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Bush, Brian W.

Publications and source records attributed to Bush, Brian W..

Future integrated mobility-energy systems: A modeling perspective

After over a century of petroleum dominance, the transportation sector is on the verge of radical transformations driven by rapid technology advancement of alternative fuels, automation, information technologies that create new mobility options and business models, and policies at all levels of government. While the technologies and fuels that will move people and goods in the future remain uncertain, the future transportation system will be more integrated with smart buildings, the electric grid, renewables, and information ecosystems, allowing for great opportunities to exploit these interconnections. Modeling tools for analyzing integrated mobility-energy systems require a deep understanding of these interconnections, of the infrastructure required to support alternative fuel vehicles, and a more nuanced understanding of transportation energy needs across multiple segments and spatiotemporal scales. In this paper, we assess the landscape of existing tools used to represent and model future mobility systems and their interactions with other energy systems. Here, we conclude that (a) out-of-sample extrapolation of emerging trends and future anticipated developments is more important than ever due to the plethora of factors driving disruptive change in mobility systems; (b) understanding adoption opportunities for alternative fuel light-duty vehicles requires modeling intra-household decisions affecting travel demand and mode choice; (c) mobility and energy systems need to be modeled as an integrated continuum, breaking the traditional approach in which dynamic energy supply models use relatively simple transportation demand and vice-versa; and (d) increased spatiotemporal fidelity and scalability are required to dynamically couple transportation/mobility and energy supply models and capitalize on these unprecedented interconnection opportunities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Enabling immersive engagement in energy system models with deep learning

Complex ensembles of energy simulation models have become crucial components of renewable energy research in recent years. Often the increasing computational cost, high-dimensional structure, and other complexities hinder researchers from fully utilizing these data sources for knowledge building. Researchers at National Renewable Energy Laboratory have determined an immersive visualization workflow to dramatically improve user engagement and analysis capability through a combination of low-dimensional structure analysis, deep learning, and custom visualization methods. We present case studies for two energy simulation platforms.

97 MATHEMATICS AND COMPUTING↗

Scenario Evaluation and Regionalization Analysis (SERA) Model: Demand Side and Refueling Infrastructure Buildout

The National Renewable Energy Laboratory's Scenario Evaluation and Regionalization Analysis (SERA) model estimates the number, size, and locations of hydrogen refueling stations that satisfy the fuel demand from fuel cell electric vehicles (FCEVs) and the hydrogen supply requirements to meet such a demand in terms of hydrogen production plants and delivery infrastructure. SERA simulates the systemwide cost-optimal evolution of hydrogen refueling infrastructure, providing insights that reduce the informational and financial risks associated with infrastructure investment decisions and helping accelerate the adoption of FCEVs. This report describes the SERA model's demand-side and refueling infrastructure buildout algorithms, and it also illustrates use of the model for simulating hydrogen refueling stations deployment scenarios using as an example the recent H2USA national hydrogen infrastructure report.

30 DIRECT ENERGY CONVERSION↗