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 (MILP) to take into account non-linearities 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 (ER Gateway) 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 confirms the feasibility of the approach.

A Demand Response Implementation in Tertiary Buildings through Model Predictive Control / Bruno, Sergio; Giannoccaro, Giovanni; La Scala, Massimo. - In: IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS. - ISSN 0093-9994. - 55:6(2019), pp. 7052-7061. [10.1109/TIA.2019.2932963]

A Demand Response Implementation in Tertiary Buildings through Model Predictive Control

Giannoccaro, Giovanni;La Scala, Massimo
2019

Abstract

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 (MILP) to take into account non-linearities 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 (ER Gateway) 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 confirms the feasibility of the approach.
2019
A Demand Response Implementation in Tertiary Buildings through Model Predictive Control / Bruno, Sergio; Giannoccaro, Giovanni; La Scala, Massimo. - In: IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS. - ISSN 0093-9994. - 55:6(2019), pp. 7052-7061. [10.1109/TIA.2019.2932963]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/951014
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