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A Demand Response Implementation in Tertiary Buildings Through Model Predictive Control

delete2019-11-01
delete24
PRE
AI
S
Sérgio Bruno *
G
Giovanni Giannoccaro
M
Massimo La Scala
DOI:10.1109/TIA.2019.2932963delete
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摘要

摘要

En 中文
In this article, a cloud-based architecture developed for the control of dispatchable resources of active users is proposed. This architecture assumes the availability of renewables, dispatchable loads, and storage resources in a demand response framework. The integration of a metering infrastructure with the cloud is a relevant aspect. The proposed methodology is based on model predictive control (MPC) and is solved by mixed-integer linear programming to take into account nonlinearities and discontinuities introduced by cost functions and storage systems. The control strategy was actually implemented on a pilot installation in a public school, requiring retrofit interventions, with particular regard to energy monitoring and cloud communication. An experimental gateway prototype was installed allowing communication between field and cloud control tiers. Experimental results are conducted to assess economic gains deriving by employing MPC when compared to rule-based ordinary controllers. Computational timings and communication latencies confirm the feasibility of the approach.
Keyword:
Cloud computing
demand response (DR)
energy router (ER)
mixed-integer linear programming (MILP)
model predictive control (MPC)
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期刊

IEEE Transactions on Industry Applications 封面图
IEEE Transactions on Industry Applications
IF:
4.5
论文数:
1.1W
被引数:
3.5W

机构

P
Politecnico di Bari
学者数:
4.0K
论文数: 4.0K
被引数: 6
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引用论文

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