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This spreadsheet serves as an Input file to the National Renewable Energy Laboratory's Waste-to-Energy System Simulation (WESyS) model developed in Stella Pro (isee systems, Lebanon, NH). WESyS is a national-level system dynamics model that simulates energy production from three sectors of the U.S. waste-to-energy industry: landfills, confined animal feeding operations (CAFOs), and publically owned treatment works (POTWs).

Author(s):
Daniel Inman, Annika Eberle, and Dylan Hettinger of the National Renewable Energy Laboratory; Steven Peterson and Corey Peck of Lexidyne, LLC.
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

This spreadsheet serves as an Input file to the National Renewable Energy Laboratory's Waste-to-Energy System Simulation (WESyS) model developed in Stella Pro (isee systems, Lebanon, NH). WESyS is a national-level system dynamics model that simulates energy production from three sectors of the U.S. waste-to-energy industry: landfills, confined animal feeding operations (CAFOs), and publically owned treatment works (POTWs).

Author(s):
Daniel Inman, Annika Eberle, and Dylan Hettinger of the National Renewable Energy Laboratory; Steven Peterson and Corey Peck of Lexidyne, LLC.
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

This spreadsheet serves as an Input file to the National Renewable Energy Laboratory's Waste-to-Energy System Simulation (WESyS) model developed in Stella Pro (isee systems, Lebanon, NH). WESyS is a national-level system dynamics model that simulates energy production from three sectors of the U.S. waste-to-energy industry: landfills, confined animal feeding operations (CAFOs), and publically owned treatment works (POTWs).

Author(s):
Daniel Inman, Annika Eberle, and Dylan Hettinger of the National Renewable Energy Laboratory; Steven Peterson and Corey Peck of Lexidyne, LLC.
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

The U.S. Department of Energy’s (DOE’s) Co-Optimization (Co-Optima) initiative is accelerating the introduction of affordable, scalable, and sustainable fuels and high-efficiency, low-emission engines with a first-of-its-kind effort to simultaneously tackle fuel and engine research and development (R&D).

Author(s):
John Farrell , John Holladay , Robert Wagner
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

Waste to Energy System Simulation Model (WESyS) - Scenario Inputs and Supplemental Tableau Workbook
Daniel Inman, Ethan Warner, Anelia Milbrandt, Alberta Carpenter, Ling Tao, Emily Newes, and Steve Peterson (Lexidyne, LLC)

Author(s):
Daniel Inman, Ethan Warner, Anelia Milbrandt, Alberta Carpenter, Ling Tao, Emily Newes, and Steve Peterson (Lexidyne, LLC)
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

Understanding the environmental effects of alternative fuel production is critical to characterizing the sustainability of energy resources to inform policy and regulatory decisions. The magnitudes of these environmental effects vary according to the intensity and scale of fuel production along each step of the supply chain. We compare the spatial extent and temporal duration of ethanol and gasoline production processes and environmental effects based on a literature review and then synthesize the scale differences on space-time diagrams.

Author(s):
Parish, Esther

The location of ethanol plants is determined by infrastructure, product and input markets, fiscal attributes of local communities, and state and federal incentives. This empirical
analysis uses probit regression along with spatial clustering methods to analyze investment activity of ethanol plants at the county level for the lower U.S. 48 states from 2000 to 2007.
The availability of feedstock dominates the site selection decision. Other factors, such as access to navigable rivers or railroads, product markets, producer credit and excise tax

Author(s):
D.M. Lambert