Preference-based modelling and prediction of occupants window behaviour in non-air-conditioned office buildings

In naturally ventilated buildings, occupants play a key role in the performance and energy efficiency of the building operation, mainly through the opening and closing of windows. To include the effects of building occupants within building performance simulation, several useful models describing building occupants and their window opening/closing behaviour have been generated in the past 20 years. However, in these models, the occupants are classified based on the whole population or on sub-groups within a building, whilst the behavioural difference between individuals is commonly ignored. This research project addresses this latter issue by evaluating the importance of the modelling and prediction of occupants window behaviour individually, rather than putting them into a larger population group. The analysis is based on field-measured data collected from a case study building containing a number of single-occupied cellular offices. The study focuses on the final position of windows at the end of the working day. In the survey, 36 offices and their occupants were monitored, with respect to the occupants presence and window use behaviour, in three main periods of a year: summer, winter and transitional. From the behaviour analysis, several non-environmental factors, namely, season, floor level, gender and personal preference, are identified to have a statistically significant effect on the end-of-day window position in the building examined. Using these factors, occupants window behaviour is modelled by three different classification methods of building occupants, namely, whole population, sub-groups and personal preference. The preference-based model is found to perform much better predictive ability on window state when compared with those developed based on whole population and sub-groups. When used in a realistic building simulation problem, the preference-based prediction of window behaviour can reflect well the different energy performance among individual rooms, caused by different window use patterns. This cannot be demonstrated by the other two models. The findings from this research project will help both building designers and building managers to obtain a more accurate prediction of building performance and a better understanding of what is happening in actual buildings. Additionally, if the habits and behavioural preferences of occupants are well understood, this knowledge can be potentially used to increase the efficiency of building operation, by either relocating occupants within the building or by educating them to be more energy efficient

The impact of updated building design standards on the thermal environment and energy performance of dwellings in China

Energy demand reduction has become a global issue involving all countries, including China. As major energy consumers in today’s society, the need for buildings to be built and operated more energy efficiently is well recognized. In 1995, the national standard on building energy efficiency in China (JGJ 26-95) was refined and updated to become the new residential Buildings standard (JGJ 26-2010) published in 2010. In the new version, many changes have been made to support the construction of more energy efficient buildings in China. For example, in the new standard, all buildings are highly recommended to install personal control on the heating system, such as by Thermostatic Radiator Valves (TRVs), together with ‘pay for what you use’ tariffs. Previous practice comprised uncontrolled heating with payment based on floor area. This paper evaluates the impact of updated building design standards on thermal conditions and energy consumption in Chinese residential buildings. In the study, two types of residential buildings have been chosen, one complying with the old Chinese building design standard, while the other complies with the new standard. The study was carried out in seven apartments in each building, with a longitudinal monitoring of indoor air temperature, outdoor air temperature, window position and energy consumption. The impact of the new design standard has been evaluated in relation to a number of aspects, that include building construction, indoor thermal environment, occupant behaviour, thermal comfort and building energy consumption. It is concluded that updating the building design standard has had a positive influence on the building conditions and energy consumption

Decision support to enable energy efficient building design for optimised retrofit and maintenance

Optimising energy consumption of new buildings (through design) and reducing energy consumption of existing buildings (using optimised retrofitting or maintenance) are important to achieving the global targets of energy saving and cutting CO2 emissions of buildings. Many decision support tools have been developed for architects and building designers to choose the best building design options with retrofit and maintenance in mind. However, there is a lack of understanding of the required data structures and databases that would support design and enable Facility Management (FM) in making best decisions during retrofit and maintenance for improved energy efficiency (EE). To address these limitations a decision support tool based on Multiple Criteria Decision Making (MCDM) for architects, energy designers and for FM is being developed within an ongoing EU research project “Design4Energy”, to enable design for EE maintenance and retrofit and support the FM in the operation stage. In this paper three aspects are presented: (1) analysis of existing decision support tools; (2) detailing the database requirements in terms of information technology (IT), components and systems, materials and the stakeholders on the basis of a literature search and a survey conducted with of stakeholders from the building sector; (3) a first prototype of a decision support tool for maintenance and retrofit being developed

