Model-Based Predictive Control for building energy management. I: Energy modeling and optimal control

Abstract The simultaneous heat and moisture transfer in the building envelope has an important influence on the indoor climate and the overall thermal performance of buildings. In this work, the development of a Building Energy Analysis Model (BEAM) predicting whole building heat and moisture transfer is presented. The coupled heat and moisture transfer model takes into account most of the main hygrothermal effects in buildings. The coupled system model is implemented in Matlab, and verified with EnergyPlus. Furthermore, BEAM is reduced via a physically based model order reduction to a lower order system model (Re-BEAM) to be easily integrated with a control algorithm. By utilizing Re-BEAM, a Model-Based Predictive Control (MBPC) method is developed to incorporate critical building information into control algorithms, such that the building energy consumption is minimized while comfort conditions are maintained. The resulting optimal setpoint schedule can be applied on any HVAC system. Simulation results of a building structure demonstrate the superiority in terms of energy and peak load reductions compared with traditional constant control methods and control methods that use a occupants-varying temperature schedule.

[1]  M. Chidambara,et al.  Further comments on "A method for simplifying linear dynamic systems" , 1967 .

[2]  Panos J. Antsaklis,et al.  Model-based predictive control for building energy management: Part II – Experimental validations , 2017 .

[3]  Joshua N. Cooper,et al.  Parameter identification and model based predictive control of temperature inside a house , 2011 .

[4]  J. Bear,et al.  Introduction to Modeling of Transport Phenomena in Porous Media , 1990 .

[5]  E. Davison,et al.  On "A method for simplifying linear dynamic systems" , 1966 .

[6]  J. J. Hirsch,et al.  DOE-2 supplement: Version 2.1E , 1993 .

[7]  Jin Wen,et al.  Review of building energy modeling for control and operation , 2014 .

[8]  Igor Mezic,et al.  Building energy modeling: A systematic approach to zoning and model reduction using Koopman Mode Analysis , 2015 .

[9]  Martin Schmelas,et al.  Adaptive predictive control of thermo-active building systems (TABS) based on a multiple regression algorithm , 2015 .

[10]  Sylvain Robert,et al.  State of the art in building modelling and energy performances prediction: A review , 2013 .

[11]  M. M. Gouda,et al.  Building thermal model reduction using nonlinear constrained optimization , 2002 .

[12]  Refrigerating.  ASHRAE handbook of fundamentals , 1967 .

[13]  James E. Braun,et al.  REDUCED-ORDER BUILDING MODELING FOR APPLICATION TO MODEL-BASED PREDICTIVE CONTROL , 2012 .

[14]  Anastasios I. Dounis,et al.  Advanced control systems engineering for energy and comfort management in a building environment--A review , 2009 .

[15]  Fraunhofer-Institut für Bauphysik,et al.  Simultaneous heat and moisture transport in building components: One- and two-dimensional calculation using simple parameters , 1995 .

[16]  Paul Fazio,et al.  Integrated analysis of whole building heat, air and moisture transfer , 2010 .

[17]  Farrokh Janabi-Sharifi,et al.  Theory and applications of HVAC control systems – A review of model predictive control (MPC) , 2014 .

[18]  D. Do,et al.  Capillary condensation of adsorbates in porous materials. , 2011, Advances in colloid and interface science.

[19]  Manfred Morari,et al.  Use of model predictive control and weather forecasts for energy efficient building climate control , 2012 .

[20]  Marija D. Ilic,et al.  Smart residential energy scheduling utilizing two stage Mixed Integer Linear Programming , 2015, 2015 North American Power Symposium (NAPS).

[21]  Björn Johannesson,et al.  Measurement of the Moisture Storage Capacity Using Sorption Balance and Pressure Extractors , 2001 .

[22]  M. Chidambara,et al.  Further remarks on simplifying linear dynamic systems , 1967, IEEE Transactions on Automatic Control.

[23]  Drury B. Crawley,et al.  EnergyPlus: Energy simulation program , 2000 .

[24]  Alfonso P. Ramallo-González,et al.  Lumped parameter models for building thermal modelling: An analytic approach to simplifying complex multi-layered constructions , 2013 .

[25]  J. H. Klems.  U-Values, Solar Heat Gain, and Thermal Performance: Recent Studies Using the MoWiTT , 1989 .

[26]  M. Aoki.  Control of large-scale dynamic systems by aggregation , 1968 .

[27]  James E. Braun,et al.  Development, validation and application of a coupled reduced-order CFD model for building control applications , 2015 .

[28]  Gerardo Maria Mauro,et al.  Simulation-based model predictive control by the multi-objective optimization of building energy performance and thermal comfort , 2016 .

[29]  David E. Culler,et al.  Reducing Transient and Steady State Electricity Consumption in HVAC Using Learning-Based Model-Predictive Control , 2012, Proceedings of the IEEE.

[30]  Alberto Sangiovanni-Vincentelli,et al.  Model-Based Hierarchical Optimal Control Design for HVAC Systems , 2014 .

[31]  Li Song,et al.  Review and Evaluation of Using R-C Thermal Modeling of Cooling Load Prediction for HVAC System Control Purpose , 2012 .

[32]  Frauke Oldewurtel,et al.  Building modeling as a crucial part for building predictive control , 2013 .

[33]  Hartwig M. Künzel,et al.  Simulation of indoor temperature and humidity conditions including hygrothermal interactions with the building envelope , 2005 .

[34]  Jan Carmeliet,et al.  Analysis of convective heat and mass transfer at the vertical walls of a street canyon , 2011 .

[35]  Paul Fazio,et al.  Transient model for coupled heat, air and moisture transfer through multilayered porous media , 2010 .

[36]  B. Anderson,et al.  Optimal control: linear quadratic methods , 1990 .

[37]  A. Bejan.  Convection Heat Transfer , 1984 .

[38]  Rp Rick Kramer,et al.  Simplified thermal and hygric building models： A literature review , 2012 .

[39]  Nursyarizal Mohd Nor,et al.  A review on optimized control systems for building energy and comfort management of smart sustainable buildings , 2014 .

[40]  B. Moore.  Principal component analysis in linear systems: Controllability, observability, and model reduction , 1981 .

[41]  Gilles Fraisse,et al.  Development of a simplified and accurate building model based on electrical analogy , 2002 .

[42]  Marc Abadie,et al.  Moisture performance of building materials: From material characterization to building simulation using the Moisture Buffer Value concept , 2009 .

[43]  M. Sherman.  INFILTRATION-PRESSURIZATION CORRELATION: SIMPLIFIED PHYSICAL MODELING , 1980 .