and Kim, H. M., Analyzing the Impacts of System Parameters on MPC-Based Frequency Control for a Stand-Alone Microgrid, Energies, Vol. 10, No. 4, 417, 2017.
Huang, H., Chen, L., and Hu, E., A New Model Predictive Control Scheme for Energy and Cost Savings in Commercial Buildings: An Airport Terminal Building Case Study, Building and Environment, Vol. 89, pp. 203-216, 2015.
Kusiak, A., Li, M., and Tang, F., Modeling and Optimization of HVAC Energy Consumption, Applied Energy, Vol. 87, No. 10, pp. 3092-3102, 2010.
Nagpal, H., Avramidis, I. I., Capitanescu, F., and Heiselberg, P., Optimal Energy Management in Smart Sustainable Buildings–A Chance-constrained Model Predictive Control Approach, Energy and Buildings, Vol. 248, 111163, 2021.
Nguyen, T. T., Yoo, H. J., and Kim, H. M., Analyzing the Impacts of System Parameters on MPC-Based Frequency Control for a Stand-Alone Microgrid, Energies, Vol. 10, No. 4, 417, 2017.
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