Optimization models for integrated biorefinery operations

Gulcan, Berkay; Eksioglu, Sandra D.; Song, Yongjia; Roni, Mohammad; Chen, Qiushi

doi:10.1007/s11590-021-01767-4

Optimization models for integrated biorefinery operations

Journal Article · Tue Jun 22 00:00:00 EDT 2021 · Optimization Letters

DOI:https://doi.org/10.1007/s11590-021-01767-4· OSTI ID:1805701

Gulcan, Berkay ^[1]; ^[2]; Song, Yongjia ^[1]; Roni, Mohammad ^[3]; Chen, Qiushi ^[1]

Clemson Univ., SC (United States)
Univ. of Arkansas, Fayetteville, AR (United States)
Idaho National Lab. (INL), Idaho Falls, ID (United States)

Variations of physical and chemical characteristics of biomass lead to an uneven flow of biomass in a biorefinery, which reduces equipment utilization and increases operational costs. Uncertainty of biomass supply and high processing costs increase the risk of investing in the US’s cellulosic biofuel industry. We propose a stochastic programming model to streamline processes within a biorefinery. A chance constraint models system’s reliability requirement that the reactor is operating at a high utilization rate given uncertain biomass moisture content, particle size distribution, and equipment failure. The model identifies operating conditions of equipment and inventory level to maintain a continuous flow of biomass to the reactor. Furthermore, the sample average approximation method approximates the chance constraint and a bisection search-based heuristic solves this approximation. A case study is developed using real-life data collected at Idaho National Laboratory’s biomass processing facility. An extensive computational analysis indicates that sequencing of biomass bales based on moisture level, increasing storage capacity, and managing particle size distribution, increases utilization of the reactor and reduces operational costs.

View Accepted Manuscript (DOE)

Research Organization:: Idaho National Laboratory (INL), Idaho Falls, ID (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Bioenergy Technologies Office

Grant/Contract Number:: AC07-05ID14517; EE0008255

OSTI ID:: 1805701

Report Number(s):: INL/JOU--21-61280-Rev000

Journal Information:: Optimization Letters, Journal Name: Optimization Letters Journal Issue: 3 Vol. 16; ISSN 1862-4472

Publisher:: Springer NatureCopyright Statement

Country of Publication:: United States

Language:: English

References (39)

