William O'Brien

The relationship between net energy use and the urban density of solar buildings

There is a paradoxical relationship between the density of solar housing and net household energy use. The amount of solar energy available per person decreases as density increases. At the same time, transportation energy, and to some extent, household operating energy decreases. Thus, an interesting question is posed: how does net energy use vary with housing density? This study attempts to provide insight into this question by examining three housing forms: low-density detached homes, medium-density townhouses, and high-density high-rise apartments in Toronto. The three major quantities of energy that are summed for each are building operational energy use, solar energy availability, and personal transportation energy use. Solar energy availability is determined on the basis of an effective annual collector efficiency. The results show that under the base case in which solar panels are applied to conventional homes, the high-density development uses one-third less energy than the low-density one. Improving the efficiency of the homes results in a similar trend. Only when the personal vehicle fleet or solar collectors are made to be extremely efficient does the trend reverse—the low-density development results in lower net energy.

Coupling stochastic occupant models to building performance simulation using the discrete event system specification formalism

When applying occupant models to building performance simulation (BPS), it is common practice to use a discrete-time approach requiring fixed time steps. Consequently, a simulated occupants decisions do not increase in frequency in response to rapid changes in environmental conditions. Furthermore, as illustrated in this study through the analysis of a discrete-time EnergyPlus simulation, changing the time step between simulation runs may have a dramatic effect on BPS predictions. It is therefore necessary to adhere to a prescribed time step, which may complicate the synchronization of events when models of different domains are coupled. The main contribution of this study is an investigation of the viability of employing the discrete event system specification (DEVS) formalism to represent occupant behaviour without fixed and prescribed time steps. Results indicate that using an adaptive time advancement scheme, the DEVS formalism permits realistic patterns of decision-making while facilitating the coupling of stochastic occupant models with thermal and heating, ventilation and air-conditioning models.

Implementation and comparison of existing occupant behaviour models in EnergyPlus

To incorporate occupant behaviour in building performance simulation (BPS), researchers have developed a number of occupant behaviour and presence models based on long-term field observations. This paper describes the implementation of models from the literature for predicting occupancy and use of operable windows, blinds, lighting, and clothing for offices in the BPS tool EnergyPlus. In order to make the occupant models from the literature more widely available to researchers and practitioners, the EnergyPlus energy management system scripts are made publicly available. The paper then presents a comparison of the model predictions based on a typical office and demonstrates how differences in these models influence BPS results. In general, the window, blinds, and lighting use model predictions vary significantly from model to another. Despite these significant variations, the BPS models with different occupant behaviour model combinations provided consistent load reduction predictions in response to design changes.

On adaptive occupant-learning window blind and lighting controls

Occupants have a significant impact upon building energy use, e.g. through the actuation of window blinds and switching off lights. Automation systems with fixed set points for controlling blinds and lights have been used in some applications as an attempt to mitigate the impact of occupant behaviour upon energy consumption. A conceptual framework of an alternative control method is presented, one in which the control system adapts control set points in real time to each occupants preferences. The potential of this hypothesis is demonstrated through a simulation-based study focused on a hypothetical south-facing office with existing empirical models that predict occupant behaviour regarding the control of window blinds and lights. The performance of a proposed adaptive automation system is simulated, one in which window-blind and lighting control set points are adapted in real time to learn the modelled occupant preferences using a Kalman filter. The performance of this alternative occupant-learning method of control is contrasted to that of two conventional control methods, one in which occupants have manual control over window blinds and lights, and the other that employs an automation system with fixed set points. The simulation results indicate that such an adaptive occupant-learning control method could lead to substantial energy savings.

Modeling, Design, and Optimization of Net-Zero Energy Buildings

Building energy design is currently going through a period of major changes. One key factor of this is the adoption of net-zero energy as a long term goal for new buildings in most developed countries. To achieve this goal a lot of research is needed to accumulate knowledge and to utilize it in practical applications. In this book, accomplished international experts present advanced modeling techniques as well as in-depth case studies in order to aid designers in optimally using simulation tools for net-zero energy building design. The strategies and technologies discussed in this book are, however, also applicable for the design of energy-plus buildings. This book was facilitated by International Energy Agencys Solar Heating and Cooling (SHC) Programs and the Energy in Buildings and Communities (EBC) Programs through the joint SHC Task 40/EBC Annex 52: Towards Net Zero Energy Solar Buildings R&D collaboration. After presenting the fundamental concepts, design strategies, and technologies required to achieve net-zero energy in buildings, the book discusses different design processes and tools to support the design of net-zero energy buildings (NZEBs). A substantial chapter reports on four diverse NZEBs that have been operating for at least two years. These case studies are extremely high quality because they all have high resolution measured data and the authors were intimately involved in all of them from conception to operating. By comparing the projections made using the respective design tools with the actual performance data, successful (and unsuccessful) design techniques and processes, design and simulation tools, and technologies are identified. Written by both academics and practitioners (building designers) and by North Americans as well as Europeans, this book provides a very broad perspective. It includes a detailed description of design processes and a list of appropriate tools for each design phase, plus methods for parametric analysis and mathematical optimization. It is a guideline for building designers that draws from both the profound theoretical background and the vast practical experience of the authors.

