Life cycle efficiency ratio: a new performance indicator for a life cycle driven approach to evaluate the potential of ventilative cooling and thermal inertia

Building envelope design has gained importance as a means to reduce heating and cooling demand related to a building’s operational phase. However, in high internal load buildings, such as offices, internal gains can easily lead to overheating. Thermal inertia (TI) and night ventilation have a great potential for reducing heat loads and temperature. However, their influence is difficult to predict due to the complex nature of the TI phenomenon, which is related to the interactions of multiple factors such as architecture, building physics and external conditions. Moreover, TI efficacy has often been studied in relation to energy savings or temperature analysis, overlooking other aspects implicated in buildings’ efficiency, such as the embodied energy involved. This paper presents a multidimensional approach to evaluate ventilative cooling and thermal inertia as a sustainable strategy to improve building performances. To that end, several scenarios of night ventilation strategies have been applied to the case study of an experimental double-office room placed in Fribourg (Switzerland). Based on this monitoring, a dynamic software simulation tool has been calibrated and used to analyze the energy savings potential and the life-cycle performance of TI. A new ratio index has been introduced to easily evaluate the life cycle efficiency. The results show the importance of balancing operational and embodied impacts when evaluating a design choice. Although high TI levels have great benefits on reducing the cooling loads, the results are completely different when a life cycle assessment is applied. Natural ventilation coupled with middle levels of TI have been identified as the best strategy to optimize the building’s energy and environmental performances, without compromising indoor temperatures.

On the Adaptation of Building Controls to the Envelope and the Occupants

David Daum

The sun is the biggest known source of energy in our solar system. We feel its strength when it gets hot during the the day and we notice its absence during the night when we feel cold. So as to be less dependent on the sun as an energy source, we implemented additional heating and cooling sources to maintain the temperature within a comfortable range. The downside to this is that the majority of energy consumed within the housing sector is used up on the heating and cooling alone. To profit from the vast energy source of the sun we propose a user-adaptive and building-adaptive blind control for residential buildings, that is implemented in prefabricated modules for facade renovation. User-adaptive means that it is the occupant who is responsible for the temperature control within the home. Building-adaptive, in this context, means that the temperature control is established automatically without any user input. Through the evaluation of occupant queries we have shown that a general measure for thermal comfort is not possible for all occupants. Consequently, there is a need for a personalized measure of thermal comfort. In order to create this the occupant enters votes via the interface; from this we deduced statistically the probability of comfort relative to the indoor temperature. According to the profile the control sets its target temperature. The profile steadily adapts the user's preferences and through this we can also capture seasonal changes in comfort temperature. This guarantees that at each point in time the control system knows the desired temperature and is taking action to achieve it. The adaption to the building is achieved with the fitting of a simple thermal building model with data collected by the sensors of the control system. We showed that the monitored data sufficiently fits the model. With the help of the simple model we evaluated different control strategies and optimized them according to the thermal profile. For our performance tests we conducted computer simulations as well as a 6-month field study. For the simulations, a specific test bed was suggested that would assess the saving potential, which can then be compared to the performance of the tested control. Results showed that the suggested control system is capitalizing on most of the achievable energy savings and thermal comfort. A 6-month field study in the LESO-PB building was carried out to test the impact on energy demand as well as comfort under real conditions. It appeared that the automatically controlled office needed only approximately 50% of the average heating energy that was used in the manually controlled offices. Furthermore, the probability of thermal comfort was, on average, 10% higher in the automatically controlled offices when compared to those that were controlled manually.

EPFL2011

Qualitative modelling of the natural ventilation potential in urban context

Mario Germano

The two objectives of natural ventilation in buildings are the improvement of indoor air quality and thermal comfort. The methodology proposed hereafter provides an assessment of the natural ventilation potential for indoor air quality, while taking into consideration the other objective. More precisely, requirements on comfort impose the appropriate ventilation strategies to be applied for each given meteorological situation. On the basis of these strategies, the methodology evaluates the appropriateness of a given location to natural ventilation. After a historical introduction (Chapter 1), the statement of the problem (Chapter 2) and a review of the state of the art (Chapter 3), Chapter 4 presents a novel methodology to assess the natural ventilation potential starting from its driving forces (wind-induced and buoyancy-induced pressures) and from its constraints (noise pollution and atmospheric pollution), which applies multicriteria analysis. The method uses the results of the atmospheric simulation model Lokal-Modell (LM, described in section 3.4). The related software tool, developed within the European project Urbvent, and tested against real cases, is presented as well. Chapter 5 gives a view of the results of an atmospheric mesoscale model, referred to as Finite Volume Model (FVM), that includes an urban module (described in section 3.6) allowing to compute the effects of the urban tissue on meteorological parameters. This model has been adapted as part of this work to use the outputs of the above-mentioned Lokal-Modell (LM) as boundary conditions. (To this end, previous works utilized NCEP/NCAR Reanalysis data, with an original spatial resolution 40 times lower than LM in latitude, 25 times lower in longitude and 6 times lower in time.) After a verification of the urban model results against on site measurements carried out in the Basel region (Switzerland) over a summertime period, Chapter 6 presents the utilization of these results within the Urbvent method of Chapter 4. The ensuing potential for natural ventilation is the object of a verification resorting to an air pollution exposure study (Expolis) in section 6.4. Attention is drawn to the fact that it has been decided to assess the natural ventilation potential of the site itself, in the most building-independent way. In so doing, an analysis of the results can tell what type of ventilation a given site is suited for and what kind of building should be built there (or how to refurbish an existing one). Put another way, the model examines whether external conditions required for applying natural ventilation coexist. How to properly design a building taking advantage of theses conditions is not addressed here. This is left to the reader or to the designer. Incidentally, the bibliography dealing with this very topic is quite abundant.

EPFL2006

Reducing Greenhouse Gas emissions is not the only solution

Justine Brun

With the increasing strength and frequency of climate change events, the urgency to mitigate climate change impact is ever so important. Canada reported his Nationally Determined Contribution (NDC) and submitted its ambition to reduce his Greenhouse Gas (GHG) emissions by 40-45% by 2030 compared to 2005 and reach net-zero emissions by 2050. Interest for energy system modelling has been increasing for planning future energy systems, as a result of growing concern for sustainable development and transition towards renewable energies. Nevertheless, planning a decarbonization of energy system can potentially lead to environmental burden shifting, and can increase impacts on other environmental impacts such as ecosystem quality or human health. Thus, this project aims towards integrating Life Cycle Analysis (LCA) and more specifically Life Cycle Impact Assessment (LCIA) within Energy Systems Modelling, in order to minimize not only climate change impacts, but human health and ecosystem quality. In addition, a dual spatial resolution was integrated in the model in order to increase data precision and computational efficiency. The results show that a low-carbon energy system, based on the optimization of GHG emissions allows to greatly reduce all the environmental impacts under analysis, compared to an all economic- based energy system, but a multi-objective optimization allows to simultaneously reduce impacts on ecosystem quality and human health, while reducing GHG emissions and keeping good economical and technical performances. The results also show that it is theoretically possible for Canada to keep on track with their emission reduction ambition by 2030, by deploying more renewable energies. This project does not allow assessing Canada’s potential to reach net-zero emissions, as environmental impacts from carbon capture technologies are still to be characterized and integrated in the model.