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Design and dispatch optimization of a solid-oxide fuel cell assembly for unconventional oil and gas production. (English) Zbl 1426.80018

The authors present a design and dispatch optimization model concerning a solid-oxide fuel cell and especially a geothermic fuel cell (GFC). The design problem consists in a minimization problem for an objective function: minimize \(w\cdot \dot{W}^{\mathrm{sup}}-\alpha_{1}c^{\mathrm{drill}}L^{\mathrm{GFC}}+\alpha_{2}C^{\mathrm{total}}\), where \(w\) represents the unit cost of electricity, \(\dot{W}^{\mathrm{sup}}\) is the supplemental electricity power, \(c^{\mathrm{drill}}\) is the drilling cost per unit length, \(L^{\mathrm{GFC}}\) is the length of the GFC and \( C^{\mathrm{total}}\) is the total cost of the construction of the system. The authors introduce different constraints involving parameters and variables such as heat exchangers, pressure drops, capital costs. The dispatch problem also consists in a minimization problem for an objective function: minimize \( C^{\mathrm{fuel}}+w\sum_{t}(\widehat{t}_{t}\cdot \dot{W}^{\mathrm{sup}})-\sum_{t}C^{NG}\cdot V_{t}^{\mathrm{use}}\cdot (\mathcal{E}_{t}^{\mathrm{elec}}+\mathcal{E}_{t}^{\mathrm{heat}})\), which is a linear combination of the system operating costs and of the supplemental electric power, less the sum of the GFC electrical and heating efficiencies at each time period. The authors here also introduce constraints which involve different parameters and variables. They observe that the problems are continuous, non-convex, and nonlinear ones. They present different strategies and tools to solve these problems, among which is the KNITRO solver, and they compare their efficiencies. The paper ends with an example.

MSC:

80M50 Optimization problems in thermodynamics and heat transfer
80A30 Chemical kinetics in thermodynamics and heat transfer
80A25 Combustion
78A57 Electrochemistry
65K10 Numerical optimization and variational techniques
65M08 Finite volume methods for initial value and initial-boundary value problems involving PDEs
76N25 Flow control and optimization for compressible fluids and gas dynamics

Software:

NEOS; KNITRO; Ipopt; AMPL
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Full Text: DOI

References:

