Minimizing cost and greenhouse gas (GHG) emissions associated with the transport of biomass feedstocks are a major focus in sustainable bioenergy production. The issue of determining appropriate candidate sites for large green-field bioenergy plants and subsequently choosing between these site options continues to involve complex decision-making processes. This paper reports on a geographical information system (GIS) based optimization model developed to identify optimal sites that minimize the biomass delivery costs and associated GHG emissions under different biomass supply scenarios. The model used extended GIS-based Fuzzy multi-criteria methods to identify candidate sites and location-allocation analysis to identify optimal energy plant locations. The model was configured to investigate sugarcane waste for bioelectricity production in Queensland, Australia. Results for the siting of bioelectricity generation capacity in Queensland identified optimally located plants with installed capacity ranges from 57 MW to 185 MW and average transportation distances of 27 km to 64 Km. The Burdekin cane growing region was identified as the most favoured location when considering feedstock transport costs and associated GHG emissions.
Keywords GIS, Biomass energy plant, Bioelectricity, Location-allocation model