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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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Citations
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Journal ArticleDOI

Non-linear grey-box modelling for heat dynamics of buildings

TL;DR: In this article, a non-linear grey-box model based on stochastic differential equations is proposed to describe the heat dynamics of a school building in Denmark, equipped with a water-based heating system.
Journal ArticleDOI

Model predictive control under forecast uncertainty for optimal operation of buildings with integrated solar systems

TL;DR: A new approximate dynamic programming methodology is introduced that represents the optimal cost-to-go functions using Gaussian process regression, and achieves good solution quality.
Journal ArticleDOI

Calibration of building thermal models using an optimal control approach

TL;DR: In this paper, an adjoint model is introduced to derive the gradient of a least squares cost function at a low computational cost, which can be solved in real-time in a continuous monitoring process.
Proceedings ArticleDOI

Using reinforcement learning for optimizing heat pump control in a building model in Modelica

TL;DR: This paper illustrates that Modelica can be used to provide a detailed environment for a BRL algorithm and demonstrates that the obtained policy outperforms both and is economically feasible after a limited amount of training days.
Journal ArticleDOI

Optimizing HVAC Energy Usage in Industrial Processes by Scheduling Based on Weather Data

TL;DR: This paper proposes a binary (0,1) integer linear programming approach to efficiently schedule activities based on weather forecasting, thus minimizing the energy required by HVAC.
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.
Journal ArticleDOI

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

Journal ArticleDOI

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.