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Probabilistic models of window opening behaviour in office buildings

Valentina Maggiora

Probabilistic models of window opening behaviour in office buildings.

Rel. Stefano Paolo Corgnati, Valentina Fabi, Rune Vinther Andersen. Politecnico di Torino, Corso di laurea magistrale in Architettura Costruzione Città, 2013


The European Union gave a pivotal importance to the sustainable development by promoting policies conveyed to make this concept becoming a reality. The three goals proposed to avoid climate changes and reduce the impact of our current lifestyle on the planet, affect also the construction industry. As a matter of fact in Europe buildings account for a 40% in the overall primary energy consumption, specifically a share of 22% is due to the residential sector and 18% to the office buildings construction.

We pass most of our lifetime inside buildings that wear out natural resources to keep comfortable and pleasant the indoor environments by heating, cooling, ventilating and illuminating. For these reasons the biggest potential energy reduction, around 30%, is addressed to the building sector.

Between the European objectives at 2020, the challenge architects and engineers have to face 2concerns a more efficient energy use in building, where the balance between produced energy and actual consumption is near to zero. The current trend to achieve this goal is oriented towards measures and techniques for maximizing the gains and minimizing the losses. However, focusing on building orientation and shape, windows position, shading devices, insulation systems but also on the plant systems and the kind of resources they use is just the top of the iceberg.

One of the most significant barriers to reduce energy consumption and to achieve the energy efficiency promoted by the European Union is the large discrepancy between the real energy use and the one predicted during the design phase (Lutzenhiser 1987, Branco et al. 2004, Andersen et al. 2008, Brohus et al. 2010), making useless all the efforts done so far to reduce energy consumption. The international project IEA ECBCS (Energy Conservation in Buildings & Community Systems) Annex 53 promoted different research fields starting from the assumption that reasons for this discrepancy are poorly understood and often, they are more related to human behaviour than building design.

Thermal and air quality are the principle factors influencing the human perception of indoor environments and consequently comfort, intended as the “the state of mind which expresses satisfaction with the thermal environment” (ASHRAE 55-2004), is thought to be one of the main drivers leading people to react and act to external stimuli. As a matter of fact, the use of thermostats, lights, windows, etc. creates an energy demand that, if the devices are not used properly, can cause grater energy costs.

One of the first concerns of architects and engineers towards occupants should be to provide a high quality of indoor conditions balanced with the lowest energy costs. Moreover they should also guarantee to occupants the highest level of possible interactions with the environmental controls (Wagner, 2007).

The main principle of the adaptive comfort has been enclosed by Nicol and Humphreys (2002) in these few words: "if a change occurs to produce discomfort, people react in ways which tend to restore their comfort”. Usually windows are the most common thermal devices used to achieve satisfactory thermal conditions (Rijal et al. 2007). Indeed they are a key factor to give the occupant the freedom to achieve their comfort conditions naturally, avoiding the cooling costs.

This master thesis starts from this background and it follows the current methodology to analyze and model occupant’s behaviour that, as Schweiker (2010) stressed is only a side of the human behaviour; our actions on building devices are influenced by psychological, physiological, social and environmental factors. Given the extreme variability of these parameters and their unpredictable combinations, only by switching from a deterministic to a probabilistic approach to occupants’ behaviour it will be possible to accomplish at the European request in a more truthful way.

This thesis aims to give a small contribution to the research in the occupants’ behaviour field trying to give an answer to the subsequent questions:

What are the environmental parameters (indoor temperature, outdoor temperature, C02, relative humidity, etc) leading us to open a window?

How the occupants’ behaviour research can be useful for architects and engineers?

What is the effect of a probabilistic approach on energy consumption?

This dissertation is structured in four main chapters describing the progressive steps of this research about occupants’ behaviour:

• The first chapter provides an overview of the reasons and of the main factors that brought to consider the occupants’ behaviour in energy saving policies. Moreover a brief description of the relation between human and comfort in inhabited spaces is provided.

• The second chapter is based on the previous studies found in literature and it describes the theory of the energy-related occupants’ behaviour. Specifically the chapter starts with the description of field surveys (questionnaires and monitoring campaign), it passes through an overview of the statistical methods used to infer the probability of actions on building devices and of the methods that can be used to implement these models into simulations software, and it ends with an overview of the state of the art concerning window opening probabilistic models.

• The third chapter reports the results of the research developed from the database, a collection of physical environmental parameters monitored in eight offices of the Czech Technical University in Prague; the database was previously prepared by selecting the variables that could be theatrically related to an opening or closing action on the window. Considering that the large variety of variable monitored was different for each room, probability sub-models for opening and closing were inferred separately for each of them. A forward selection in the logistic regression was used to select the predictors and find the equation related to the opening and closing action. One of the seven probabilistic models found, was chosen to be implemented into the energy simulation software IDA ICE and to test the impact of a probabilistic approach in building energy simulation comparing the result to the deterministic one.

• The four and last chapter considers the implication of the probabilistic analysis of the occupants’ behaviour in different energy saving approach; specifically it consider the implications of using a probabilistic model of occupants’ behaviour in new approaches to building design and the development of new technological systems to guarantee energy efficiency. Moreover it is also stressed the importance of the occupants awareness concerning the consequences on energy consumption.

Relators: Stefano Paolo Corgnati, Valentina Fabi, Rune Vinther Andersen
Publication type: Printed
Subjects: A Architettura > AO Design
A Architettura > AQ Functional spaces of the dwelling
Corso di laurea: Corso di laurea magistrale in Architettura Costruzione Città
Classe di laurea: UNSPECIFIED
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/3394

Executive summary


1 Introduction

1.1 Background

1.1.1 European perspective

1.1.2 Focusing on utility system and envelope optimization

1.1.3 IEA ECBS Annex 53: a human centred vision

1.2 Occupants’ behaviour and thermal comfort

1.3 Aim of the study

2 From modelling to simulation: the theory of energy-related occupants’ behaviour

2.1 Modelling the energy-related occupant behaviour

2.2 Different mathematical approaches

2.3 Simulating the energy-related occupant behaviour

2.4 Windows behaviour: state of the art

3 From monitoring to simulation: practice on a case-study

3.1 Observing the reality: the office building in Prague

3.1.1 The supporting project

3.1.2 The hypothetical drivers

3.1.3 The subjective drivers of occupant behaviour:

the questionnaire survey

3.2 Database features

3.3 Behavioural statistical models

3.3.1 Statistical results

3.3.2 Common features

3.3.3 Further improvements

3.4 Simulating the reality

3.4.1 The building reference model

3.4.2 The statistical input implementation

4 Conclusive chapter

4.1 Creativity and technology

4.2 To sum up

4.3 General Conclusions




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