Performance-Risk Analysis For the Design of High-Performance Affordable Homes
Net-zero energy, emissions, and carbon sustainability targets for buildings are becoming achievable with the use of renewable energy technologies and high-performance construction, equipment, and appliances. Methodologies and tools have also been developed and tested to help design teams search for viable strategies for net-zero buildings during the early stages of design. However, the risks for underperformance of high-performance technologies, systems, and whole buildings are usually not assessed methodically. The negative consequences have been, often reluctantly, reported. This paper presents a methodology for explicitly considering and assessing underperformance risks during the design of high-performance buildings.
The methodology is a first attempt to formalize extensive applied research and industry experiences in the quest for net-zero energy homes in the U.S., and build on existing tools and methods from performance-based design, as well as optimization, decision, and risk analysis. The methodology is knowledge driven and iterative in order to facilitate new knowledge acquired to be incorporated in the decision making. As a point of departure in the process, a clear definition of the project vision and a two-level organization of the corresponding building function performance objectives are laid out, with objectives further elaborated into high-performance targets and viable alternatives selected from the knowledge-base to meet these. Then, a knowledge guided search for optimized design strategies to meet the performance targets takes place, followed by a selection of optimized strategies to meet the objectives and the identification of associated risks from the knowledge-base. These risks are then evaluated, leading either to mitigation strategies or to changing targets and alternatives, and feeding back to the knowledge-base.
A case study of affordable homes in hot humid climate is used to test the methodology and demonstrate its application. The case study clearly illustrates the advantages of using the methodology to minimize under performance risks. Further work will follow to develop the underpinning mathematical formalisms of the knowledge base and the risk evaluation procedure.