A multi-objective optimization model for the design of a biomass co-firing supply network

• Main Authors: San Juan, Jayne Lois G., Sy, Charlle L., Tan, Raymond Girard R.
• Format: text
• Published: Animo Repository 2018
• Subjects: Biomass energy; Pollution prevention; Chemical Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/252
• Institution: De La Salle University

Because of increasing energy consumption, shrinking fossil fuel reserves, and climate change as an effect of greenhouse gas emissions, the interest in more sustainable and renewable sources of energy, such as biomass, has grown. Co-firing biomass with coal is an attractive alternative because it is an immediate and practical way to reduce coal usage and harmful emissions, requiring only minor modifications to the power plant. A multi-objective mixed integer non-linear programming model for a biomass co-firing network integrating biomass property considerations with investment, transportation and production planning is formulated and validated. A balance between the two conflicting objectives is achieved using a goal programming approach. Computational experiments reveal that biomass and coal blend ratios should be managed carefully to reach acceptable fuel properties. When improperly managed, it can negatively impact conversion yield and equipment life. Furthermore, less efficiency loss despite unsuitable feedstock properties encourage the model to use more biomass to replace coal because it will not negatively impact costs and would decrease pollutant emissions. Analysis also shows that pre-treatment facilities are prioritized depending on the effectiveness in improving properties that the biomass input violate the most based on power plant system requirements. Biomass seasonality as it impacts availability and quality are accounted for in purchase and storage planning, where purchases are done during periods when availability and quality is better, when low availability and quality are foreseen in succeeding periods, and the biomass are stored for future use. On the other hand, when quality and quantity of biomass does not experience significant seasonal changes, storage is avoided due to the damage it causes.