Semantic Scholar Open Access 2022 27 sitasi

Demonstration of Intelligent HVAC Load Management With Deep Reinforcement Learning: Real-World Experience of Machine Learning in Demand Control

Yan Du F. Li Kuldeep R. Kurte J. Munk H. Zandi

Lihat Sumber DOI

Abstrak

Buildings account for 40% of total primary energy consumption and 30% of all CO2 emissions worldwide. A large portion of building energy consumption is due to heating, ventilation, and air-conditioning (HVAC) systems. In the summer, for example, more than 50% of a building’s electricity consumption is used for cooling. With proper energy management, buildings can provide load shifting, peak shaving, frequency regulation, and many other demand response services.

Penulis (5)

Yan Du

F. Li

Kuldeep R. Kurte

J. Munk

H. Zandi

Format Sitasi

APA MLA BibTeX

Du, Y., Li, F., Kurte, K.R., Munk, J., Zandi, H. (2022). Demonstration of Intelligent HVAC Load Management With Deep Reinforcement Learning: Real-World Experience of Machine Learning in Demand Control. https://doi.org/10.1109/MPE.2022.3150825

Akses Cepat

Lihat di Sumber doi.org/10.1109/MPE.2022.3150825

Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Total Sitasi: 27×
Sumber Database: Semantic Scholar
DOI: 10.1109/MPE.2022.3150825
Akses: Open Access ✓