Browsing by Author "Gumerman, Etan"

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    Assessing the Outcomes of a Long-term, Zero-emission Strategy for GoTriangle’s Transit Fleet
    (2019-04-19) Floum, Jackson; Fu, Yingyu; Yoshizumi, Alexander; Zhang, Liyue
    The goal of this project was to assess how GoTriangle might most effectively implement battery electric vehicle (BEV) buses by analyzing possible environmental and social factors and providing recommendations for BEV bus implementation to maximize operating efficiency and social good. The core questions that drove the analyses were (1) whether GoTriangle is a good candidate for BEV bus implementation and (2) how GoTriangle might best implement BEV buses. Four analytical components were chosen to address the goals of the project based on participatory feedback from project clients: (1) analysis of potential grid impacts of charging the electric fleet, (2) comparisons between BEV bus well-to-wheel emissions and conventional diesel bus well-to-wheel emissions, (3) suitability analysis of route legs – the most granular transportation planning units used by GoTriangle, and (4) spatial analysis of emissions to address environmental health and environmental justice concerns. This report found that GoTriangle is likely a good candidate for BEV bus implementation. Increased demand to the grid would likely be negligible from a transmission point-of-view. In maximum fuel-economy scenarios with an energy mix based upon Duke Energy’s integrated resource plan, it appeared that BEV buses would contribute less emissions in every category when compared to diesel buses. Though, it should be said that comparatively larger contributions of some air pollutants were observed in minimum fuel-economy scenarios. Many bus route legs – the smallest planning units used in route optimization – appeared to be good candidates for implementation based on physical characteristics known to be associated with energy consumption. Route legs located near and around Raleigh were found to be some of the most optimal options based on their physical properties and comparatively greater potential to mitigate human exposure to criteria pollutants.
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    Modeling Energy Efficiency as a Supply Resource
    (2017-08-22) Gumerman, Etan; Vegh, Tibor
    Energy efficiency may be an inexpensive way to meet future demand and reduce greenhouse gas emissions, yet little work has been attempted to estimate annual energy efficiency supply functions for electricity planning. The main advantage of using a supply function is that energy efficiency adoption can change as demand changes. Models such as Duke University’s Dynamic Integrated Economy/Energy/Emissions Model (DIEM) have had to rely on simplistic or fixed estimates of future energy efficiency from the literature rather than on estimates from energy efficiency supply curves. This paper attempts to develop a realistic energy efficiency supply curve and to improve on the current energy efficiency modeling. It suggests an alternative approach based on saved-energy cost data from program administrators and explains the methodologies employed to create the supply curve. It illustrates this approach with results from DIEM for various electricity demand scenarios. The analysis suggests that an additional 5%–9% of energy efficiency is deployed for every 10% increase in the cost of electricity. Therefore, DIEM “invested” in energy efficiency up to an inelastic point on the energy efficiency supply curve. By contrast, the U.S. Environmental Protection Agency’s energy efficiency approach assumes that realized energy efficiency is fixed, and has no elasticity, regardless of changes to marginal costs or constraints that affect emissions or economics.
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    The Impact of Electric Vehicle Adoption in North Carolina
    (2019-04-24) Chen, Shiwen; Jiang, Yi; Shen, Yangdi; Singh, Nikhita
    The U.S total annual sales of Battery Electric Vehicles (EVs) and Plug-in EVs increased from 16 thousand in 2011 to 190 thousand in 2017; that is 12 times in size over 6 years (Fitzgerald). Consequently, the demand for electricity has increased rapidly, which creates new challenges and opportunities for the electricity generation system and the power grid. This project assesses the impacts of different scenarios of penetration of EVs in the Duke Energy Carolinas/Duke Energy Progress (DEC/DEP) region in 2030. Specifically, the project simulates the real-time EVs operation in 2030 and provides economic, environmental and social insights. First this project will characterize scenarios of EV penetration in the region that take EV growth and charging patterns into consideration. Then the additional demand caused by each scenario will be generated by a custom model built for this project. Lastly this project will utilize Aurora, an electric modeling, forecasting, and analysis tool, to simulate the impact of the additional demand on the DEC/DEP system in 2030. The results of this project underline the relationship between the economic and environmental impact of electric vehicles and the DEC/DEP fuel mix.