SCALABLE METHODOLOGY FOR ENERGY EFFICIENCY RETROFIT DECISION ANALYSIS
Yeonsook Heo, Fei Zhao, Sang Hoon Lee, Yuming Sun, Jinsol Kim, Godfried Augenbroe, Diane Graziano, Leah B. Guzowski, Ralph T. Muehleisen
This paper introduces a scalable methodology that supports energy retrofit decision-making at two levels. The methodology is based on normative energy models to provide objective and transparent benchmarking and assessment. The aggregate-level analysis evaluates the effectiveness of policy and business plans on energy savings by benchmarking the energy performance of a collection of buildings and projecting the effects of different retrofit scenarios over time. The individual- level analysis supports risk-conscious decision-making for building stakeholders by providing explicit information about the energy performance risks associated with specific retrofit alternatives. This paper describes model results for a small set of commercial buildings in the Chicago Loop and findings relevant to the method’s application.
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