Current state and requirements in components and energy systems databases

With the objective to develop a suitable database for the Design4Energy (D4E) workspace, the requirement identification of the component and energy system database started from the analysis of the existing database solutions. The classification, evaluation and analysis of the state of the art of the BIM and energy efficiency oriented database have inspired the requirement identification and also the approach, concept and functionalities design in T3.2. This document then identifies the major related stakeholders of the envisioned platform and project outputs. Taking into account the project objectives and the interests of the analysed stakeholders, this report brings the requirement for simulation outputs which could help the end users or architects to understand the energetic performance of their on-going design, IT requirements in architecture, data structure and interface, as well as the operation and maintenance issues. As another main focus of this document, components and energy systems database (DB) are detailed described. It defines and recommends the parameters for different building components such as wall, roof, floor, windows and doors, lighting system, renewable energy system and HVAC components such as heat pump, boiler, energy storage and distribution. During the research of the database requirement, interviews, questionnaire, literature review, internal discussions with partners and energy experts, investigation of the simulation software and BIM technologies have been the main data sources. The key information presented within this document can be summarised as follows: · Objectives and vision of the component and energy system database. · Analysis of existing database solutions. By classifying the current practices into three categories: construction material database, component database and others such as building type database, different technologies and platforms are analysed. · Identification and analysis of the major stakeholders related to the D4E scope. · Questionnaire design and the collected results · Database requirement in system architecture, interoperability, data structure, user interface and user management. · Database requirement description of the simulation outputs, specifying the interesting data which could help the end users to understand their on-going building design. · Database requirement description of the operation and maintenance related issues. · Database requirement description of building components, including envelope (wall, covers/roof, floor), window and door. The recommended parameters are given in table format. · Database requirement description of energy systems, focusing on the subcategories like lighting system, renewable energy, heat pump, boiler, energy storage and distribution, in each subcategory, requirements for specific technologies are described. Introduction of the strengths and weaknesses of the latest and popular technologies is also included in appendices

Functional requirements and system architecture for decision support of energy efficient building design in retrofit and maintenance stage

This paper describes development of a methodology to support better retrofit and maintenance with optimised energy consumption using evolving technologies in material, components and systems both at building and neighbourhood levels. It is based on a retrofit and maintenance scenario focused on specification of the functional requirements, databases requirement and system architecture for the construction and operation of the decision support tool. Decision support (DS) tools have already been developed for architects and building designers to choose best building design options with retrofit and maintenance in mind. However, there is a lack of understanding of the required data structures, databases, definition of the functional requirements and the variety of the possible system architectures for this application. The proposed DS tool will support Facility Management (FM) to design their option on Building Information Model (BIM) file by making best retrofit and maintenance decisions for improved energy efficiency (EE) without needing full knowledge of the latest technologies in any required subject and without being expert in building energy performance analysis and simulation. A detailed retrofit and maintenance scenario and its corresponding process map are developed and explained in details. Database requirements are extracted and discussed, leading to specification of the necessary structure and content with a level of details. The functional requirements for retrofit and maintenance design scenario are discussed and an exhaustive list is generated. The decision support tool was structured using four building blocks: (i) energy performance and simulation block; (ii) retrofit and maintenance options generator; (iii) optimisation block and; (iv) a decision making block based on Multiple Criteria Decision Making (MCDM) method

Effectiveness of using phase change materials on reducing summer overheating issues in UK residential buildings with identification of influential factors

The UK is currently suffering great overheating issues in summer, especially in residential buildings where no air-conditioning has been installed. This overheating will seriously affect people’s comfort and even health, especially for elderly people. Phase change materials (PCMs) have been considered as a useful passive method, which absorb excessive heat when the room is hot and release the stored heat when the room is cool. This research has adopted a simulation method in Design Builder to evaluate the effectiveness of using PCMs to reduce the overheating issues in UK residential applications and has analyzed potential factors that will influence the effectiveness of overheating. The factors include environment-related (location of the building, global warming/climate change) and construction-related (location of the PCM, insulation, heavyweight/lightweight construction). This research provides useful evidence about using PCMs in UK residential applications and the results are helpful for architects and engineers to decide when and where to use PCMs in buildings to maintain a low carbon lifestyle

A field study on occupants’ ventilation behaviour through balcony doors in university students’ apartments during transitional seasons in Beijing