[1] Akkaya A, Sahin B, Erdem H (2008) An analysis of SOFC/GT CHP system based on exergetic performance criteria. Int J Hydrog Energy 33(10):2566-77 · doi:10.1016/j.ijhydene.2008.03.013
[2] Anyenya G, Haun B, Daubenspeck M, Braun R, Sullivan NP (2016) Experimental testing of a novel kilowatt-scale multistack solid-oxide fuel cell assembly for combined heat and power. J Electrochem Energy Convers Storage 13(4):041001 · doi:10.1115/1.4035352
[3] Anyenya G, Sullivan N, Braun R (2017) Modeling and simulation of a novel 4.5 KW \[_e\] e multi-stack solid-oxide fuel cell prototype assembly for combined heat and power. Energy Convers Manag 140:247-259 · doi:10.1016/j.enconman.2017.02.071
[4] AMPL (2018) Optimization LLC, AMPL Version 20170207
[5] Fourer R, Gay D, Kernighan B (2003) AMPL-a modeling language for mathematical programming. Duxbury Press · Zbl 0701.90062
[6] Bauman J, Huang C, Gani M, Deo M (2010) Oil Shale: a solution to the liquid fuel dilemma, Ch. 7, pp 135-146. American Chemical Society: Washington
[7] Becker WL, Braun R, Penev M, Melaina M (2012) Design and techno-economic performance analysis of a 1 MW solid oxide fuel cell polygeneration system for combined production of heat, hydrogen, and power. J Power Sources 200:34-44 · doi:10.1016/j.jpowsour.2011.10.040
[8] Biegler LT, Zavala VM (2009) Large-scale nonlinear programming using IPOPT: an integrating framework for enterprise-wide dynamic optimization. Comput Chem Eng 33(3):575-582 · doi:10.1016/j.compchemeng.2008.08.006
[9] Birdwell J, Mercier T, Johnson R, Brownfield M (2013) In-place oil shale resources examined by grade in the major basins of the Green River formation, Colorado, Utah, and Wyoming. U.S. Geological Survey Fact Sheet, 2012-3145
[10] Birdwell J, Mercier T, Johnson R, Brownfield M (2015) In-place oil shale resources of the Mahogany Zone, Green River formation, sorted by grade, overburden thickness, and stripping ratio, Piceance Basin, Colorado, and Uinta Basin, Utah. U.S. Geological Survey Fact Sheet, 2015-3005
[11] Boehm RF (1987) Design and analysis of thermal systems. Wiley, New York
[12] Borgnakke C, Sonntag RE (2009) Fundamentals of thermodynamics. Wiley, Hoboken
[13] Bove R, Ubertini S (2006) Modeling solid oxide fuel cell operation: approaches, techniques and results. J Power Sources 159:543-559 · doi:10.1016/j.jpowsour.2005.11.045
[14] Brandt A (2008) Converting oil shale to liquid fuels: energy inputs and greenhouse gas emissions of the Shell in-situ conversion process. Environ Sci Technol 42:7489-7495 · doi:10.1021/es800531f
[15] Braun RJ, Kazempoor P (2013) Application of SOFCs in combined heat, cooling and power systems. In: Solid Oxide Fuel Cells, pp 327-382
[16] Braun RJ (2010) Techno-economic optimal design of solid oxide fuel cell systems for micro-combined heat and power applications in the US. J Fuel Cell Sci Technol 7(3):031018 · doi:10.1115/1.3211099
[17] Burnham AK, McConaghy JR (2006) Comparison of the acceptability of various oil shale processes. Department of Energy, USA
[18] Byrd RH, Hribar ME, Nocedal J (1999) An interior point algorithm for large-scale nonlinear programming. SIAM J Optim 9(4):877-900 · Zbl 0957.65057 · doi:10.1137/S1052623497325107
[19] Byrd RH, Nocedal J, Waltz RA (2006) KNITRO: an integrated package for nonlinear optimization. Springer, Berlin, pp 35-59 · Zbl 1108.90004
[20] Calise F, Dentice-d’Accadia M, Vanoli L, von Spakovsky M (2006) Single-level optimization of a hybrid SOFC-GT power plant. J Power Sources 159:1169-1185 · doi:10.1016/j.jpowsour.2005.11.108
[21] Calise F, Dentice-d’Accadia M, Vanoli L, von Spakovsky MR (2007) Full load synthesis/design optimization of a hybrid SOFC-GT power plant. Energy 32(4):446-458 · doi:10.1016/j.energy.2006.06.016
