Simulation-Optimization Approach for the Logistics Network Design of Biomass Co-Firing with Coal at Power Plants

Maria F. Aranguren, Krystel K. Castillo-Villar, Mario Aboytes-Ojeda and Marcio H. Giacomoni
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Maria F. Aranguren: Texas Sustainable Energy Research Institute and Mechanical Engineering Department, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA
Krystel K. Castillo-Villar: Texas Sustainable Energy Research Institute and Mechanical Engineering Department, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA
Mario Aboytes-Ojeda: Texas Sustainable Energy Research Institute and Mechanical Engineering Department, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA
Marcio H. Giacomoni: Civil and Environmental Engineering Department, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA

Sustainability, 2018, vol. 10, issue 11, 1-18

Abstract: This work proposes a hybrid scheme that combines a simulation model and a mathematical programming model for designing logistic networks for co-firing biomass, specifically switchgrass, in conventional coal-fired power plants. The advantages of co-firing biomass include: (1) the creation of green jobs; (2) the efficient use of current power plant infrastructure; (3) fostering the penetration of renewable energy into power networks; and, (4) the reduction of greenhouse gas (GHG) emissions. The novelty of this work lies in the inclusion of (1) the inherent variability of biomass supply at the parcel level, and (2) the effects of climate change on future biomass supply when designing a feedstock logistic network. The design optimization is conducted at the farm/parcel level (most, if not all, previous works have used county level average data) and integrates the crop growth predictions employing United States Department of Agriculture’s (USDA’s) Agricultural Land Management with Numerical Assessment Criteria (ALMANAC) simulation model; the output of the simulations is input into the mixed integer linear programming (MILP) hub-and-spoke model to minimize the overall cost of the logistic network. Specifically, the MILP-based model selects the parcels and depot locations as well as biomass transportation flows by taking into consideration different types of soil, land cover characteristics, and predicted yields, which account for both historical and forecasted weather data. The hybrid methodology was tested by solving realistic situations, which considered varying weather conditions. The gross results indicate that the optimized logistic network enabled meeting a 20% biomass co-firing rate demand, which reduced 1,158,867 Mg per year in GHG emissions by co-firing with biomass.

Keywords: supply chain network design; biomass; simulation; climate change; MILP; logistics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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