The effect of location and facility demand on the marginal cost of delivered wood chips from energy crops: A case study of the state of Tennessee

Abstract

Cost-supply curves for delivered wood chips from short rotation woody crops were calculated for 21 regularly-spaced locations spanning the state of Tennessee. These curves were used to systematically evaluate the combined effects of location and facility demand on wood chip feedstock costs in Tennessee. The cost-supply curves were developed using BRAVO, a GIS-based decision support system which calculates marginal cost of delivering wood chips to a specific location given road network maps and maps of farmgate prices and supplies of woody chips from short rotation energy crops.Marginal costs of delivered chips varied by both facility location in the state and facility demand. Marginal costs were lowest in central Tennessee unless the facility demand was greater than 2.7 million dry Mg per year (3 million dry tons per year) in which case west Tennessee was the Iowest cost region. Marginal costs rose rapidly with increasing facility demand in the mountainous eastern portion of the state. Transportation costs accounted for 18 to 29% of the delivered cost and ranged between $8 and $18/dry Mg ($7 and $16/dry ton). Reducing the expected farmer participation rate from 100% to 50% or 25% dramatically raised the marginal costs of feedstock supply in the east and central regions of the state. The analysis demonstrates the need to use geographically-specific information when projecting the potential costs and supplies of biomass feedstock.

Sources of Biomass Feedstock Variability and the Potential Impact on Biofuels Production

“…As densification technologies continue to improve and as national and global biofuels industries emerge, biomass resources will be shipped greater distances, potentially increasing the variability of biomass received at biorefineries as well as offering new opportunities to reduce variability through wider supply and blending. However, issues of low bulk mass and energy densities must be addressed to keep transportation costs economical [51,52]. It is important to understand all potential sources of variability in order to expand the current feedstock supply and to mitigate factors that will cause fluctuations in product quality.…”

Identification, assessment and ordering of concepts for agro-energy planning and possibilities of spatial analysis

“…Therefore, in order to develop this type of study for a spatial application, it is necessary to previously conduct an approach similar to the one that MICHELAZZO (2005) carried out, when analyzed the rising of straw recovery costs related to the distance, thereby establishing the logistic cost of straw recovery. Moreover, taking into consideration the capital and operational costs, it is necessary to establish the recovery cost that is embedded in each route of straw recovery, described in some studies of biomass logistics as farmgate price, which means the cost that the plant have to pay for the biomass supplier, regardless of the logistic cost (GRAHAM et al, 1997). It is also worth to note that information about secondary roads or non-paved roads is scarce, for this reason, it is essential to incorporate a non-linearity factor in the distance between the area of collection and the mill (MONFORTI et al, 2013).…”

Investigation of thermochemical biorefinery sizing and environmental sustainability impacts for conventional supply system and distributed pre‐processing supply system designs

“…Additionally, we consider each case with either high moisture (50% as harvested) or low builds upon previous systems and analyses developed over the last several years. [10][11][12][13][14] SCM is a geographically based modeling system for locating biorefi neries and predicting the associated supplies (price and quantity) of bioenergy feedstocks. SCM combines geographic estimates of feedstock supply with a transportation network to either select optimal locations for biorefi neries or to identify the lowest-cost feedstock supplies for a set of predefi ned locations.…”