Modeling energy systems using large data sets
Date
2024
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Abstract
Modeling and simulation are playing an increasingly import role in the sciences, and science is having a broader impact on policy definition at a local, national, and global scale. It is therefore important that simulations which impact policy produce high-quality results. The veracity of these models depend on many factors, including the quality of input data, the verification process for the simulations, and how result data are transformed into conclusions. Input data often comes from multiple sources and it is difficult to create a single, verified data set. This dissertation describes the challenges in creating a research-quality, verified and aggregated data set. It then offers solutions to these challenges, then illustrates the process using three case studies of published modeling and simulation results from different application domains.
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Subject
large data
science informed policy
modelling
energy simulation