02422nas a2200217   4500008004100000022001400041245009700055210006900152260001200221300000900233520152700242653002301769653002201792653002801814653002201842653002501864100001901889700001901908700001801927856025901945       2018                        eng d  a1570-646X00aA critical review on questionnaire surveys in the field of energy-related occupant behaviour0 acritical review on questionnaire surveys in the field of energyr  c07/2018  a1-213 a<p>Occupants perform various actions to satisfy their physical and non-physical needs in buildings. These actions greatly affect building operations and thus energy use. Clearly understanding and accurately modelling occupant behaviour in buildings are crucial to guide energy-efficient building design and operation, and to reduce the gap between design and actual energy performance of buildings. To study and understand occupant behaviour, a cross-sectional questionnaire survey is one of the most useful tools to gain insights on general behaviour patterns and drivers, and to find connections between human, social and local comfort parameters. In this study, 33 projects were reviewed from the energy-related occupant behaviour research literature that employed cross-sectional surveys or interviews for data collection from the perspective of findings, limitations and methodological challenges. This research shows that future surveys are needed to bridge the gaps in literature but they would need to encompass a multidisciplinary approach to do so as until now only environmental and engineering factors were considered in these studies. Insights from social practice theories and techniques must be acquired to deploy robust and unbiased questionnaire results, which will provide new, more comprehensive knowledge in the field, and therefore occupant behaviour could be better understood and represented in building performance simulation to support design and operation of low or net-zero energy buildings.</p>10abehaviour modeling10aenergy efficiency10aEnergy use in buildings10aoccupant behavior10aquestionnaire survey1 aBelafi, Zsofia1 aHong, Tianzhen1 aReith, Andras  uhttp://link.springer.com/10.1007/s12053-018-9711-zhttp://link.springer.com/content/pdf/10.1007/s12053-018-9711-z.pdfhttp://link.springer.com/content/pdf/10.1007/s12053-018-9711-z.pdfhttp://link.springer.com/article/10.1007/s12053-018-9711-z/fulltext.html02103nas a2200181   4500008004100000245008900041210006900130520146500199653003601664653001001700653002301710653002901733653001501762100001901777700001901796700001801815856008801833       2018                        eng d00aA Library of Building Occupant Behaviour Models Represented in a Standardised Schema0 aLibrary of Building Occupant Behaviour Models Represented in a S3 a<p>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 ‘occupant behaviour XML’ (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.</p>10abuilding performance simulation10aobXML10aOccupant Behaviour10aoccupant behaviour model10aXML schema1 aBelafi, Zsofia1 aHong, Tianzhen1 aReith, Andras  uhttps://simulationresearch.lbl.gov/publications/library-building-occupant-behaviour02859nas a2200229   4500008004100000022003900041245011200080210006900192260001200261300001200273490000700285520208600292653002302378653003602401653001502437653002302452653001702475100001902492700001902511700001802530856008102548       2017                        eng d  aPrint 1996-3599;  Online 1996-874400aSmart Building Management vs. Intuitive Human Control — Lessons learnt from an office building in Hungary0 aSmart Building Management vs Intuitive Human Control Lessons lea  c12/2017  a811-8280 v103 a<p>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.</p>10abuilding operation10abuilding performance simulation10acase study10aOccupant Behaviour10aoptimization1 aBelafi, Zsofia1 aHong, Tianzhen1 aReith, Andras  uhttps://simulationresearch.lbl.gov/publications/smart-building-management-vs