On the use of machine learning methods to predict component reliability from data-driven industrial case studies Alsina, Emanuel F.; Chica, Manuel; Trawiński, Krzysztof The International Journal of Advanced Manufacturing Technology, Vol. 94, Issue 5-8 https://doi.org/10.1007/s00170-017-1039-x	journal	September 2017
Sample Average Approximation Method for Chance Constrained Programming: Theory and Applications Pagnoncelli, B. K.; Ahmed, S.; Shapiro, A. Journal of Optimization Theory and Applications, Vol. 142, Issue 2 https://doi.org/10.1007/s10957-009-9523-6	journal	March 2009
Socio-economic drivers in implementing bioenergy projects Domac, J.; Richards, K.; Risovic, S. Biomass and Bioenergy, Vol. 28, Issue 2 https://doi.org/10.1016/j.biombioe.2004.08.002	journal	February 2005
The evolution of system reliability optimization Coit, David W.; Zio, Enrico Reliability Engineering & System Safety, Vol. 192 https://doi.org/10.1016/j.ress.2018.09.008	journal	December 2019
Optimal Redundancy for Reliability in Series Systems Ghare, P. M.; Taylor, R. E. Operations Research, Vol. 17, Issue 5 https://doi.org/10.1287/opre.17.5.838	journal	October 1969
Integrated Bioenergy Supply Chain Network Planning Problem Memişoğlu, Gökhan; Üster, Halit Transportation Science, Vol. 50, Issue 1 https://doi.org/10.1287/trsc.2015.0598	journal	February 2016
Optimal design of sustainable cellulosic biofuel supply chains: Multiobjective optimization coupled with life cycle assessment and input-output analysis You, Fengqi; Tao, Ling; Graziano, Diane J. AIChE Journal, Vol. 58, Issue 4 https://doi.org/10.1002/aic.12637	journal	April 2011
Process synthesis and optimization of biorefinery configurations Pham, Viet; El-Halwagi, Mahmoud AIChE Journal, Vol. 58, Issue 4 https://doi.org/10.1002/aic.12640	journal	June 2011
An algorithm to solve integer programming problems: An efficient tool for reliability design Misra, Krishna B. Microelectronics Reliability, Vol. 31, Issue 2-3 https://doi.org/10.1016/0026-2714(91)90214-R	journal	January 1991
Application of genetic algorithm for reliability allocation in nuclear power plants Yang, Joon-Eon; Hwang, Mee-Jung; Sung, Tae-Yong Reliability Engineering & System Safety, Vol. 65, Issue 3 https://doi.org/10.1016/S0951-8320(98)00103-3	journal	September 1999
Optimal control of operation efficiency of belt conveyor systems Zhang, Shirong; Xia, Xiaohua Applied Energy, Vol. 87, Issue 6 https://doi.org/10.1016/j.apenergy.2010.01.006	journal	June 2010
Optimal energy control of a crushing process based on vertical shaft impactor Numbi, B. P.; Xia, X. Applied Energy, Vol. 162 https://doi.org/10.1016/j.apenergy.2014.12.017	journal	January 2016
A novel experimental data-driven exponential convex model for reliability assessment with uncertain-but-bounded parameters Meng, Zeng; Zhang, Zhuohui; Zhou, Huanlin Applied Mathematical Modelling, Vol. 77 https://doi.org/10.1016/j.apm.2019.08.010	journal	January 2020
The effects of physical and chemical preprocessing on the flowability of corn stover Crawford, Nathan C.; Nagle, Nick; Sievers, David A. Biomass and Bioenergy, Vol. 85 https://doi.org/10.1016/j.biombioe.2015.12.015	journal	February 2016
Setting a baseline for Integrated Landscape Design: Cost and risk assessment in herbaceous feedstock supply chains Hansen, Jason K.; Roni, Mohammad S.; Nair, Shyam K. Biomass and Bioenergy, Vol. 130 https://doi.org/10.1016/j.biombioe.2019.105388	journal	November 2019
Discrete element modeling of switchgrass particles under compression and rotational shear Guo, Yuan; Chen, Qiushi; Xia, Yidong Biomass and Bioenergy, Vol. 141 https://doi.org/10.1016/j.biombioe.2020.105649	journal	October 2020
Analyzing the design and management of biomass-to-biorefinery supply chain Ekşioğlu, Sandra D.; Acharya, Ambarish; Leightley, Liam E. Computers & Industrial Engineering, Vol. 57, Issue 4 https://doi.org/10.1016/j.cie.2009.07.003	journal	November 2009
Chance constrained programming approach to process optimization under uncertainty Li, Pu; Arellano-Garcia, Harvey; Wozny, Günter Computers & Chemical Engineering, Vol. 32, Issue 1-2 https://doi.org/10.1016/j.compchemeng.2007.05.009	journal	January 2008
Optimal design of a multi-product biorefinery system Zondervan, Edwin; Nawaz, Mehboob; de Haan, André B. Computers & Chemical Engineering, Vol. 35, Issue 9 https://doi.org/10.1016/j.compchemeng.2011.01.042	journal	September 2011
