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

Abstract

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.

Recent Advances in Technologies, Methods, and Economic Analysis for Sustainable Development of Energy, Water, and Environment Systems

“…Results showed that the energy supply demand and energy distribute demand by the microgrid had a levelized cost of energy, which is lower than the scheme of extending the electric grid to the communities. Juan et al [52] developed a multi-objective target-oriented robust Monte Carlo model to optimize a biomass co-firing network, integrating uncertainties in the biomass properties with investment and operations planning. Compared to the deterministic solution, the robust optimal network had a relatively insusceptible influence on the uncertainties.…”

Wood Pellet Driven-Biochar Characterization Produced at Different Targeted Pyrolysis Temperatures

“…Nevertheless, co-firing presents challenges as biomass performs less efficiently than coal, as highlighted in recent studies (Chen and Liu 2023;Hariana et al 2023;Shobar et al 2020;Sugiyono et al 2023). Additionally, biomass combustion is challenging to control due to its high moisture content and lower energy density (San Juan et al 2021), resulting in lower energy output than coal. Therefore, to make biomass suitable for co-firing it necessitates pretreatment.…”