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Open Access Publications from the University of California
Cover page of Coordinate control of air movement for optimal thermal comfort

Coordinate control of air movement for optimal thermal comfort


Personally controlled air movement can maintain or enhance thermal comfort in warm environments and reduce energy consumption. Unlike controlling a personal fan, using a system of fans for multiple occupants is difficult as it is hard to find an appropriate fan speed setting that maximizes occupants’ satisfaction. Since limited work has been carried out on this issue, in this paper, a novel cooperative control approach for a system of fans is proposed to provide optimized air movement for multiple occupants. This is the first time that a system of fans is controlled cooperatively in the research of built environment. The proposed approach predicts airflow in a cost-effective manner by calibrating the fans in the real environment. The operation of the fans is optimized by minimizing the worst-case deviation between the actual air speed and the desired air speed, which can be determined based on either the PMV – SET model or the occupants’ feedback. This minimax-error problem is formulated as an equivalent linear programming problem which can be solved using standard methods. The proposed approach was tested in two different indoor scenarios respectively by 1) measuring air speed directly in a business conference room and 2) involving human subject surveys in a university classroom. In the first experiment, the measured air speeds after optimization are closer to the target values at all tested temperature levels (26 °C, 27.5 °C and 29 °C) indicating improved thermal comfort. In the second experiment, only 62% of the occupants (totally 34) are satisfied with slightly increased room temperature (around 26.5 °C) before optimization, while this number increased to 94% after optimization.

Cover page of Performance analysis of pulsed flow control method for radiant slab system

Performance analysis of pulsed flow control method for radiant slab system


We present a novel pulsed flow control method (PFM) using a two-position valve to regulate the capacity of radiant slab systems. Under PFM, the on-time duration of the valve is short (compared to all prior work, e.g. 4-minute), and fixed, while the off-time varies. We present a novel, open-source, finite difference model that assesses three-dimensional transient slab heat transfer, accounting for the transient heat storage of the pipe fluid. Sensitivity analysis results indicate the dominant factors influencing energy performance of the PFM are: on-time duration; pipe diameter; and spacing. We experimentally validated both the new control strategy and model in full-scale laboratory experiments. Compared with previous intermittent control strategies (with on-time durations over 30 min), at 50% part load the PFM reduces 27% required water flow rate and increases supply to return water temperature differential. Compared with the variable temperature control method, at 50% part load the PFM reduces 24% required water flow rate. The energy performance of PFM is comparable to that of a conventional variable flow rate control. However, it has more accurate capacity control, achieves a more uniform surface temperature distribution, and reduces initial investment by substituting two-position for modulating valves, thus showing promise for engineering applications.

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Cover page of Machine learning approaches to predict thermal demands using skin temperatures: Steady-state conditions

Machine learning approaches to predict thermal demands using skin temperatures: Steady-state conditions


Inefficient controlling strategies in heating and cooling systems have given rise to a large amount of energy waste and to widespread complaints about the thermal environment in buildings. An intelligentcontrol method based on a support vector machine (SVM) classifier is proposed in this paper. Skin temperatures are the only inputs to the model and have shown attractive prediction power in recognizingsteady state thermal demands. Data were accumulated from two studies to consider potential use for either individuals or a group of occupants. Using a single skin temperature correctly predicts 80% ofthermal demands. Using combined skin temperatures from different body segments can improve the model to over 90% accuracy. Results show that three skin locations contained enough information forclassification and more would cause the curse of dimensionality. Models using different skin temperatures were compared. Optimal parameters for each model were provided using grid search technique. Considering the overfitting possibility and the cases without learning processes, SVM classifiers with a linear kernel are preferred over Gaussian kernel ones.

Cover page of Building operating systems services: An architecture for programmable buildings.

Building operating systems services: An architecture for programmable buildings.


Commercial buildings use 73% of all electricity consumed in the United States [30], and numerous studies suggest that there is a significant unrealized opportunity for savings [69, 72, 81]. One of the many reasons this problem persists in the face of financial incentives is that owners and operators have very poor visibility into the operation of their buildings. Making changes to operations often requires expensive consultants, and the technological capacity for change is unnecessarily limited. Our thesis is that some of these issues are not simply failures of incentives and organization but failures of technology and imagination: with a better software framework, many aspects of building operation would be improved by innovative software applications.

To evaluate this hypothesis, we develop an architecture for implementing building applications in a flexible and portable way, called the Building Operating System Services. BOSS allows software to reliability and portably collect, process, and act on the large volumes of data present in a large building. The minimal elements of this architecture are hardware abstraction, data management and processing, and control design; in this thesis we present a detailed design study for each of these components and consider various tradeoffs and findings. Unlike previous systems, we directly tackle the challenges of opening the building control stack at each level, providing interfaces for programming and extensibility while considering properties like scale and fault-tolerance.

