Multi-objective robust optimization for the design of biomass co-firing networks
College
Gokongwei College of Engineering
Department/Unit
Industrial Engineering
Document Type
Conference Proceeding
Source Title
Proceedings of the International Conference on Industrial Engineering and Operations Management
Volume
2019
Issue
MAR
First Page
1428
Last Page
1437
Publication Date
1-1-2019
Abstract
Biomass co-firing in coal power plants is an immediate and practical approach to reduce coal usage and pollutant emissions because only minor modifications are required. With direct co-firing, biomass can be used directly as secondary fuel in power plants to partially displace coal. Although it requires minimal investments, it can lead to equipment corrosion from unconventional fuel properties of the biomass-coal blend. With indirect co-firing, the risk of damage is minimized by separately processing biomass. The solid biochar by-product can be used as soil fertilizer to achieve further reductions in GHG emissions through carbon sequestration. However, as this calls for a separate biomass energy conversion plant, its investment cost is higher. Moreover, this system faces uncertainties from the inherent variability in biomass quality. This must be accounted for because mixing fuels results in the blending of their properties. In this work, a robust optimization model is proposed to design cost and environmentally effective biomass co-firing networks that decides on appropriate co-firing configurations and fuel blends. A case study is solved to demonstrate validity. Results of Monte Carlo simulation show that the robust optimal network configuration is relatively immune to uncertainty realizations as compared with the optimum identified with deterministic models. © IEOM Society International.
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Recommended Citation
San Juan, J. G., & Sy, C. L. (2019). Multi-objective robust optimization for the design of biomass co-firing networks. Proceedings of the International Conference on Industrial Engineering and Operations Management, 2019 (MAR), 1428-1437. Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/2294
Disciplines
Industrial Engineering | Operations Research, Systems Engineering and Industrial Engineering
Keywords
Biomass energy; Robust optimization
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