Towards a classification of the building stock in terms of potential energy savings through advanced control

Wagner, Alexis; Ruellan, Marie; Heinrich, Matthias; Bourdais, Romain

doi:10.1016/j.enbuild.2024.114050

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2024

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Cited by 2 publications

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Building Potential Energy Savings Estimation Through Portfolio-Based Modeling

Matson,

Vassiljeva,

Parts

et al. 2024

Lecture Notes in Computer Science

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Building Potential Energy Savings Estimation Through Portfolio-Based Modeling

Matson,

Vassiljeva,

Parts

et al. 2024

Lecture Notes in Computer Science

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Validation of a Model Predictive Control Strategy on a High Fidelity Building Emulator

Fop,

Yaghoubi,

Capozzoli

2024

Energies

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In recent years, advanced controllers, including Model Predictive Control (MPC), have emerged as promising solutions to improve the efficiency of building energy systems. This paper explores the capabilities of MPC in handling multiple control objectives and constraints. A first MPC controller focuses on the task of ensuring thermal comfort in a residential house served by a heat pump while minimizing the operating costs when subject to different pricing schedules. A second MPC controller working on the same system tests the ability of MPC to deal with demand response events by enforcing a time-varying maximum power usage limitation signal from the electric grid. Furthermore, multiple combinations of the control parameters are tested in order to assess their influence on the controller performance. The controllers are tested on the BOPTEST framework, which offers standardized test cases in high-fidelity emulation models, and pre-defined baseline control strategies to allow fair comparisons also across different studies. Results show that MPC is able to handle multi-objective optimal control problems, reducing thermal comfort violations by between 66.9% and 82% and operational costs between 15.8% up to 20.1%, depending on the specific scenario analyzed. Moreover, MPC proves its capability to exploit the building thermal mass to shift heating power consumption, allowing the latter to adapt its time profile to time-varying constraints. The proposed methodology is based on technologically feasible steps that are intended to be easily transferred to large scale, in-field applications.

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Towards a classification of the building stock in terms of potential energy savings through advanced control

Cited by 2 publications

References 31 publications

Building Potential Energy Savings Estimation Through Portfolio-Based Modeling

Building Potential Energy Savings Estimation Through Portfolio-Based Modeling

Validation of a Model Predictive Control Strategy on a High Fidelity Building Emulator

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