A Multi-Objective Optimization Model for the Design of Biomass Co-Firing Networks Integrating Feedstock Quality Considerations

Abstract

The growth in energy demand, coupled with declining fossil fuel resources and the onset of climate change, has resulted in increased interest in renewable energy, particularly from biomass. Co-firing, which is the joint use of coal and biomass to generate electricity, is seen to be a practical immediate solution for reducing coal use and the associated emissions. However, biomass is difficult to manage because of its seasonal availability and variable quality. This study proposes a biomass co-firing supply chain optimization model that simultaneously minimizes costs and environmental emissions through goal programming. The economic costs considered include retrofitting investment costs, together with fuel, transport, and processing costs, while environmental emissions may come from transport, treatment, and combustion activities. This model incorporates the consideration of feedstock quality and its impact on storage, transportation, and pre-treatment requirements, as well as conversion yield and equipment efficiency. These considerations are shown to be important drivers of network decisions, emphasizing the importance of managing biomass and coal blend ratios to ensure that acceptable fuel properties are obtained.

Towards Efficient and Clean Process Integration: Utilisation of Renewable Resources and Energy-Saving Technologies

“…San Juan et al [142] developed a MILP model for optimising a biomass co-firing supply chain network. The model considers feedstock properties while minimising economic cost and environmental emissions through goal programming.…”

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

“…However, the approach proposed by Pérez-Fortes et al [14] is limited because it assumed strict constraints for quality requirements, when these limits are often violated in practice, while Mohd Idris et al [12] and Griffin et al [13] overlooked the consideration of feedstock properties despite its critical impact on system decisions and performance. San Juan et al [15] and San Juan et al [16] address this by developing a multi-objective optimization models that captures the changes in biomass properties as it moves along the supply chain and its impact on conversion yield and equipment damage. Most of these literatures which cover optimization modelling of co-firing supply chain focus only on direct co-firing despite the trade-offs between the two co-firing schemes [17].…”

“…Most of these literatures which cover optimization modelling of co-firing supply chain focus only on direct co-firing despite the trade-offs between the two co-firing schemes [17]. San Juan et al [15] and Aviso et al [3] are works which address these gaps in literature by developing optimization models which consider the selection between direct and indirect co-firing integrated with biochar-based carbon sequestration. However, these two studies assume simplistic and deterministic conditions.…”

“…Only Castillo-Villar et al [21] considered biomass quality as an uncertainty in a biomass supply network design problem, but the impact of biomass quality was modelled only as additional costs incurred from pretreatment. San Juan and Sy [22] proposed a robust optimization model considering only the lower heating value of biomass as the uncertain parameter. However, there are several aspects of biomass quality that have significant impact on supply chain decisions, such as moisture content, ash content, and bulk density.…”

Performance Enhancement of a Multiresonant Piezoelectric Energy Harvester for Low Frequency Vibrations

“…In recent years, the advancement of new methods and applications of wireless networks drives the demand on microenergy harvesting for continuous power supply [11]. Among these various renewable energy sources, such as biomass [12,13], heat [14] and vibration [15,16], vibration-based energy harvesting has attracted the interest of many researchers because of the ubiquity and availability of various vibration sources. In addition to energy harvesting, piezoelectric materials have a wide range of applications [17][18][19][20][21] in various science and engineering disciplines.…”