<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Blum</style></author><author><style face="normal" font="default" size="100%">Filip Jorissen</style></author><author><style face="normal" font="default" size="100%">Sen Huang</style></author><author><style face="normal" font="default" size="100%">Yan Chen</style></author><author><style face="normal" font="default" size="100%">Javier Arroyo</style></author><author><style face="normal" font="default" size="100%">Kyle Benne</style></author><author><style face="normal" font="default" size="100%">Yanfei Li</style></author><author><style face="normal" font="default" size="100%">Valentin Gavan</style></author><author><style face="normal" font="default" size="100%">Lisa Rivalin</style></author><author><style face="normal" font="default" size="100%">Lieve Helsen</style></author><author><style face="normal" font="default" size="100%">Draguna Vrabie</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Marina Sofos</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prototyping the BOPTEST Framework for Simulation-Based Testing of Advanced Control Strategies in Buildings</style></title><secondary-title><style face="normal" font="default" size="100%">IBPSA Building Simulation 2019</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">benchmarking</style></keyword><keyword><style  face="normal" font="default" size="100%">building simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Model predictive control</style></keyword><keyword><style  face="normal" font="default" size="100%">software development</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><pub-location><style face="normal" font="default" size="100%">Rome, Italy</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Advanced control strategies are becoming increasingly necessary in buildings in order to meet and balance requirements for energy efficiency, demand flexibility, and occupant comfort. Additional development and widespread adoption of emerging control strategies, however, ultimately require low implementation costs to reduce payback period and verified performance to gain control vendor, building owner, and operator trust. This is difficult in an already first-cost driven and risk-averse industry. Recent innovations in building simulation can significantly aid in meeting these requirements and spurring innovation at early stages of development by evaluating performance, comparing state-of-the-art to new strategies, providing installation experience, and testing controller implementations. This paper presents the development of a simulation framework consisting of test cases and software platform for the testing of advanced control strategies (BOPTEST - Building Optimization Performance Test). The objectives and requirements of the framework, components of a test case, and proposed software platform architecture are described, and the framework is demonstrated with a prototype implementation and example test case.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Filip Jorissen</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Lieve Helsen</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Simplifications for hydronic system models in Modelica</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Building Performance Simulation</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Building systems and their heating, ventilation and air conditioning ow networks, are becoming increasingly complex. Some building energy simulation tools simulate these ow networks using pressure drop equations. These ow network models typically generate coupled algebraic nonlinear systems of equations, which become increasingly more difficult to solve as their sizes increase. This leads to longer computation times and can cause the solver to fail. These problems also arise when using the equation-based modelling language Modelica and Annex 60 based libraries. This may limit the applicability of the library to relatively small problems unless problems are restructured. This paper discusses two algebraic loop types and presents an approach that decouples algebraic loops into smaller parts, or removes them completely. The approach is applied to a case study model where an algebraic loop of 86 iteration variables is decoupled into smaller parts with a maximum of 5 iteration variables.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Filip Jorissen</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Lieve Helsen</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Simulation Speed Analysis and Improvements of Modelica Models for Building Energy Simulation</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper presents an approach for speeding up Modelica models. Insight is provided into how Modelica models are solved and what determines the tool’s computational speed. Aspects such as algebraic loops, code efficiency and integrator choice are discussed. This is illustrated using simple building simulation examples and Dymola. The generality of the work is in some cases verified using OpenModelica. Using this approach, a medium sized office building including building envelope, heating ventilation and air conditioning (HVAC) systems and control strategy can be simulated at a speed five hundred times faster than real time.&lt;/p&gt;</style></abstract><custom2><style face="normal" font="default" size="100%">LBNL-1002904</style></custom2></record></records></xml>