Modelling the Urban Microclimate and its Influence on Building Energy Demands of an Urban Neighbourhood

In the past decades the portion of the population living in urban areas has continuously increased. Due to the high building density, the microclimate in urban areas changed significantly compared to rural areas. The temperatures measured in urban areas are, due to the urban heat island (UHI) effect, higher compared to the rural temperatures. The UHI intensities are increasing with higher building densities and growing cities. Space cooling and heating demands of buildings are strongly affected by the local microclimate at the building sites. Due to the climate change and the limited energy resources, energy saving and sustainability are nowadays important issues. A significant part of the global energy consumption is used for space cooling and space heating of buildings. Thus its minimization for buildings in urban areas has great energy saving potential. Most building energy simulation (BES) models were developed for stand-alone buildings and therefore do not consider effects of the urban microclimate. This can lead to inaccurate predictions of the space cooling and heating demands for buildings in urban areas. The aim of this paper is to investigate the urban microclimate and its potential influence on the energy demand of buildings in an urban context by conducting detailed flow, radiation and building energy simulations at the urban neighborhood scale. CitySim is used for the radiation and building energy simulations. In CitySim detailed radiation models for solar and longwave radiation are implemented that can account for the radiation exchange between neighbouring buildings. The flow around the buildings is modelled by running CFD (computational fluid dynamics) simulations using OpenFOAM. As a result it is shown, how the temperatures and wind speeds can strongly differ within different urban areas. Further an approach is presented, to consider the local microclimate in the building energy simulation tool CitySim.

Novel models towards predictive control of advanced building systems and occupant comfort in buildings

Nikolaos Zarkadis

People in developed countries spend today most of their time inside buildings as part of the modern way of life. As a result, the building sector accounts for almost 40% of the total energy consumption and a big part of the energy bill goes to maintain the visual and thermal comfort of their occupants. At the same time, awareness is being raised during the last decades about the greenhouse gas emissions and the possibly irreversible effects of global warming; both linked to excessive use of non-renewable primary energy sources which still power most of the world, including our buildings. Thus, moderating the energy consumed in them is a top priority. However, this does not imply a horizontal cut in energy consumption that would result in a drop of user comfort. Instead, we suggest that improving energy efficiency in buildings while maintaining or even improving the user comfort is the optimal solution. It is indeed the core of this thesis that there is a great energy saving potential in refining the control of building systems such as electric lighting, heating, cooling and ventilation, which more than often consume a lot of energy without delivering the analogous amount of visual and thermal comfort. In this direction, this thesis proposes the development of a novel predictive control algorithm for the control of electrochromic glazing using a low cost sky scanner using a simple web camera. The developed algorithm demonstrated an average prediction accuracy of 92% and integrates and controls the blinds and electric lighting to maximise visual comfort taking into account outdoor and indoor conditions, presence and user actions. Measurements and extensive simulations showed that the elaborated algorithm improves thermal and visual comfort when compared to standard glazing coupled with blinds and exhibits acceptable levels of energy consumption for space heating and electric lighting. In the same subject of improving building control, a novel approach for controlling building systems by using state-based stochastic data-driven models to identify "season" is defined and developed. We reason that the season variable is unique to every building and it depends on weather conditions, user behaviour and building construction. The developed models identified "season" with an accuracy that ranged from 69 to 91% and it was shown through simulations that a controller based on Hidden Markov Models can reduce energy demand for heating and improve the thermal comfort of occupants in different building construction types. Finally, the use of Hidden Markov Models was further explored in this thesis by suggesting a novel model for the estimation of occupants' visual comfort in buildings. The proposed model is based on horizontal workplane illuminance measurements using ceiling-mounted sensors as well on vertical illuminance monitoring at the observer's eyes plane (pupillary illuminance) by means of wearable portable sensors. We argue that the proposed model improves greatly over the various existing discomfort glare indices and metrics and it is also convincingly demonstrated that it can be seamlessly integrated and used in building automation systems based on fuzzy logic.

EPFL2015

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

Advanced Control of Electrochromic Windows

Nicolas Morel, Nikolaos Zarkadis

In our research we use the technology of electrochromic (EC) glazing to maximize the use of daylight and minimize the energy consumption in buildings while preserving visual and thermal comfort of the users. We propose an advanced automatic control of EC windows coupled with an anidolic daylighting system (ADS), blinds and dimmable fluorescent lights. EC windows with a visible transmittance range (Tv) of 0.15 – 0.50 were installed on the southern façade of an office room of the LESO experimental building (EPFL campus in Lausanne, Switzerland). The system is divided in two independent zones: The lower zone is equipped with EC windows and blinds while the upper zone features in addition the ADS, which facilitates the even distribution of daylight across the room. Electric lighting is used only complementary when daylight is not sufficient. Data regarding instantaneous weather conditions, room conditions, as well as user wishes is collected and recorded in the database of the building's central management system (KNX/EIB). To address visual comfort requirements, a novel sky-scanner approach is implemented into a predictive control strategy to take into account the time the EC glazing requires to switch between different transmission states (up to 15 minutes). For the thermal comfort, we consider a wider time horizon, taking under consideration also the time, day and season. User has always the possibility of manually overriding the automatic control system. Adaptive fuzzy logic algorithms are implemented allowing the system to learn from users' wishes. Simulations showed that the elaborated algorithms for the automatic control of EC windows can provide better thermal and visual comfort conditions when compared to standard glazing coupled with blinds and still exhibit acceptable levels of energy consumption for space heating and electric lighting. Field study results showed that workplane illuminances were mostly kept inside acceptable visual comfort levels (at around 450-1000 lx). Field survey results regarding the acceptance of the system by the users are also presented along with a discussion on the efficacy of an EC windows system to handle glare issues without the use of blinds.

EPFL Solar Energy and Building Physics Laboratory (LESO-PB)2013