Persistent Workplace Energy Savings and Awareness through Intelligent Dashboards: Monitoring, Advice, Comparison, Control and Automation

Commercial buildings consume at least 18% of the total electrical energy used in the United States. Over 2.8 billion dollars are wasted every year due to computers being left on during the night and weekend. Yet up to 40% of the plug-load energy consumption can be reduced by behavior change. In the field of Human Computer Interaction (HCI), recent intervention studies have identified that monitoring and controls can motivate more environmentally-focused behavior in residences, where the occupants also have a financial interest. These studies, however, have not adequately addressed behavior in office environments, neither been thoroughly quantified for impact nor fully explored control strategies. This dissertation addresses these limitations through the development of an Intelligent Dashboard for Occupants (ID-O) that provides diverse feedback (selfmonitoring, advice, comparison) and control (remote and automated control) features. With an ID-O, through a variety of interventions, one can explore 1) energy conservation, 2) energy awareness, and 3) persistent energy savings. Three intervention strategies are considered in this dissertation in the following order: • Feedback; • Feedback and on-line control; • Feedback, on-line control and automated control The first two give rise to the following expectation, namely, that there is an increase in energy conservation, energy awareness and persistent energy savings, even after the intervention has been removed. The third strategy suggests that it will (relatively) provide the greatest increase in energy conservation with a (relative) reduction in energy awareness and persistent energy savings, after the intervention has been removed. These then are the hypotheses that underlie this dissertation. To thoroughly investigate the effectiveness of feedback and control interfaces, the ID-O dashboards were deployed in a large office building over a period of nine months. Eighty employees were recruited and their baseline data was collected for fourteen weeks. With four groups of 20 employees, three different configurations were tested alongside one control group – one with only feedback (self-monitoring, advice, and comparison), one with feedback and on-line control, and one with feedback, on-line and automated control. The dashboards were in place for thirteen weeks, and then removed for eleven weeks, allowing for measurements of user electricity consumption before, during and after the availability of an Intelligent Dashboard. During the interventions, the more features that were offered, the greater savings that were achieved. After the interventions were removed, all dashboard groups persistently saved energy with only a slight decrease in savings. Surveys were conducted at the end of the pre, during and post interventions. Between the during- and post-interventions, the biggest awareness increase was found for the group with only feedback and the group with feedback and on-line control. A relatively low increase was measured for the group with feedback, on-line and automated control. The following results were demonstrated: • Provision of feedback (self-monitoring, advice, and comparison) through energy dashboards increases 1) energy conservation, 2) energy awareness, and 3) persistent energy savings, even after the intervention has been removed. • Introduction of feedback and on-line controls have greater 1) energy conservation, 2) energy awareness and 3) persistent energy savings, even after the intervention is removed. • Added intervention by automated calendar controls demonstrated the highest energy savings, after the interventions had been removed. As expected, there is reduced energy awareness, but not reduced persistent energy savings. Beyond its main contribution on energy conservation, awareness and persistent savings, this dissertation contributes to the increasing field study literature on HCI interface choices specifically focused on energy and behavioral impacts. It also adds to the expanding breadth of existing HCI intervention studies in office environments with greater participant numbers over a longer duration; and provides quantified energy savings from technology-specific plug load management in offices through behavioral change.