2015•Unpublished venueRequires access

MPC-based reference governors for thermostatically controlled residential buildings

Ján Drgoňa, Martin Klaučo, Michal Kvasnica

Open publisher page 16 citations

Abstract

This paper tackles the design of a reference governor strategy based on model predictive control (MPC) which allows to improve economics of conventional relay-based thermostats in residential buildings. In this set up, MPC serves as a supervisory controller which generates optimal setpoints for the thermostat. The thermostat, which operates in an on/off manner, then controls the heating actuator that influences the indoor temperature. We show how to include the dynamical behavior of such a thermostat into the MPC optimization problem. Optimal setpoints can then be obtained by solving a mixed integer linear programming problem. Efficiency of the proposed strategy is verified on a simulation case study.

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What this paper is about

This paper tackles the design of a reference governor strategy based on model predictive control (MPC) which allows to improve economics of conventional relay-based thermostats in residential buildings. In this set up, MPC serves as a supervisory controller which generates optimal setpoints for the thermostat. The thermostat, which operates in an on/off manner, then controls the heating actuator that influences the indoor temperature. We show how to include the dynamical behavior of such a thermostat into the MPC optimization problem. Optimal setpoints can then be obtained by solving a mixed integer linear programming problem. Efficiency of the proposed strategy is verified on a simulation case study.

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OpenAlex reports 16 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper tackles the design of a reference governor strategy based on model predictive control (MPC) which allows to improve economics of conventional relay-based thermostats in residential buildings. In this set up, MPC serves as a supervisory controller which generates optimal setpoints for the thermostat. The thermostat, which operates in an on/off manner, then controls the heating actuator that influences the indoor temperature. We show how to include the dynamical behavior of such a thermostat into the MPC optimization problem. Optimal setpoints can then be obtained by solving a mixed integer linear programming problem. Efficiency of the proposed strategy is verified on a simulation case study.

Key concepts: Thermostat, Control theory (sociology), Actuator, Model predictive control, Governor, Computer science, Controller (irrigation), Linear programming

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