Past Research Projects

Understanding and Modeling the Impact of Occupant Energy Usage Characteristics in Buildings: There are several challenges and market barriers to fully integrating new energy efficient technologies in the commercial building sector. Among these several barriers, addressing the occupant behavior challenge will provide opportunities to conserve energy in the short term while new technologies are being researched and developed to be fully integrated in existing and new building systems. Thus, the objective of this research is to understand and model the effect of the difference in occupant energy use characteristics on the total energy consumption in commercial buildings. To achieve this objective, data is being collected from public databases, real time monitoring of buildings, and surveys to different building and occupant groups. The results are being used to develop and validate an agent based model (ABM) that simulates occupant energy use characteristics in commercial buildings. This research will result in fundamental contributions related to advancing the knowledge, understanding and modeling of occupant energy use characteristics for choosing and designing sustainable building systems. First this research explores a major problem facing building decision makers, and that is how to reconcile predicted and actual energy consumption in buildings by studying the effect of differences in occupant energy use characteristics. This approach will result in more accurate estimates of building performance by using the developed ABM to simulate occupants’ energy use characteristics, schedule; as well as, their location in the building at any given time during the day; and generate a list of equipment they are using to achieve reliable energy consumption estimates. Another important aspect of this model is the feedback during the building operation phase that will allow the decision maker to test energy conservation opportunities, and determine which of these will result in greatest and fastest influence on the occupants to change their energy use habits.

Integrated Social, Environmental, Economic, and Technical (SEET) Model for Sustainable Retrofit of Existing Buildings: Existing non-residential building stock is a key target for energy efficient interventions to substantially reduce adverse impacts on the environment, human health and the economy. However, the decision to sustainably retrofit existing buildings has become extremely complex given the conflicting objectives of the building stakeholders, and uncertainty about the expected economic and environmental benefits of the proposed retrofits. An integrated modeling approach that captures these complexities will allow for a better understanding of the sustainable building retrofit process, and provide a framework to efficiently and effectively retrofit most of the nation’s deteriorating infrastructure. In this research, I am developing and testing an agent based simulation framework (SEET) to enhance and support the sustainable retrofit of existing buildings. The SEET framework will integrate the building stakeholders’ requirements and behaviors (Social), the budget constraints (Economic), the required energy savings and carbon footprint reduction benchmarks (Environmental), and available range of possible retrofit measures (Technical) to simulate their complex interactions. Thus, the three main research objectives are to: (1) understand how the requirements of the different building stakeholders affect the sustainable retrofit decision; (2) determine to what extent does information related to environmental impact, economic constraints, and technical feasibility influence the requirements of the building stakeholders; and (3) establish how to model these requirements and influences using agent based modeling techniques (ABMT). The proposed research will result in several contributions to the area of decision making to sustainably retrofit existing buildings. The new modeling methodology enables the integration of social aspects with environmental, economic and technical aspects of sustainable building retrofits. ABMT provides computational capabilities to consider the social and behavioral aspects of sustainable building retrofit management, and can be applied to enable more effective design decisions to sustainably retrofit existing buildings and reduce their environmental impact. The modeling framework that will be developed in this research will provide the basis for future extension to comprise a larger number of buildings representing city blocks and communities, to implement more sophisticated adaptive agents that identify optimal rules for sustainable retrofits of urban areas.