Multi-Objective Target-Oriented Robust Optimization of Biomass Co-Firing Networks Under Quality Uncertainty

Reductions in coal use and greenhouse gas emissions may be achieved through implementing biomass co-firing in existing coal-fired power plants with minor retrofits. Furthermore, the biomass may be sourced sustainably from agricultural wastes. Under direct co-firing, biomass is directly used as secondary fuel, while indirect co-firing separately processes the biomass reducing risks for equipment damage from unconventional feedstock. Despite the increased costs, this approach generates a biochar by-product that may be applied directly to soil for permanent carbon sequestration. However, these systems face uncertainties in biomass quality that may increase costs and environmental impacts during actual operations. This work develops a multi-objective target-oriented robust optimization model to design biomass co-firing networks integrating uncertainty in biomass properties with investment and operations planning. A case study is solved to demonstrate model capabilities. Monte Carlo simulation shows that the robust optimal network is relatively insusceptible to uncertainties compared to the deterministic solution.

Automated summary

Biomass co-firing can reduce coal use and greenhouse gas emissions, but faces challenges from uncertainties in biomass quality. A study developed a multi-objective robust optimization model integrating uncertainty in biomass properties with investment and operations planning, demonstrating its capabilities. Monte Carlo simulation showed that the robust optimal network is relatively insusceptible to uncertainties compared to the deterministic solution.