[22] Contreras J, Losi A, Russo M, Wu FF (2002) Simulation and evaluation of optimization problem solutions in distributed energy management systems. IEEE Trans Power Syst 17(1):57-62 · doi:10.1109/59.982193
[23] Czyzyk J, Mesnier MP, Moré JJ (1998) The NEOS Server. IEEE J Comput Sci Eng 5(3):68 · doi:10.1109/99.714603
[24] Dodds PE, Staffell I, Hawkes AD, Li F, Grunewald P, McDowall W, Ekins P (2015) Hydrogen and fuel cell technologies for heating: a review. Int J Hydrogen Energy 40:2065-2083 · doi:10.1016/j.ijhydene.2014.11.059
[25] Dolan ED (2001) The NEOS Server 4.0 Administrative Guide. Technical Memorandum ANL/MCS-TM-250, Mathematics and Computer Science Division, Argonne National Laboratory
[26] Douvartzides S, Coutelieris F, Tsiakaras P (2003) On the systematic optimization of ethanol-fed SOFC-based electricity generating systems in terms of energy and exergy. J Power Sources 114(2):203-212 · doi:10.1016/S0378-7753(02)00611-0
[27] Elmer T, Worall M, Wu S, Riffat SB (2015) Fuel cell technology for domestic built environment applications: State of-the-art review. Renew Sustain Energy Rev 42:913-931 · doi:10.1016/j.rser.2014.10.080
[28] Fontell E, Kivisaari T, Christiansen N, Hansen JB, Palsson J (2004) Conceptual study of a 250 kW planar SOFC system for CHP application. J Power Sources 131:49-56 · doi:10.1016/j.jpowsour.2004.01.025
[29] Fullenbaum R, Smith C, Rao M, Xiao J, Adams S, Fontaine, R (2015) Oil and gas upstream cost study. US Energy Information Administration DT007965
[30] Gropp, W.; Moré, JJ; Buhman, MD (ed.); Iserles, A. (ed.), Optimization environments and the NEOS server, No. 167 (1997), Cambridge · Zbl 1031.65075
[31] Hazra KG, Lee KJ, Economides CE, Moridis G (2013) Comparison of heating methods for in-situ oil shale extraction. In: IOR 2013-17th European Symposium on Improved Oil Recovery
[32] Johnson RC, Mercier TJ, Brownfield ME, Self JG (2010) Assessment of in-place oil shale resources in the Eocene Green River Formation, Uinta Basin, Utah and Colorado. U.S. Geological Survey Digital Data Series DDS-69-BB p 153
[33] Lee KJ, Moridis GJ, Ehlig-Economides CA (2016a) In situ upgrading of oil shale by SteamFrac in multistage transverse fractured horizontal wellsystem. Recovery Util Environ Eff 38(20):3034-3041
[34] Lee KJ, Moridis GJ, Ehlig-Economides CA (2016b) A comprehensive simulation model of kerogen pyrolysis for the in-situ upgrading of oil shales. SPE J 21(05):1612-1630 · doi:10.2118/173299-PA
[35] Lee KJ, Moridis GJ, Ehlig-Economides CA (2017a) Compositional simulation of hydrocarbon recovery from oil shale reservoirs with diverse initial saturations of fluid phases by various thermal processes. Energy Explor Exploit 35(2):172-193 · doi:10.1177/0144598716684307
[36] Lee KJ, Moridis GJ, Ehlig-Economides CA (2017b) Numerical simulation ofdiverse thermal in situ upgrading processes for the hydrocarbon production from kerogen in oil shale reservoirs. Energy Explor Exploit 35(3):315-337 · doi:10.1177/0144598716689354
[37] Li H, Nalim R, Haldi PA (2006) Thermal-economic optimization of a distributed multi-generation energy system-a case study of Beijing. Appl Therm Eng 26(7):709-719 · doi:10.1016/j.applthermaleng.2005.09.005
[38] Li Q, Han X, Liu Q, Jiang X (2014) Thermal decomposition of Huadian oil shale. Part 1. Crit Org Intermed Fuel 121:109-116
[39] Lisbona P, Corradetti A, Bove R, Lunghi P (2007) Analysis of a solid oxide fuel cell system for combined heat and power applications under non-nominal conditions. Electrochim Acta 53:1920-1930 · doi:10.1016/j.electacta.2007.08.046
[40] Naimaster E, Sleiti A (2013) Potential of SOFC CHP systems for energy-efficient commercial buildings. Energy Build 61:153-160 · doi:10.1016/j.enbuild.2012.09.045