Thermal zoning and interzonal airflow in the design and simulation of solar houses: a sensitivity analysis

Many assumptions must be made about thermal zoning and interzonal airflow for modelling the performance of buildings. This is particularly important for solar homes, which are subjected to high levels of periodic solar heat gains in certain zones. The way in which these passive solar heat gains are distributed to other zones of a building has a significant effect on predicted energy performance, thermal comfort and optimal design selection. This article presents a comprehensive sensitivity analysis that quantifies the effect of thermal zoning and interzonal airflow on building performance, optimal south-facing glazing area, and thermal comfort. The effect of controlled shades to control unwanted solar gains is also explored. Results show that passive solar buildings, in particular, can benefit from increased air circulation with a forced air system because it allows solar gains to be redistributed and thus reduces direct gain zone overheating and total energy consumption.

International survey on current occupant modelling approaches in building performance simulation

It is not evident that practitioners have kept pace with latest research developments in building occupant behaviour modelling; nor are the attitudes of practitioners regarding occupant behaviour modelling well understood. In order to guide research and development efforts, researchers, policy-makers, and software developers require a better understanding of current practice and acceptance of occupant modelling. This paper provides results, analysis, and discussion of the results of a 36-question international survey on current occupant modelling practice and attitudes in building performance simulation. In total, 274 valid responses were collected from BPS users (practitioners, educators, and researchers) from 37 countries. The results indicate that most assumptions made about occupants vary widely and are considerably simpler than what has been observed in reality. Most participants cited lack of time or understanding as their primary reason for not delving deeply into occupant modelling, but responded that they are receptive to further training.

Model-based predictive control of office window shades

In the automation of interior window shading devices, a control system that relies on a prediction of environmental conditions and a buildings thermal response can provide savings to space-conditioning loads beyond what can be achieved using a reactive approach. The development of these control strategies can be difficult because of the uniqueness of each building. A simplified model-based predictive control (MPC) method for window shades is proposed. To this end, a control-oriented model representing the heat transfer problem in a perimeter office space was developed. The parameters of the model were estimated using the ensemble Kalman filter (EnKF). The energy-savings potential of the EnKF-based MPC approach for window shades was investigated using EnergyPlus simulations. This was accomplished by implementing the control-oriented model into the energy management system application of EnergyPlus. Simulations were conducted to assess the energy saving potential of using the EnKF-based MPC for roller blinds in a south-facing perimeter office space in Ottawa, Canada. The simulation-based results indicate the potential for about 35% reduction in electricity usage for space conditioning over manually operated interior roller blinds.

Development and implementation of a thermostat learning algorithm

In the current article, the thermostat keypress actions with concurrent occupancy, temperature, and relative humidity data in private office spaces were analyzed. The authors observed that the occupants interact with their thermostats infrequently (on average once every 56 h of occupancy); and when they did so, occupants changed the temperature set-point, on average, by 1°C. The authors observed that about one-third of the thermostat overrides were either to decrease the set-points during the heating season, or to increase the set-points during the cooling season. The temperatures leading to the thermostat overrides changed by ∼3°C seasonally. It was noted that the frequency of thermostat interactions can be approximated as a univariate logistic regression model that inputs the indoor temperature as the predictor variable. A recursive algorithm was formulated to develop univariate thermostat use models inside building controllers. It was implemented inside four commercial controllers serving seven private office spaces to choose operating set-points. One year after the implementation, the iterative learning process resulted in a 2°C–3°C reduction in the set-points during the heating season and a 2°C–3°C increase in the set-points during the cooling season with respect to the default 22°C set-point in both seasons.

A method to generate design-sensitive occupant-related schedules for building performance simulations

Despite the purported benefits of occupant behavior (OB) models in simulating the effect of design factors on OB and vice versa, there are challenges associated with their use in building simulation practice due to the additional time and computational requirements. To this end, this article presents a method to incorporate these models in building performance simulations (BPS) as design-sensitive schedules. As an example demonstrating this method, more than 2,900 design alternatives of an office were generated by varying orientation, window to wall ratio (WWR), the optical characteristics of windows and blinds, and indoor surface reflectances. By using daylight simulations and stochastic OB modeling, unique light use schedules were generated for each design alternative. Two data-mining algorithms were then examined to identify the relationship between light use schedules and design parameters. Results indicated that WWR and building orientation had the strongest effect on light use schedules. These findings are relevant for building energy codes, as they provide an intermediate approach to incorporating design-sensitive schedules as BPS inputs. These design-sensitive schedules are expected to be superior to default ones currently specified in codes and standards, which ignore the effect of design factors on OB, and ultimately on energy consumption.