Demand-response in building heating systems: A Model Predictive Control approach

Gianni Bianchini, Marco Casini, Antonio Vicino and Donato Zarrilli

Applied Energy, 2016, vol. 168, issue C, 159-170

Abstract: In this paper we consider the problem of optimizing the operation of a building heating system under the hypothesis that the building is included as an active consumer in a demand response program. Demand response requests to the building operational system come from an external market player or a grid operator. Requests assume the form of price–volume signals specifying a maximum volume of energy to be consumed during a given time slot and a monetary reward assigned to the participant in case it fulfills the conditions. A receding horizon control approach is adopted for the minimization of the energy bill, by exploiting a simplified model of the building. Since the resulting optimization problem is a mixed integer linear program which turns out to be manageable only for buildings with very few zones, a heuristics is devised to make the algorithm applicable to realistic size problems as well. The derived control law is tested on the realistic simulator EnergyPlus to evaluate pros and cons of the proposed algorithm. The performance of the suboptimal control law is evaluated on small- and large-scale test cases.

Keywords: Energy management systems; Model Predictive Control; Building heating systems; Demand response; Mathematical modeling; Optimization (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (48)

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DOI: 10.1016/j.apenergy.2016.01.088

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