Occupant behaviour has an important role in both the environmental performance and energy performance of buildings, which has been thoroughly demonstrated in the past several decades. Based on a review work, some research gaps have been identified in the area of occupants’ ventilation behaviour and to answer those gaps a field study was carried out in a student dormitory building in Beijing, China, over the period of one transitional season in 2015. The study monitored students’ ventilation behaviour dynamically with concurrent measurement of relevant influential factors that have been identified in existing studies carried out in conventional buildings. The analysis carried out in the study aimed to demonstrate the influence of those previously-identified factors in the case study building. The factors examined in the study included outdoor air temperature, indoor air temperature, occupant presence, and certain aspects relating to personal preferences. From the analysis, it was found that all these factors can influence students’ ventilation behaviour in dormitories. However, the influence of occupant presence seems to be different from the findings in conventional buildings which focused mainly on the use of external windows, and not balcony doors, which are included in this study

Impact of occupant behaviour on the energy-saving potential of retrofit measures for a public building in the UK

© 2016 Taylor & Francis In building refurbishment projects, dynamic building simulation is popularly used to predict the energy-saving potential of various refurbishment scenarios. However, in this process, it is not clear whether occupant behaviour should be carefully modelled due to the lack of evidence about its impact on the prediction results. To answer this question, this study selected a UK public building and used dynamic building simulation to predict the energy-saving potential of common refurbishment measures, under various occupant behavioural conditions. The results revealed that for the case study building occupants’ heating behaviour has a significant impact on the predicted energy-saving potential of all evaluated refurbishment measures: when changing from passive heating users to active heating users, the energy-saving potential was nearly doubled. Although occupants’ window opening behaviour was not shown to be as important as heating behaviour for the refurbishment of the case study building, it has a specific influence on the refurbishment measure of increasing window layers: when windows are opened longer, the effectiveness of increasing window layers on promoting the building energy efficiency is decreased. According to the findings from this study, occupant behaviour should be considered as an important aspect in building refurbishment projects

Design specification and system architecture of a decision support of energy efficiency building retrofit and maintenance instructions

This paper describes the development of a methodology to better support retrofit and maintenance for optimised energy consumption based on automated decision support. The process takes into account evolving technologies in material, components and systems at building and neighbourhood levels to make optimised decisions for users and clients. The methodology builds on a retrofit and maintenance scenario then specification of the functional requirements, databases requirement and system architecture for the creation and operation of the decision support tool. Decision support tools have already been developed for architects and building designers to choose best building design options with retrofit and maintenance in mind. However, there is still a lack of understanding of the required data structures, databases and system architecture for advanced and easy decision making. The proposed method involves energy performance analyses of the proposed solutions and interactions with the user to reach an optimal choice for the client. To choose the optimal solution the system will automatically generate all possible alternatives then conduct an evaluation of the options on the basis of a selection of criteria. First the criteria are weighed for their importance to use in ranking the alternatives automatically. The proposed DS tool would support Facility Management (FM) to design their option on Building Information Model (BIM) file, using energy performance analysis and other techniques without being an expert in building energy performance analysis and simulation or costing for example. The functional requirements for the retrofit and maintenance design scenario are discussed and an exhaustive list is generated. The decision support tool is structured using four building blocks which are: (i) energy performance and simulation block; (ii) retrofit and maintenance options generator; (iii) optimisation block and; (iv) the decision making block that is based on Multiple Criteria Decision Making (MCDM) method

A cross comparison between different methods measuring environmental parameters for occupant window behaviour

When studying occupant window behaviour in buildings, the measurement of environmental factors often requires dedicated measuring equipment. Currently, there is no universally accepted methods for the measurement, and in particular the location of sensors. Therefore, researchers more often select the one they are most familiar with, which reduces the comparability of the collected data for different studies. This study, therefore, has carried out a comprehensive review on the existing methods used to measure significant environmental factors, such as indoor and outdoor temperatures, occupant window operation, and relevant adaptive behaviour. The study repeated different methods to measure both indoor temperature and outdoor temperatures in a case study and compared different environmental factors. From the analysis, it was found that the differences due to various indoor measurement methods was not quite significant, although there were obvious deviations from the reference value. Some environmental factors, such as solar gain and window opening, had greater influences and created larger differences. For outdoor measurement, the distance between the location of measured data to the case study building seemed to have significant impact. To make use of different behavioural studies as shared data base, it is recommended to develop a comprehensive standard methodology for measuring environmental factors.</p