Semantic Scholar Open Access 2019 72 sitasi

A simplified HVAC energy prediction method based on degree-day

Huajing Sha Peng Xu Chong Hu Zhiling Li Yongbao Chen +1 lainnya

Abstrak

Abstract A building heating, ventilation, and air-conditioning (HVAC) system consumes large amounts of energy. Energy consumption prediction is an effective strategy for operation optimization and energy management in a building. The energy consumption of an HVAC system in a building is influenced by many factors, such as weather conditions, building usage, and thermal performance. However, it is impractical to consider all factors for predicting energy consumption. In this paper, a simplified data-driven model is proposed for predicting the energy consumption of an HVAC system in a building. A novel feature transformation method is introduced to select the most relevant features. Three input features (i.e., degree-day, day type, and month type) are finally adopted in this model. Compared to models developed in previous studies, this simplified model largely reduces the computation time and is easier to operate. The cross-validated root mean square error of this method for cooling energy prediction is less than 20%, indicating its suitability for use in engineering applications.

Topik & Kata Kunci

Computer Science

Penulis (6)

Huajing Sha

Peng Xu

Chong Hu

Zhiling Li

Yongbao Chen

Zhe Chen

Format Sitasi

APA MLA BibTeX

Sha, H., Xu, P., Hu, C., Li, Z., Chen, Y., Chen, Z. (2019). A simplified HVAC energy prediction method based on degree-day. https://doi.org/10.1016/J.SCS.2019.101698

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Informasi Jurnal

Tahun Terbit: 2019
Bahasa: en
Total Sitasi: 72×
Sumber Database: Semantic Scholar
DOI: 10.1016/J.SCS.2019.101698
Akses: Open Access ✓