%0 Journal Article %1 bergero2017efficiency %A Bergero, Federico Martín %A Casella, Francesco %A Kofman, Ernesto %A Fernández, Joaquín %D 2017 %J Building Simulation %K 2017 QSS building simulation solver %R 10.1007/s12273-017-0400-1 %T On the efficiency of quantization-based integration methods for building simulation %U https://doi.org/10.1007/s12273-017-0400-1 %X Models describing energy consumption, heating, and cooling of buildings usually impose difficulties to the numerical integration algorithms used to simulate them. Stiffness and the presence of frequent discontinuities are among the main causes of those difficulties, that become critical when the models grow in size. Quantized State Systems (QSS) methods are a family of numerical integration algorithms that can efficiently handle discontinuities and stiffness in large models. For this reason, they are promising candidates for overcoming the mentioned problems. Based on this observation, this article studies the performance of QSS methods in some systems that are relevant to the field of building simulation. The study includes a performance comparison of different QSS algorithms against state-of-the-art classic numerical solvers, showing that the former can be more than one order of magnitude faster.

@article{bergero2017efficiency, abstract = {Models describing energy consumption, heating, and cooling of buildings usually impose difficulties to the numerical integration algorithms used to simulate them. Stiffness and the presence of frequent discontinuities are among the main causes of those difficulties, that become critical when the models grow in size. Quantized State Systems (QSS) methods are a family of numerical integration algorithms that can efficiently handle discontinuities and stiffness in large models. For this reason, they are promising candidates for overcoming the mentioned problems. Based on this observation, this article studies the performance of QSS methods in some systems that are relevant to the field of building simulation. The study includes a performance comparison of different QSS algorithms against state-of-the-art classic numerical solvers, showing that the former can be more than one order of magnitude faster.}, added-at = {2017-09-05T09:25:04.000+0200}, author = {Bergero, Federico Mart{\'i}n and Casella, Francesco and Kofman, Ernesto and Fern{\'a}ndez, Joaqu{\'i}n}, biburl = {https://www.bibsonomy.org/bibtex/2608eb6778f81fee35915d58fa96a79f5/thorade}, day = 02, description = {On the efficiency of quantization-based integration methods for building simulation | SpringerLink}, doi = {10.1007/s12273-017-0400-1}, interhash = {0aaf811856bd38c6230c9e1dbd48a0aa}, intrahash = {608eb6778f81fee35915d58fa96a79f5}, issn = {1996-8744}, journal = {Building Simulation}, keywords = {2017 QSS building simulation solver}, month = sep, timestamp = {2017-09-05T09:25:04.000+0200}, title = {On the efficiency of quantization-based integration methods for building simulation}, url = {https://doi.org/10.1007/s12273-017-0400-1}, year = 2017 }