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Received December 16, 2020
Accepted March 16, 2021
- This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Multiscale modeling and integration of a combined cycle power plant and a two-tank thermal energy storage system with gPROMS and SimCentral
Department of Chemical Engineering, Hanbat National University, San 16-1, Dukmyung-dong, Yuseong-gu, Daejeon 34158, Korea 1PENTECH Engineering, 803, JEI PLATZ, 186, Gasan Digital 1-ro, Geumcheon-gu, Seoul 08502, Korea 2Institute for Materials and Processes, School of Engineering, The University of Edinburgh, Robert Stevenson Road, Edinburgh, EH9 3FB, UK 3AVEVA, 13F, Kbiz DMC Tower, 189, Seongam-ro, Mapo-gu, Seoul 03929, Korea
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Korean Journal of Chemical Engineering, July 2021, 38(7), 1333-1347(15), 10.1007/s11814-021-0789-1
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Abstract
With different computational tools, simulations ranging from detailed and rigorous mathematical models to overall process plant of black box models can be carried out. Whereas most of these computational tools cannot practically execute different scales of models at the same time, it becomes relevant to devise strategies in coupling two or more of them for better analysis of processes. In this light, this study proposes Excel as an interactive scale bridge of data exchange to aid the multiscale modeling and dynamic simulation of combined cycle (CC) power plant integration with two-tank thermal energy storage (TES) system using gPROMS and SimCentral. This is relevant to analyze not only the performance of TES, but the feasibility of its integration with CC in augmenting energy production to meet daily power demand. The integrated system modeled in four operational modes of CC increased in power generation by 7.3MW at an efficiency of 98.30%. The study validated the usefulness of the TES integration of 99.66% efficiency. The research results provide a communication strategy for different computational tools and an approach to effectively increase CC power production to meet varying daily demand.
Keywords
References
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Alqahtani BJ, Patino-Echeverri D, Appl. Energy, 169, 927 (2016)
Garbrecht O, Bieber M, Kneer R, Energy, 118, 876 (2017)
Johnson M, Vogel J, Hempel M, Dengel A, Seitz M, Hachmann B, Energy Procedia, 73, 281 (2015)
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Drost K, Antoniak Z, Brown D, Energy Conv. Eng. Con., 4, 251 (1990)
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Krzhizhanovskaya VV, Groen D, Bozak B, Hoekstra AG, Procedia. Comput. Sci., 51, 1082 (2015)
Helmns A, Carey VP, J. Therm. Sci. Eng. Appl., 10(5), 051004 (2018)
Parsazadeh M, Duan XL, Appl. Energy, 216, 142 (2018)
Fasano M, Borri D, Cardellini A, Alberghini M, Morciano M, Chiavazzo E, Asinari P, Energy Procedia, 126, 509 (2017)
Lee JC, Kofi OS, Kim SY, Hong SG, Oh M, J. Eng. Sci. Technol., 10, 48 (2015)
Morales-Rodriguez R, Gani R, Comput. Aided Chem. Eng., 24, 207 (2007)
Morales-Rodriguez R, Gani R, Comput. Aided Chem. Eng., 26, 495 (2007)
Morales-Rodriguez R, Gani R, Dechelotte S, Vacher A, Baudouin O, Chem. Eng. Res. Des., 86(7A), 823 (2008)
Jaworski Z, Zakrzewska B, Comput. Chem. Eng., 35(3), 434 (2011)
Heidebrecht P, Pfafferodt M, Sundmacher K, Chem. Eng. Sci., 66(19), 4389 (2011)
Vlachos DG, Mhadeshwar AB, Kaisare NS, Comput. Aided Chem. Eng., 30(10-12), 1712 (2006)
Pozzetti G, Peters B, Int. J. Multiph. Flow, 99, 186 (2018)
Park HM, Int. J. Heat Mass Transf., 75, 545 (2014)
Oh DH, Jeon RY, Kim JH, Lee CH, Oh M, Kim KJ, Cryst. Growth Des., 19(2), 658 (2019)
Vo ND, Jung MY, Oh DH, Park JS, Moon I, Oh M, Combust. Flame, 189, 12 (2018)
Lee GH, Vo ND, Jeon RY, Han SW, Hong SU, Oh M, Korean J. Chem. Eng., 35(9), 1791 (2018)
Lee HH, Lee JC, Joo YJ, Oh M, Lee CH, Appl. Energy, 131, 425 (2014)
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Weinan E, Engquist B, Li X, Ren W, Vanden-Eijnden E, Commun. Comput. Phys., 2(3), 367 (2007)
Ingram GD, Cameron IT, Hangos KM, Chem. Eng. Sci., 59(11), 2171 (2004)
Dada JO, Mendes P, Integr. Biol., 3(2), 86 (2011)
Yang AD, Marquardt W, Comput. Chem. Eng., 33(4), 822 (2009)
Hoekstra A, Chopard B, Coveney P, Philos. Trans. R. Soc. A Math. Phys. Eng. Sci., 372(2021), 201303 (2014)
Chopard B, Borgdorff J, Hoekstra AG, Philos. Trans. R. Soc. A Math. Phys. Eng. Sci., 372(2021), 201303 (2014)
Zitney SE, CAPE-OPEN integration for advanced process engineering co-simulation, Final Report. DOE/NETL-IR-2007.
Zaversky F, Garcia-Barberena J, Sanchez M, Astrain D, Sol. Energy, 93, 294 (2013)
Jarvis RB, Pantelides CC, Robust dynamic simulation of chemical engineering processes, PhD Thesis, Imperial College London University (1993).
Shelton W, Lyons J, Shell gasifier IGCC base cases, Report. NETL PED-IGCC-98-002 (2000).
Boukelia TE, Mecibah MS, Kumar BN, Reddy KS, Energy, 88, 292 (2015)
Dunn RI, Hearps PJ, Wright MN, Proc. IEEE, 100(2), 504 (2012)
Lee WS, Lee JC, Oh HT, Baek SW, Oh M, Lee CH, Energy, 134, 731 (2017)
Schulte-Fischedick J, Tamme R, Herrmann U, Ameri. Soc. of Mech. Eng., 2, 515 (2008).