Energy Production from Poultry Waste: Development and Application of an Economic Model to Compare Various Concepts

The purpose of this study was to examine whether there is a profitable way to recover energy from the poultry waste produced by Seaboard Farms in Chattanooga Tennessee. This study dovetails with an earlier study conducted by the SMARTPARK^TMproject, where SMARTPARK^TMengineers determined there could be large energy savings through the placement of heat exchangers, and the sharing of hot and cold utilities between companies in that same industrial park. They suggested construction of a Centrally Managed Energy Recovery Facility (CMERF^TM) which would incorporate the heat exchangers to match heat streams between the two plants, which are reasonably close together, in order to meet their steam and cold utility requirements. This paper explores the options for employing a power or fuel generation system in addition to this, using as fuel the poultry waste materials (meat, feathers, bones) from the poultry plant. In order to do this, data from technical publications were analyzed and the options narrowed to four possibilities, in two main categories: an indirectly fired gas turbine, utilizing either compressed air (IFGT) or a steam cycle (STC) and a moving bed combustor, an integrated gasification combined cycle (IGCC), and catalytic steam gasification. A technical and economic analysis was carried out on both of these options to determine an ideal candidate for the location, energy market, and fuel source options. From this analysis an economic model was developed for each of the options, and these options were compared through a sensitivity analysis for all of the major factors. This economic model was verified and validated through data from literature sources. Through this careful technical and economic analysis, the IGCC is recommended as the ideal option, due to its reasonable installation costs and flexibility with feedstock. This option proved to be the most beneficial for the cost across the range of variables.