NDLI: Data-driven predictive direct load control of refrigeration systems

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The Journal of Engineering

Data-driven predictive direct load control of refrigeration systems

Content Provider	IET Digital Library
Author	Shafiei, Seyed Ehsan Knudsen, Torben Wisniewski, Rafael Andersen, Palle
Abstract	A predictive control using subspace identification is applied for the smart grid integration of refrigeration systems under a direct load control scheme. A realistic demand response scenario based on regulation of the electrical power consumption is considered. A receding horizon optimal control is proposed to fulfil two important objectives: to secure high coefficient of performance and to participate in power consumption management. Moreover, a new method for design of input signals for system identification is put forward. The control method is fully data driven without an explicit use of model in the control implementation. As an important practical consideration, the control design relies on a cheap solution with available measurements than using the expensive mass flow meters. The results show successful implementation of the method on a large-scale non-linear simulation tool which is validated against real data. The performance improvement results in a 22% reduction in the energy consumption. A comparative simulation is accomplished showing the superiority of the method over the existing approaches in terms of the load following performance.
Starting Page	1022
Ending Page	1033
Page Count	12
ISSN	17518644
Volume Number	9
e-ISSN	17518652
Issue Number	Issue 7, Apr (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/9/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2014.0666
Journal	IET Control Theory & Applications
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Control Design Control of Electric Power System Control of Heat System Control System Analysis Control System Synthesis Data-driven Predictive Direct Load Control Demand Response Electrical Power Consumption Regulation Energy Consumption Input Signal Large-scale Nonlinear Simulation Tool Load Following Performance Load Regulation Nonlinear Control System Optimal Control Power Consumption Power Consumption Management Power System Control Predictive Control Receding Horizon Optimal Control Refrigeration Refrigeration And Cold Storage Refrigeration And Cooling (energy Utilisation) Refrigeration System Smart Grid Integration Smart Power Grid SubSpace Identification Synthesis Method System Identification
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications

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