[41] Najafi B, Shirazi A, Aminyavari M, Rinaldi F, Taylor RA (2014) Exergetic, economic and environmental analyses and multi-objective optimization of an SOFC-gas turbine hybrid cycle coupled with an MSF desalination system. Desalination 334(1):46-59 · doi:10.1016/j.desal.2013.11.039
[42] Nellis G, Klein S (2009) Heat transfer, vol 10. Cambridge University Press, New York, pp 1056-1058 · Zbl 1165.80001
[43] Palazzi F, Autissier N, Marechal FM, Favrat D (2007) A methodology for thermo-economic modeling and optimization of solid oxide fuel cell systems. Appl Thermal Eng 27(16):2703-2712 · doi:10.1016/j.applthermaleng.2007.06.007
[44] Petrescu S, Petre C, Costea M, Malancioiu O, Boriaru N, Dobrovicescu A, Feidt M, Harman C (2010) A methodology of computation, design and optimization of solar Sterling power plant using hydrogen/oxygen fuel cells. Energy 35(2):729-739 · doi:10.1016/j.energy.2009.10.036
[45] Pruitt KA, Braun RJ, Newman AM (2013) Evaluating shortfalls in mixed-integer programming approaches for the optimal design and dispatch of distributed generation systems. Appl Energy 102:386-398 · doi:10.1016/j.apenergy.2012.07.030
[46] Pruitt KA, Leyffer S, Newman AM, Braun RJ (2014) A mixed-integer nonlinear program for the optimal design and dispatch of distributed generation systems. Optim Eng 15(1):167-197 · Zbl 1314.90056 · doi:10.1007/s11081-013-9226-6
[47] Ren H, Zhou W, Nakagami K, Gao W, Wu Q (2010) Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects. Appl Energy 87(12):3642-3651 · doi:10.1016/j.apenergy.2010.06.013
[48] Riensche E, Stimming U, Unverzagt G (1998) Optimization of a 200 kW SOFC co-generation power plant: Part I: variation of process parameters. J Power Sources 73(2):251-256 · doi:10.1016/S0378-7753(98)00002-0
[49] Sadeghi M, Chitsaz A, Mahmoudi SMS, Rosen MA (2015) Thermo-economic optimization using an evolutionary algorithm of a trigeneration system driven by a solid oxide fuel cell. Energy 89:191-204 · doi:10.1016/j.energy.2015.07.067
[50] Sadeghi S, Ameri M (2013) Multi-objective optimization of PV-Bat-SOFC hybrid system: Effect of different fuels used in solid oxide fuel cell. J Energy Eng 140(2):04013022 · doi:10.1061/(ASCE)EY.1943-7897.0000170
[51] Sanaye S, Katebi A (2014) 4E analysis and multi objective optimization of a micro gas turbine and solid oxide fuel cell hybrid combined heat and power system. J Power Sources 247:294-306 · doi:10.1016/j.jpowsour.2013.08.065
[52] Shah A, Fishwick R, Wood J, Leeke G, Rigby S, Greaves M (2010) A review of novel techniques for heavy oil and bitumen extraction and upgrading. Energy Environ Sci 3(6):700-714 · doi:10.1039/b918960b
[53] Sullivan N, Anyenya G, Haun B, Daubenspeck M, Bonadies J, Kerr R, Fischer B, Wright A, Jones G, Li R (2016) In-ground operation of geothermic fuel cells for unconventional oil and gas recovery. J Power Sources 302:402-409 · doi:10.1016/j.jpowsour.2015.10.093
[54] Trendewicz AA, Braun RJ (2013) Techno-economic analysis of solid oxide fuel cell-based combined heat and power systems for biogas utilization at wastewater treatment facilities. J Power Sources 233:380-393 · doi:10.1016/j.jpowsour.2013.01.017
[55] Velumani S, Guzman C, Peniche R, Vega R (2010) Proposal of a hybrid CHP system: SOFC/micro-turbine/absorption chiller. Int J Energy Res 34(12):1088-95 · doi:10.1002/er.1632
[56] Wächter A, Biegler LT (2006) On the implementation of a Primal-Dual Interior Point Filter Line Search algorithm for large-scale nonlinear programming. Math Program 106(1):25 · Zbl 1134.90542 · doi:10.1007/s10107-004-0559-y
[57] White FM (2009) Fluid mechanics. McGraw-Hill, New York
[58] Zavala VM, Laird CD, Biegler LT (2008) Interior-point decomposition approaches for parallel solution of large-scale nonlinear parameter estimation problems. Chem Eng Sci 63(19):4834-4845 · doi:10.1016/j.ces.2007.05.022
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