CAREER: Modeling for Insights with an Open Source Energy Economy Optimization Model

  • Decarolis, Joe J. (Investigador principal)

Detalles del proyecto

Descripción

This research has four main goals: (i) institute a transparent process for Energy Economy Optimization (EEO) model development and application, (ii) generate new insights into energy system development at the national and global scale through the rigorous application of uncertainty analysis, (iii) involve analysts, decision makers, and students in the modeling effort through participation in a joint cognitive process of discovery, and (iv) use EEO models as a tool to teach students ranging from high school to graduate school to think critically about energy systems and environmental sustainability from a systems perspective. This project aims to advance the field of energy modeling by developing a new open source framework that includes Tools for Energy Model Optimization and Analysis (TEMOA). The TEMOA framework will be the first to include an EEO model whose source code and data are archived in a web-accessible repository, enabling anyone to verify results published in the literature. In addition, the TEMOA framework will include tools to enable model iteration in a parallel computing environment, which will dramatically improve the ability to conduct uncertainty analysis. Results will be disseminated directly to the energy modeling and operations research communities via conference presentations, published papers, and the collaborative relationships. In addition, the open source framework will be available to other researchers to modify and use for their own analysis. Results will also be integrated into educational activities ranging from high school to doctoral studies.

EstadoFinalizado
Fecha de inicio/Fecha fin15/1/1131/12/16

Financiación

  • National Science Foundation: USD400,795.00

!!!ASJC Scopus Subject Areas

  • Estadística, probabilidad e incerteza
  • Química (todo)
  • Bioingeniería
  • Ciencias ambientales (todo)
  • Ingeniería (todo)

Huella digital

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