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Historically, detailed building energy simulation programs have been used to either perform heating and cooling load calculat ions for HVAC equipment sizing purposes or to predict the whole building annual energy usage for evaluating a particular design. Based on user inputs that describe the building and imported weather data, these software programs simulate the hourly building performance over the course of a year, and provide outputs such as energy consumption by end use, demand, utility costs, etc. In this conventional approach, the building design parameters are essentially fixed by the user before the simulation is performed. Therefore, the standard practice is to use these programs for design analysis rather than design synthesis. The intent of the automated design methodology concept proposed in this paper is to use detailed building energy simulation programs in a different manner. Due to design constraints, aesthetic issues, program restrictions, or specific owner requirements, the optimal design may not be always desired. More valuable to the designer than determining the optimum is knowing the "latitude" s/he has in changing certain design variables while maintaining pre-selected desired performance criteria. The goal of the automated design methodology is thus to provide designers with a decision support tool rather than an optimization tool, i.e., a manner of generating numerous (in the hundreds) design alternatives which meet pre-stipulated performance criteria from which the designer can make the final selection for a particular project. Implementing such a methodology early in the design process will provide building professionals with a much larger solution set of possible designs options (which may not have been selected from intuition and experience alone). This paper describes the concept of automated design, lays the foundation for building such a methodology, and provides an illustrative example which begins to explore one possible approach of practically implementing the automated design approach. [ABSTRACT FROM AUTHOR]

This paper proposes a methodology to calibrate multi-zone airflow models in existing buildings. The methodology has been demonstrated with the widely used multi-zone model CONTAM and applied to two buildings, one synthetic and one actual. The methodology builds on previous work with the calibration process enhanced by the use of carbon dioxide tracer gas test data. A key concept highlighted in this paper is that calibration of airflow models is a highly over-parameterized problem and that some form of model reduction is imperative. This is achieved by performing an airflow-based sensitivity analysis to identify influential system drivers, a tracer gas-based sensitivity analysis to identify macro-zones (i.e. groups of rooms that can be combined into one zone for the purposes of predicting or studying dynamic airflow behavior under different types of stimuli), and finally, a process of tuning the model parameters. It is found that for mechanically ventilated commercial buildings, calibrating multi-zone models by reconciling differences between measured and predicted tracer gas behavior is more strongly impacted by those factors which significantly influence room air change rates than by airflow path leakage parameter tuning. [ABSTRACT FROM AUTHOR]

In general, U.S. municipal and state benchmarking and disclosure programs have proven effective in encouraging the development of a strong market for building energy efficiency. Available data for select cities in the United States shows that energy savings per unit of floor space for these programs range between 6% and 8% over a two-year period (Pan et al. 2016, 10). Despite the merit of these programs, however, several shortcomings have been identified, including the need for: (1) more efficient and cost-effective assessment of buildings for retrofit opportunities, and (2) greater standardization and automation of the benchmarking and disclosure processes. To address these shortcomings, Lawrence Berkeley National Laboratory, Johnson Controls, and ICF International are developing a free, on-line, open-source, building energy efficiency upgrade targeting tool. The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Inverse Modeling Toolkit (IMT), and Johnson Controls' LEAN Energy Analysis, serve as the technical basis for the tool, which will automatically regress monthly energy usage versus ambient temperature; compare model coefficients to quantify energy and cost-savings potential; and analyze model coefficients to identify energy conservation measures (operational or equipment) for a single building or portfolio. The tool is unique in its open-source, modular, online, and 100% automated format. The source code will be published on GitHub and thus available for use and modification by the buildings community. This paper discusses: (1) the market's need for the tool; (2) the tool's analytic methodology, based on a combination of ASHRAE's IMT and LEAN Energy Analysis; (3) tool innovations with industry impact, including a fully automated approach for building change-point selection; (4) and the outcomes of early pilot applications of the tool among 36 hotel buildings. Future work and potential applications are also discussed. [ABSTRACT FROM AUTHOR]