Journal article
Challenges of implementing economic model predictive control strategy for buildings interacting with smart energy systems
Risø National Laboratory for Sustainable Energy, Technical University of Denmark1
Department of Electrical Engineering, Technical University of Denmark2
Center for Electric Power and Energy, Centers, Technical University of Denmark3
Distributed Energy Resources, Center for Electric Power and Energy, Centers, Technical University of Denmark4
Berlin Energy Agency5
Technical University of Lisbon6
Energy System Management, Center for Electric Power and Energy, Centers, Technical University of Denmark7
When there is a high penetration of renewables in the energy system, it requires proactive control of large numbers of distributed demand response resources to maintain the system’s reliability and improve its operational economics. This paper presents the Economic Model Predictive Control (EMPC) strategy for energy management in smart buildings, which can act as active users interacting with smart energy systems.
The challenges encountered during the implementation of EMPC for active demand side management are investigated in detail in this paper. A pilot testing study shows energy savings and load shifting can be achieved by applying EMPC with weather forecast and dynamic power price signals
| Language: | English |
|---|---|
| Year: | 2016 |
| Pages: | 1476-1486 |
| ISSN: | 18735606 and 13594311 |
| Types: | Journal article |
| DOI: | 10.1016/j.applthermaleng.2016.11.141 |
| ORCIDs: | Zong, Yi , You, Shi , Hu, Junjie and Han, Xue |
