Semantic Scholar Open Access 2020 136 sitasi

Data-driven methods for building control — A review and promising future directions

E. Maddalena Yingzhao Lian C. Jones

Lihat Sumber DOI

Abstrak

Abstract A review of the heating, ventilation and air-conditioning control problem for buildings is presented with particular emphasis on its distinguishing features. Next, we not only examine how data-driven algorithms have been exploited to tackle the main challenges present in this area, but also point to promising future investigations both from theoretical and from practical viewpoints. Rule based control, reinforcement learning, model predictive control (MPC), and learning MPC techniques are compared on the basis of four attributes that we expect an ideal solution to possess. Finally, on-line learning MPC with guarantees is recognized as an approach with high potential that needs to be further investigated by researchers. Such a solution is likely to be accepted by practitioners since it meets the industry expectations of reduced deployment time and costs.

Topik & Kata Kunci

Computer Science

Penulis (3)

E. Maddalena

Yingzhao Lian

C. Jones

Format Sitasi

APA MLA BibTeX

Maddalena, E., Lian, Y., Jones, C. (2020). Data-driven methods for building control — A review and promising future directions. https://doi.org/10.1016/j.conengprac.2019.104211

Akses Cepat

Lihat di Sumber doi.org/10.1016/j.conengprac.2019.104211

Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Total Sitasi: 136×
Sumber Database: Semantic Scholar
DOI: 10.1016/j.conengprac.2019.104211
Akses: Open Access ✓