An Integrated Process Model and Decision Support System for Energy Efficient Retrofits

摘要

The importance of the built environment in tackling current energy and sustainability challenges is widely recognized. There is significant value in retrofitting existing buildings. Owners, project managers, designers, and contractors now actively seek opportunities to upgrade the energy performance of standing buildings. These prospects lie in the retrofit process, within which many collaborative decisions take place at critical stages. The procedure is currently inefficient, with decision makers unaware early in the process of the ultimate implications of their actions on the energy-efficiency outcomes of the building they are creating. Thus, there is substantial room for a decision support system (DSS) that can guide facility owners and project managers in undertaking advanced energy retrofits of existing buildings by considering effects of decisions on energy performance.;Approaches that support decision-making prediction in energy performance include checklists, databases, and forward and inverse modeling. We know that integrated system upgrades result in more significant energy reduction rates than do standard approaches. Because all team members do not inform these synergies early in the process, however, energy-efficient decisions do not occur. In a typical energy-efficient retrofit design, decisions are entered into simulations without collaboration to document them and predict the design's energy performance. Such late evaluations cannot go beyond the projection of energy performance that is already selected for the design. Thus, there is a need for a decision-support system that stimulates both the collaborative design process and early decision-making on system performance information.;The research methodology consisted of a literature review on critical design activities and energy conservation measures (ECM) as the first stage, followed by interview design and testing the need statement with experts. Then we collected decision variables through involvement in case-study meetings and interviews with project participants. For the process delineation, we mapped three "as is" process models to cross-case with recommendations from the literature, and delivered a "to be" process model. The refined "to be" process model we offer is also fed by the ECM measure that is tracked in case studies, project participant interviews, and project documents. To inform the design team lead by PMs, a simplified comparative energy-consumption prediction methodology is developed.;Consequently, this research creates a project management DSS to manage the deep-retrofit process during collaboration meetings and design charrettes. It aims to improve the integrated design process by providing a just-in-time relative energy analysis compared to a standard baseline. This energy-efficiency prediction methodology is scalable to other project values such as IEQ or cost. The knowledge we add to the field combines process with critical ECM performance measures. The opportunity to have a comparative energy analysis of decisions early in the design process will also improve system option opportunities and present the ability to change them.