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Use of model predictive control and weather forecasts for energy efficient building climate control

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In this paper, the authors investigated how ModelPredictive control and weatherpredictions can increase the energy efficiency in Integrated Room Automation (IRA) while respecting occupant comfort.
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This article is published in Energy and Buildings.The article was published on 2012-02-01 and is currently open access. It has received 1070 citations till now. The article focuses on the topics: Model predictive control & HVAC.

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Journal ArticleDOI

A modeling framework for optimal energy management of a residential building

TL;DR: In this paper, a mathematical model for the optimal energy management of a residential building and a centralized energy management system (CEMS) framework for off-grid operation is presented, where the optimal decisions are determined in real-time by considering these models with realistic parameter settings and customer preferences.
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A systematic feature selection procedure for short-term data-driven building energy forecasting model development

TL;DR: A systematic feature selection procedure for developing a building energy forecasting model is proposed which attempts to integrate statistical analysis, building physics and engineering experiences and is compared with models using other feature selection techniques.
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Occupant feedback based model predictive control for thermal comfort and energy optimization: A chamber experimental evaluation

TL;DR: In this paper, the authors explored the benefit of using thermal comfort feedback from occupants in the model predictive control (MPC) design based on a novel dynamic thermal sensation (DTS) model.
Posted Content

Experimental analysis of data-driven control for a building heating system

TL;DR: Model-assisted batch reinforcement learning is applied to the setting of building climate control subjected to dynamic pricing and it is found that within 10 to 20 days sensible policies are obtained that can be used for different outside temperature regimes.
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Price-responsive model predictive control of floor heating systems for demand response using building thermal mass

TL;DR: Test results show that, compared to the conventional on-off controller, the MPC controller is able to use building thermal mass to optimally shift energy consumption to low-price periods, improve thermal comfort at the beginning of occupancy, reduce energy demand during peak periods, and save electricity costs for residential end-users.
References
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Book

Predictive Control With Constraints

TL;DR: A standard formulation of Predictive Control is presented, with examples of step response and transfer function formulations, and a case study of robust predictive control in the context of MATLAB.
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Model predictive control: theory and practice—a survey

TL;DR: The flexible constraint handling capabilities of MPC are shown to be a significant advantage in the context of the overall operating objectives of the process industries and the 1-, 2-, and ∞-norm formulations of the performance objective are discussed.
Journal Article

Optimal Filtering

TL;DR: This book helps to fill the void in the market and does that in a superb manner by covering the standard topics such as Kalman filtering, innovations processes, smoothing, and adaptive and nonlinear estimation.
Book

Stochastic programming

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Meso-gamma scale forecasts using the nonhydrostatic model LM

TL;DR: It is concluded, that orographic filtering is necessary and the effect of such filtering on precipitation forecasts is investigated, and examples of model predictions at the meso-γ scale are given.
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Q1. What have the authors contributed in "Use of model predictive control and weather forecasts for energy efficient building climate control" ?

This paper presents an investigation of how Model Predictive Control ( MPC ) and weather predictions can increase the energy efficiency in Integrated Room Automation ( IRA ) while respecting occupant comfort. In this paper it is reported on the development and analysis of a Stochastic Model Predictive Control ( SMPC ) strategy for building climate control that takes into account hance-constrained control the uncertainty due to the use of weather predictions. As first step the potential of MPC was assessed by means of a large-scale factorial simulation study that considered different types of buildings and HVAC systems at four representative European sites. The findings suggest that SMPC outperforms current control practice.