Our contributions consist of a principled factoring of functionality onto an architecture which permits the type of application we are interested in, and the implementation and evaluation of the three key components. This work has included significant real-world experience, collecting over 45,000 streams of data from a large variety of instrumentation sources in multiple buildings, and taking direct control of several test buildings for a period of time. We evaluate our approach using focused benchmarks and case studies on individual architectural components, and holistically by looking at applications built using the framework.

Cover page of Evaluating a Social Media Application for Conserving Energy and Improving Operations in Commercial Buildings

Evaluating a Social Media Application for Conserving Energy and Improving Operations in Commercial Buildings


Compared to the wealth of studies on residential energy behavior, studies on the energy attitudes and behaviors of commercial building occupants have been few. However, occupants exert significant control and influence over energy use in commercial buildings, and it has been estimated that 20% to 50% of total building energy use is controlled or impacted by occupants. This study explores the potential for using a web-based social network to promote energy awareness and influence energy-conserving behavior in the workplace. The research team developed a social media application prototype and conducted usability testing with 128 subjects to understand the perspectives of typical office building occupants. The key findings presented are: 1) the influence of personalized energy information; (2) the influence of normative energy information; (3) the potential for sharing personal energy goals and energy data; (4) the effects of incentives such as self-selected goals or rewards, and (5) the implications of using social media for improving communications between building occupants and operators.Findings suggest that highly individualized energy information, at the level or individual workstations or offices, offers benefits for engaging and informing individuals about their energy use, and that the cost of energy is viewed as the most useful energy metric, a finding supported by previous research. Social aspects of sharing energy use information and personal energy goals were also viewed favorably by the usability test participants. Overall the study found considerable potential for using social media to engage commercial building occupants in energy conservation, and to improve communications between occupants and building management. The paper concludes with recommendations for the design of energy feedback systems including those with social media characteristics.

Cover page of Broken Information Feedback Loops Prevent Good Building Energy Performance—Integrated Technological and Sociological Fixes Are Needed

Broken Information Feedback Loops Prevent Good Building Energy Performance—Integrated Technological and Sociological Fixes Are Needed


Information feedback loops for building performance range from the long-term— including university education of building designers and their experiential learning from past work on a time scale of years or decades; to the short term—including building occupants seeking to manage their environment with operable windows and thermostats, to building controls themselves on a time scale of seconds or minutes. In between are owners seeking to make informed renovation and retrofit decisions on a time scale of years, and operators looking for ongoing commissioning opportunities on a time scale of hours to months.

Unfortunately all of these feedback loops are often broken, with meaningful convenient performance information typically unavailable for decision-making. Even automatic building controls often fail to perform as expected because of erroneous or missing data from sensors. We examine the current typical disconnects for each of the feedback loops, their interactions, and potential solutions. 

Both improved technology and organizational change are needed to fully establish all the feedback loops for building performance, achieving the twin goals of building quality (e.g., comfort) and reduced resource use (e.g., energy). Currently research sometimes provides an intervention to temporarily close one or more of the feedback loops. However, closing of information feedback loops is often inhibited by perceptions of professional or business risk. Achieving the vision of ubiquitous deep efficiency for buildings will require research, development and demonstration integrating both technological and sociological issues to durably establish feedback at all time scales in building design and operation.

Cover page of Open Graphic Evaluative Frameworks

Open Graphic Evaluative Frameworks


Buildings are the world’s largest consumer of energy, accounting for 34% of total use. In the United States residential and commercial buildings are responsible for 72% of electricity useand40% of CO2 emissions. In order to reduce the impact of buildings on the environment and to utilize freely availableenvironmental resources, building design must be based on site climate conditions, e.g. solar radiation and air temperature. This paper presents a web-based framework that enables the production of user-generated visualizations of weather data. The Open Graphic Evaluative Framework (Open GEF) was developed using the Graphic Evaluative Frameworks (GEF) approach to authoring design-assistant software, which is more appropriate than the now dominant ‘generalized design tool' approach when supporting design processes that require a high level of calibration to the cyclic and acyclic shifting of environmental resources. Building on previous work that outlined the theoretical underpinnings and basic methodology of the GEF approach, technical specifications are presented here for the implementation of a Java driven web-based visualization platform. By enabling more nuanced and customizable views of weather data, the software offers designers an exploratory framework rather than a highly directed tool. Open GEF facilitates design processes more highly calibrated to climatic flows that could reduce the overall impact of buildings in the environment.