Abstract
Optimization of the electricity consumption of chiller systems can save more energy for modern factories. However, under the traditional manually operated control mode, chiller systems often waste additional electricity due to time delay. For this issue, a strategy was proposed to reduce the electricity consumption of chiller systems. This strategy uses state-of-the-art time series prediction models to predict cooling demand, aiming to minimize the negative effects of time delay in the system. Finally, the strategy was applied in a real factory environment and compared with the manual control mode. The comparative results demonstrated the effectiveness of this method.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 43rd Chinese Control Conference, CCC 2024 |
| Editors | Jing Na, Jian Sun |
| Publisher | IEEE Computer Society |
| Pages | 1760-1764 |
| Number of pages | 5 |
| ISBN (Electronic) | 9789887581581 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 43rd Chinese Control Conference, CCC 2024 - Kunming, China Duration: 28 Jul 2024 → 31 Jul 2024 |
Publication series
| Name | Chinese Control Conference, CCC |
|---|---|
| ISSN (Print) | 1934-1768 |
| ISSN (Electronic) | 2161-2927 |
Conference
| Conference | 43rd Chinese Control Conference, CCC 2024 |
|---|---|
| Country/Territory | China |
| City | Kunming |
| Period | 28/07/24 → 31/07/24 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- chiller systems
- time delay
- time series prediction
Fingerprint
Dive into the research topics of 'Optimization in Chiller System: A Strategy to Solving Time Delay Based on Cooling Demand Prediction'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver