The Joy of Stochastic Forecasting: An Overview of the Stochastic Buildings Energy and Adoption Model

February 14, 2011 - 3:00pm
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One of the key challenges in developing useful, far reaching forecast models is addressing uncertainty, notably regarding the achievement of technology development goals (i.e. cost and performance targets). This is the motivation behind the Stochastic Buildings Energy and Adoption Model (SBEAM), developed at LBNL as part of the Stochastic Energy Deployment System (SEDS). SBEAM is a DOE developed energy use forecast model explicitly written to incorporate uncertainty into its calculations. This talk will focus on the value of employing uncertainty and the platform used to develop stochastic models, Analytica®. The structure, methodology and data gathering process of SEDS will also be presented. Finally, the usefulness of the model will be demonstrated with a stochastic analysis of the market penetration of important emerging buildings technologies. The model is of potential value to researchers, both as a management tool and as a source of benefits estimates required as support to proposals. BIOS: Chris Marnay is a Staff Scientist in the Technology Evaluation, Modeling, and Assessment group within the Environmental Energy Technologies Division of Berkeley Lab. He models problems related to likely future adoption patterns of small-scale distributed energy resources, especially when clustered with loads in locally controlled buildings scale microgrids. He also leads forecasting work using the National Energy Modeling System (NEMS) and the Stochastic Energy Deployment System (SEDS). He has an A.B. in Development Studies, an M.S. in Agricultural and Resource Economics, and a Ph.D. in Energy and Resources, all from the University of California, Berkeley. Michael Stadler is a Research Scientist at Berkeley Lab, California, USA. He studied at the Vienna University of Technology, from which he holds a Masters degree in electrical engineering and a Ph.D. summa cum laude in energy economics. In addition, he supported the University of California, Berkeley’s Pacific Region combined heat and power (CHP) Application Center, where he conducted site analyses of varied commercial, agricultural, and industrial CHP projects. So far, he contributed to more than 110 scientific publications, reports, and software tools in his nine-year career. He currently works on DER and storage modeling for the Distributed Energy Resources Costumer Adoption Model (DER-CAM) design as well as on stochastic building simulation for the SEDS project. Nicholas DeForest is a Senior Research Associate at LBNL. He is primarily responsible for development work of SBEAM. He also works as part of the DER-CAM development team. He received a M.S. in mechanical engineering from UC Berkeley.

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