Solution approaches for the multiobjective stochastic programming Abdelaziz, Fouad Ben European Journal of Operational Research, Vol. 216, Issue 1 https://doi.org/10.1016/j.ejor.2011.03.033	journal	January 2012
Coupled DEM–CFD simulation of drying wood chips in a rotary drum – Baffle design and model reduction Scherer, Viktor; Mönnigmann, Martin; Berner, Marc Oliver Fuel, Vol. 184 https://doi.org/10.1016/j.fuel.2016.05.054	journal	November 2016
Biomass feeding for thermochemical reactors Dai, Jianjun; Cui, Heping; Grace, John R. Progress in Energy and Combustion Science, Vol. 38, Issue 5 https://doi.org/10.1016/j.pecs.2012.04.002	journal	October 2012
A numerical study on the influence of particle shape on hopper discharge within the polyhedral and multi-sphere discrete element method Höhner, D.; Wirtz, S.; Scherer, V. Powder Technology, Vol. 226 https://doi.org/10.1016/j.powtec.2012.03.041	journal	August 2012
DEM study of granular transport in partially filled horizontal screw conveyors Orefice, L.; Khinast, J. G. Powder Technology, Vol. 305 https://doi.org/10.1016/j.powtec.2016.09.067	journal	January 2017
Discrete element modeling of deformable pinewood chips in cyclic loading test Xia, Yidong; Lai, Zhengshou; Westover, Tyler Powder Technology, Vol. 345 https://doi.org/10.1016/j.powtec.2018.12.072	journal	March 2019
A generic data-driven software reliability model with model mining technique Yang, Bo; Li, Xiang; Xie, Min Reliability Engineering & System Safety, Vol. 95, Issue 6 https://doi.org/10.1016/j.ress.2010.02.006	journal	June 2010
A supply chain network design model for biomass co-firing in coal-fired power plants Roni, Md. S.; Eksioglu, Sandra D.; Searcy, Erin Transportation Research Part E: Logistics and Transportation Review, Vol. 61 https://doi.org/10.1016/j.tre.2013.10.007	journal	January 2014
Bioenergy to mitigate for climate change and meet the needs of society, the economy and the environment Sims, Ralph E. H. Mitigation and Adaptation Strategies for Global Change, Vol. 8, Issue 4 https://doi.org/10.1023/B:MITI.0000005614.51405.ce	journal	January 2003
Genetic algorithms in optimization of system reliability Painton, L.; Campbell, J. IEEE Transactions on Reliability, Vol. 44, Issue 2 https://doi.org/10.1109/24.387368	journal	June 1995
Reliability optimization of coherent systems Prasad, V. R.; Kuo, W. IEEE Transactions on Reliability, Vol. 49, Issue 3 https://doi.org/10.1109/24.914551	journal	January 2000
Stochastic Optimization of Maintenance and Operations Schedules Under Unexpected Failures Basciftci, Beste; Ahmed, Shabbir; Gebraeel, Nagi Z. IEEE Transactions on Power Systems, Vol. 33, Issue 6 https://doi.org/10.1109/TPWRS.2018.2829175	journal	November 2018
System Reliability Allocation and a Computational Algorithm Fyffe, David E.; Hines, William W.; Lee, Nam Kee IEEE Transactions on Reliability, Vol. R-17, Issue 2 https://doi.org/10.1109/TR.1968.5217517	journal	June 1968
Dynamic Programming Bellman, R. Science, Vol. 153, Issue 3731 https://doi.org/10.1126/science.153.3731.34	journal	July 1966
A Sample Approximation Approach for Optimization with Probabilistic Constraints Luedtke, James; Ahmed, Shabbir SIAM Journal on Optimization, Vol. 19, Issue 2 https://doi.org/10.1137/070702928	journal	January 2008
Beyond Beta Kotz, Samuel; van Dorp, Johan René https://doi.org/10.1142/5720	journal	December 2004
Optimal Estimation of Executive Compensation by Linear Programming Charnes, A.; Cooper, W. W.; Ferguson, R. O. Management Science, Vol. 1, Issue 2 https://doi.org/10.1287/mnsc.1.2.138	journal	January 1955
Optimizing Call Center Staffing Using Simulation and Analytic Center Cutting-Plane Methods Atlason, Júlíus; Epelman, Marina A.; Henderson, Shane G. Management Science, Vol. 54, Issue 2 https://doi.org/10.1287/mnsc.1070.0774	journal	February 2008
An Economic Analysis of the Future U.S. Biofuel Industry, Facility Location, and Supply Chain Network Chen, Xiaoguang; Önal, Hayri Transportation Science, Vol. 48, Issue 4 https://doi.org/10.1287/trsc.2013.0488	journal	November 2014
A discrete numerical model for granular assemblies Cundall, P. A.; Strack, O. D. L. Géotechnique, Vol. 29, Issue 1 https://doi.org/10.1680/geot.1979.29.1.47	journal	March 1979

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