Design and optimization of steam power systems in industrial parks based on the distributed steam turbine system

doi:10.1016/j.cjche.2024.10.011

中国化学工程学报 ›› 2025, Vol. 77 ›› Issue (1): 259-272.DOI: 10.1016/j.cjche.2024.10.011

Design and optimization of steam power systems in industrial parks based on the distributed steam turbine system

Lingwei Zhang, Ziyuan Cui, Yufei Wang

School of Chemical Engineering and Environment, China University of Petroleum (Beijing), Beijing 102249, China

收稿日期:2024-06-16 修回日期:2024-10-04 接受日期:2024-10-08 出版日期:2025-01-28 发布日期:2024-11-28
通讯作者: Yufei Wang,E-mail:wangyufei@cup.edu.cn
基金资助:
Financial support from the National Natural Science Foundation of China under Grant (22393954 and 22078358) is gratefully acknowledged.

Design and optimization of steam power systems in industrial parks based on the distributed steam turbine system

Lingwei Zhang, Ziyuan Cui, Yufei Wang

School of Chemical Engineering and Environment, China University of Petroleum (Beijing), Beijing 102249, China

Received:2024-06-16 Revised:2024-10-04 Accepted:2024-10-08 Online:2025-01-28 Published:2024-11-28
Contact: Yufei Wang,E-mail:wangyufei@cup.edu.cn
Supported by:
Financial support from the National Natural Science Foundation of China under Grant (22393954 and 22078358) is gratefully acknowledged.

摘要/Abstract

摘要： Steam power systems (SPSs) in industrial parks are the typical utility systems for heat and electricity supply. In SPSs, electricity is generated by steam turbines, and steam is generally produced and supplied at multiple levels to serve the heat demands of consumers with different temperature grades, so that energy is utilized in cascade. While a large number of steam levels enhances energy utilization efficiency, it also tends to cause a complex steam pipeline network in the industrial park. In practice, a moderate number of steam levels is always adopted in SPSs, leading to temperature mismatches between heat supply and demand for some consumers. This study proposes a distributed steam turbine system (DSTS) consisting of main steam turbines on the energy supply side and auxiliary steam turbines on the energy consumption side, aiming to balance the heat production costs, the distance-related costs, and the electricity generation of SPSs in industrial parks. A mixed-integer nonlinear programming model is established for the optimization of SPSs, with the objective of minimizing the total annual cost (TAC). The optimal number of steam levels and the optimal configuration of DSTS for an industrial park can be determined by solving the model. A case study demonstrates that the TAC of the SPS is reduced by 220.6×10³ USD (2.21%) through the arrangement of auxiliary steam turbines. The sub-optimal number of steam levels and a non-optimal operating condition slightly increase the TAC by 0.46% and 0.28%, respectively. The sensitivity analysis indicates that the optimal number of steam levels tends to decrease from 3 to 2 as electricity price declines.

关键词: Industrial parks, Steam power systems, Distributed steam turbine system, Mixed-integer nonlinear programming, Optimization, Enthalpy

Abstract: Steam power systems (SPSs) in industrial parks are the typical utility systems for heat and electricity supply. In SPSs, electricity is generated by steam turbines, and steam is generally produced and supplied at multiple levels to serve the heat demands of consumers with different temperature grades, so that energy is utilized in cascade. While a large number of steam levels enhances energy utilization efficiency, it also tends to cause a complex steam pipeline network in the industrial park. In practice, a moderate number of steam levels is always adopted in SPSs, leading to temperature mismatches between heat supply and demand for some consumers. This study proposes a distributed steam turbine system (DSTS) consisting of main steam turbines on the energy supply side and auxiliary steam turbines on the energy consumption side, aiming to balance the heat production costs, the distance-related costs, and the electricity generation of SPSs in industrial parks. A mixed-integer nonlinear programming model is established for the optimization of SPSs, with the objective of minimizing the total annual cost (TAC). The optimal number of steam levels and the optimal configuration of DSTS for an industrial park can be determined by solving the model. A case study demonstrates that the TAC of the SPS is reduced by 220.6×10³ USD (2.21%) through the arrangement of auxiliary steam turbines. The sub-optimal number of steam levels and a non-optimal operating condition slightly increase the TAC by 0.46% and 0.28%, respectively. The sensitivity analysis indicates that the optimal number of steam levels tends to decrease from 3 to 2 as electricity price declines.

Key words: Industrial parks, Steam power systems, Distributed steam turbine system, Mixed-integer nonlinear programming, Optimization, Enthalpy

Lingwei Zhang, Ziyuan Cui, Yufei Wang. Design and optimization of steam power systems in industrial parks based on the distributed steam turbine system[J]. 中国化学工程学报, 2025, 77(1): 259-272.

Lingwei Zhang, Ziyuan Cui, Yufei Wang. Design and optimization of steam power systems in industrial parks based on the distributed steam turbine system[J]. Chinese Journal of Chemical Engineering, 2025, 77(1): 259-272.

