Buildings in Europe are the largest end use sector and especially residential buildings account for two thirds of this energy use. Despite the fact that building characteristics play a major role in a dwelling’s energy consumption, occupant characteristics and behaviour significantly affect this energy use as well. The Ecommon campaign monitored 32 residential dwellings for 6 months in the Netherlands, capturing quantitative (temperature, CO2, humidity, movement, boiler and ventilation electricity consumption, real time and total electricity and gas consumption on the meter) and quantitative data (comfort perception, actions taken like closing and opening windows, thermostat use, use and type of clothes, and metabolic activity). Additionally in the beginning of the campaign a survey was given to the tenants with questions on income, gender, education level, thermostat and ventilation preferences, bathing patterns and other related data. This paper describes the experimental set up of the campaign, the temperature and occupancy profiles for each type of room for the 32 dwellings and the findings on the clothing patterns and metabolic activity. Temperature profiles show that these dwellings have higher temperatures through the whole day than the common assumption of the daily average of 18 o C suggested for the calculations of the national simulation software. A method is demonstrated on how a combination of motion detection and CO2 can lead to reliable occupancy profiles.@en

Indoor thermal comfort is generally assessed using the PMV or the adaptive model. This research presents the results obtained by in-situ real time measurements of thermal comfort and thermal comfort perception in 17 residential dwellings in the Netherlands. The study demonstrates the new possibilities offered by relatively cheap, sensor-rich environments to collect data on clothing, heating, and activities related to thermal comfort, which can be used to improve and validate existing comfort models. The results are analysed against the adaptive comfort model and its underlying assumptions. Data analysis showed that while indoor temperatures are within the adaptive model's comfort bandwidth, occupants often reported comfort sensations other than neutral. Furthermore, when indoor temperatures were below the comfort bandwidth, tenants also often reported that they felt ‘neutral’. The adaptive model could overestimate as well as underestimate the occupant's adaptive capacity towards thermal comfort. Despite the significant outdoors temperature variation, the indoor temperature of the dwellings and the clothing were observed to remain largely constant. Certain actions towards thermal comfort such as ‘turning the thermostat up’ were taking place while tenants were reporting thermal sensation ‘neutral’ or ‘a bit warm’. This indicates that either there is an indiscrimination among the various thermal sensation levels or alliesthesia plays a role and the neutral sensation is not comfortable, or many actions are happening out of habit and not in order to improve one's thermal comfort. A chi2 analysis showed that only six actions were correlated to thermal sensation in thermally poorly efficient dwellings, and six in thermally efficient dwellings.@en

Reducing energy consumption in the residential sector is an imperative EU goal until 2020. An important boundary condition in buildings is that energy savings shouldn’t be achieved at the expense of thermal comfort. There is, however, little known about comfort perception in residential buildings and its relation to the PMV theory. In this research an in-situ method for real time measurements of the quantitative and qualitative parameters that affect thermal comfort as well as the reported thermal comfort perception was developed and applied in 30 residential dwellings in the Netherlands. Quantitative data (air temperature, relative humidity, presence) have been wirelessly gathered with 5 minutes interval for 6 months. The thermal sensation was gathered wirelessly as well, using a battery powered comfort dial. Other qualitative data (metabolic activity, clothing, actions related to thermal comfort) were collected twice a day using a diary. The data analysis showed that while the neutral temperatures are well predicted by the PMV method, the cold and warm sensations are not. It seems that people reported (on a statistically significant way) comfortable sensation while the PMV method doesn’t predict it, indicating a certain level of psychological adaptation to expectations. Additionally it was found that, although clothing and metabolic activities were similar among tenants of houses with different thermal quality, the neutral temperature was different: in houses with a good energy rating, the neutral temperature was higher than in houses with a poor rating.@en

Residential buildings account for a significant amount of the national energy consumption of all OECD countries and consequently the EU and the Netherlands. Therefore, the national targets for CO2 reduction should include provisions for a more energy efficient building stock for all EU member states. National and European level policies the past decades have improved the quality of the building stock by setting stricter standards on the external envelope of newly made buildings, the efficiency of the mechanical and heating components, the renovation practices and by establishing an energy labelling system. Energy related occupancy behavior is a significant part, and relatively unchartered, of buildings’ energy consumption. This thesis tried to contribute to the understanding of the role of the occupant related to the energy consumption of residential buildings by means of simulations and experimental data obtained by an extensive measurement campaign.@en

This report presents the results of the second part of the Monicair project1, which aim was to explore in how far the better determination of a number of parameters, which up to now were measured on-ly seldom, could support the development of better prediction models for the heating energy con-sumption in dwellings. Energy labelling calculations, as well as energy consumption forecasts, on which energy policies rely, are based on models. In the past years several studies have demonstrated that these models show large deviations from reality, making the prediction of possible energy sav-ings biased. These poor predictions can be hypothesised to be the result of poor estimation of the U–values of walls, poor estimation of the infiltration and ventilation flow rates and poor estimation of the heated surface area and of the temperature preferences of occupants. Additionally, there is very little knowledge on how occupant’s perception of comfort influences their ventilation and heating behaviour and finally the total energy use for heating. This report presents the results of a field study in which monitoring data was collected in order to further analyse parameters that could influence strongly the heating energy consumption and to fi-nally improve energy prediction models. A mix of modern and older dwellings was studied, as this can give a better idea of possible energy savings when renovating dwellings. @en