@article {31313, title = {Buildings.Occupants: a Modelica package for modelling occupant behaviour in buildings}, journal = {Journal of Building Performance Simulation}, year = {2018}, month = {11/2018}, pages = {1 - 12}, abstract = {

Energy-related occupant behaviour is crucial to design and operation of energy and control systems in buildings. Occupant behaviours are often oversimplified as static schedules or settings in building performance simulation ignoring their stochastic nature. The continuous and dynamic interaction between occupants and building systems motivates their simultaneous simulation in an efficient manner. In the past, simultaneous simulation has relied on co-simulation approaches or customized source code changes to building simulation programmes. This paper presents Buildings. Occupants, an open-source package implemented in Modelica, for the simulation of occupant behaviours of lighting, windows, blinds, heating and air conditioning systems in office and residential buildings. Examples were presented to illustrate how the models in the Occupants package are capable to simulate stochastic occupant behaviours. The major contribution of this work is to introduce the equation-based modelling approach to simulate occupant behaviours in buildings and to develop an open-source Occupants package in the Modelica language

}, keywords = {modelica, Modelica Buildings Library, Modelica Occupants Package, Occupant Behaviour, Occupant behaviour modelling}, issn = {1940-1493}, doi = {10.1080/19401493.2018.1543352}, url = {https://www.tandfonline.com/doi/full/10.1080/19401493.2018.1543352https://www.tandfonline.com/doi/pdf/10.1080/19401493.2018.1543352}, author = {Zhe Wang and Tianzhen Hong and Ruoxi Jia} } @article {30489, title = {A Library of Building Occupant Behaviour Models Represented in a Standardised Schema}, journal = {Energy Efficiency}, year = {2018}, abstract = {

Over the past four decades, a substantial body of literature has explored the impacts of occupant behaviour (OB) on building technologies, operation, and energy consumption. A large number of data-driven behavioural models have been developed based on field data. These models lack standardisation and consistency, leading to difficulties in applications and comparison. To address this problem, an ontology was developed using the drivers-needs-actions-systems (DNAS) framework. Recent work has been carried out to implement the theoretical DNAS framework into an eXtensible Markup Language (XML) schema, titled {\textquoteleft}occupant behaviour XML{\textquoteright} (obXML) which is a practical implementation of OB models that can be integrated into building performance simulation (BPS) programs. This paper presents a newly developed library of OB models represented in the standardised obXML schema format. This library provides ready-to-use examples for BPS users to employ more accurate occupant representation in their energy models. The library, which contains an initial effort of 52 OB models, was made publicly available for the BPS community. As part of the library development process, limitations of the obXML schema were identified and addressed, and future improvements were proposed. Authors hope that by compiling this library building, energy modellers from all over the world can enhance their BPS models by integrating more accurate and robust OB patterns.

}, keywords = {building performance simulation, obXML, Occupant Behaviour, occupant behaviour model, XML schema}, doi = {10.1007/s12053-018-9658-0}, author = {Zsofia Belafi and Tianzhen Hong and Andras Reith} } @article {30305, title = {Smart Building Management vs. Intuitive Human Control {\textemdash} Lessons learnt from an office building in Hungary}, journal = {Building Simulation}, volume = {10}, year = {2017}, month = {12/2017}, pages = {811-828}, abstract = {

Smart building management and control are adopted nowadays to achieve zero-net energy use in buildings. However, without considering the human dimension, technologies alone do not necessarily guarantee high performance in buildings. An office building was designed and built according to state-of-the-art design and energy management principles in 2008. Despite the expectations of high performance, the owner was facing high utility bills and low user comfort in the building located in Budapest, Hungary. The objective of the project was to evaluate the energy performance and comfort indices of the building, to identify the causes of malfunction and to elaborate a comprehensive energy concept. Firstly, current building conditions and operation parameters were evaluated. Our investigation found that the state-of-the-art building management system was in good conditions but it was operated by building operators and occupants who are not aware of the building management practice. The energy consumption patterns of the building were simulated with energy modelling software. The baseline model was calibrated to annual measured energy consumption, using actual occupant behaviour and presence, based on results of self-reported surveys, occupancy sensors and fan-coil usage data. Realistic occupant behaviour models can capture diversity of occupant behaviour and better represent the real energy use of the building. This way our findings and the effect of our proposed improvements could be more reliable. As part of our final comprehensive energy concept, we proposed intervention measures that would increase indoor thermal comfort and decrease energy consumption of the building. A parametric study was carried out to evaluate and quantify energy, comfort and return on investment of each measure. It was found that in the best case the building could save 23\% of annual energy use. Future work includes the follow-up of: occupant reactions to intervention measures, the realized energy savings, the measurement of occupant satisfaction and behavioural changes.

}, keywords = {building operation, building performance simulation, case study, Occupant Behaviour, optimization}, issn = {Print 1996-3599; Online 1996-8744}, doi = {10.1007/s12273-017-0361-4}, author = {Zsofia Belafi and Tianzhen Hong and Andras Reith} }