Journal ArticleDOI
Building modeling as a crucial part for building predictive control
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TLDR
In this paper, the authors provide an overview of identification methods for buildings and analyze their applicability for subsequent predictive control, and propose a new methodology to obtain a model suitable for the use in a predictive control framework combining the building energy performance simulation tools and statistical identification.About:
This article is published in Energy and Buildings.The article was published on 2013-01-01. It has received 306 citations till now. The article focuses on the topics: Building science & Building automation.read more
Citations
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Journal ArticleDOI
An evaluation of the suitability of lumped-capacitance models in calculating energy needs and thermal behaviour of buildings
TL;DR: In this article, the suitability of these models in calculating peak loads and seasonal energy needs and their accuracy in estimating buildings' dynamic behaviour was investigated and a room and an apartment were simulated using simplified models and with the benchmarked software TRNSYS.
Journal ArticleDOI
Management of hybrid energy supply systems in buildings using mixed-integer model predictive control
TL;DR: In this paper, a mixed-integer model predictive controller for hybrid energy supply systems in buildings is presented, which is based on a hierarchical building control concept where the energy supply level is coupled to the energy consumption level only by the heat load.
Journal ArticleDOI
A new comprehensive approach for cost-optimal building design integrated with the multi-objective model predictive control of HVAC systems
TL;DR: In this article, a new comprehensive approach is proposed to support cost-optimal design of building envelope's thermal characteristics and HVAC (heating, ventilating and air-conditioning) systems in presence of a simulation-based model predictive control (MPC) for heating and cooling operations.
Proceedings ArticleDOI
Online Simultaneous State Estimation and Parameter Adaptation for Building Predictive Control
Mehdi Maasoumy,Barzin Moridian,Meysam Razmara,Mahdi Shahbakhti,Alberto Sangiovanni-Vincentelli +4 more
TL;DR: The Parameter-Adaptive Building (PAB) model as mentioned in this paper uses Extended Kalman Filter (EKF) and unscented Kalman filter (UKF) techniques to tune the parameters of the building model and provide an estimate for all states of the model.
Journal ArticleDOI
Modeling Environment for Model Predictive Control of Buildings
TL;DR: The Model Predictive Control (MPC) is an advanced control that can be used for dynamic optimization of HVAC equipment as discussed by the authors, and it has been shown that a simplified building model can adequately replace a more complex model, resulting in significantly shorter computational times for optimization.
References
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Book
The EM algorithm and extensions
TL;DR: The EM Algorithm and Extensions describes the formulation of the EM algorithm, details its methodology, discusses its implementation, and illustrates applications in many statistical contexts, opening the door to the tremendous potential of this remarkably versatile statistical tool.
Journal ArticleDOI
A review on buildings energy consumption information
TL;DR: In this article, the authors analyzed available information concerning energy consumption in buildings, and particularly related to HVAC systems, and compared different types of building types and end uses in different countries.
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Finding the Observed Information Matrix When Using the EM Algorithm
TL;DR: A procedure is derived for extracting the observed information matrix when the EM algorithm is used to find maximum likelihood estimates in incomplete data problems and a method useful in speeding up the convergence of the EM algorithms is developed.
Journal ArticleDOI
N4SID: subspace algorithms for the identification of combined deterministic-stochastic systems
TL;DR: Two new N4SID algorithms to identify mixed deterministic-stochastic systems are derived and these new algorithms are compared with existing subspace algorithms in theory and in practice.