参考文献

[1] IEA, World Energy Outlook 2023, International Energy Agency, Paris, 2023.
[2] C.L. Chen, C.Y. Lin, J.Y. Lee, Retrofit of steam power plants in a petroleum refinery, Appl. Therm. Eng. 61(1) (2013) 7-16.
[3] D.W. Townsend, B. Linnhoff, Heat and power networks in process design. part II: Design procedure for equipment selection and process matching, AlChE. J. 29(5) (1983) 748-771.
[4] V.R. Dhole, B. Linnhoff, Total site targets for fuel, co-generation, emissions, and cooling, Comput. Chem. Eng. 17(1993) S101-S109.
[5] K. Raissi, Total site integration, Ph. D. Thesis, UMIST, U.K., 1994.
[6] L. Sun, S. Doyle, R. Smith, Heat recovery and power targeting in utility systems, Energy 84(2015) 196-206.
[7] Y. Shokri, M. Ghazi, M. Nikiyan, A. Maleki, M.A. Rosen, Optimal equipment arrangement of a total site for cogeneration of thermal and electrical energy by using exergoeconomic approach, Energy Rep. 7(2021) 5330-5343.
[8] B. Wang, J.J. Klemes, P.S. Varbanov, K. Shahzad, M.R. Kabli, Total Site Heat Integration benefiting from geothermal energy for heating and cooling implementations, J. Environ. Manage. 290(2021) 112596.
[9] S.A. Papoulias, I.E. Grossmann, A structural optimization approach in process synthesis-I utility systems, Comput. Chem. Eng. 7(6) (1983) 695-706.
[10] S.P. Mavromatis, A.C. Kokossis, Conceptual optimisation of utility networks for operational variations-I. targets and level optimisation, Chem. Eng. Sci. 53(8) (1998) 1585-1608.
[11] P.S. Varbanov, S. Doyle, R. Smith, Modelling and Optimization of Utility Systems, Chem. Eng. Res. Des. 82(5) (2004) 561-578.
[12] O. Aguilar, S.J. Perry, J.K. Kim, R. Smith, Design and optimization of flexible utility systems subject to variable conditions part 1: Modelling framework, Chem. Eng. Res. Des. 85(8) (2007) 1136-1148.
[13] O. Aguilar, S.J. Perry, J.K. Kim, R. Smith, Design and optimization of flexible utility systems subject to variable conditions part 2: Methodology and applications, Chem. Eng. Res. Des. 85(8) (2007) 1149-1168.
[14] Z.G. Shang, A. Kokossis, A transhipment model for the optimisation of steam levels of total site utility system for multiperiod operation, Comput. Chem. Eng. 28(9) (2004) 1673-1688.
[15] L. Sun, C. Liu, Reliable and flexible steam and power system design, Appl. Therm. Eng. 79(2015) 184-191.
[16] J.C. Bruno, F. Fernandez, F. Castells, I.E. Grossmann, A rigorous MINLP model for the optimal synthesis and operation of utility plants, Chem. Eng. Res. Des. 76(3) (1998) 246-258.
[17] C.L. Chen, C.Y. Lin, A flexible structural and operational design of steam systems, Appl. Therm. Eng. 31(13) (2011) 2084-2093.
[18] L. Zhao, F.Q. You, A data-driven approach for industrial utility systems optimization under uncertainty, Energy 182(2019) 559-569.
[19] H. Zhao, G. Rong, Y.P. Feng, Effective solution approach for integrated optimization models of refinery production and utility system, Ind. Eng. Chem. Res. 54(37) (2015) 9238-9250.
[20] J. Jimenez-Romero, A. Azapagic, R. Smith, Style: A new optimization model for Synthesis of uTility sYstems with steam LEvel placement, Comput. Chem. Eng. 170(2023) 108060.
[21] J. Jimenez-Romero, A. Azapagic, R. Smith, BEELINE: BilevEl dEcomposition aLgorithm for synthesis of Industrial eNergy systEms, Comput. Chem. Eng. 180(2024) 108406.
[22] C.L. Chang, Y.F. Wang, X. Feng, Optimal synthesis of multi-plant heat exchanger networks considering both direct and indirect methods, Chin. J. Chem. Eng. 28(2) (2020) 456-465.
[23] C.A. Kastner, R. Lau, M. Kraft, Quantitative tools for cultivating symbiosis in industrial parks; a literature review, Appl. Energy 155(2015) 599-612.
[24] Z.Y. Cui, H. Lin, Y. Wu, Y.F. Wang, X. Feng, Optimization of pipeline network layout for multiple heat sources distributed energy systems considering reliability evaluation, Processes 9(8) (2021) 1308.
[25] K. Ravi Kumar, N.V.V. Krishna Chaitanya, N. Sendhil Kumar, Solar thermal energy technologies and its applications for process heating and power generation-A review, J. Clean. Prod. 282(2021) 125296.
[26] Y. Wu, R.Q. Wang, Y.F. Wang, X. Feng, An area-wide layout design method considering piecewise steam piping and energy loss, Chem. Eng. Res. Des. 138(2018) 405-417.
[27] W. Wagner, J.R. Cooper, A. Dittmann, J. Kijima, H.-J. Kretzschmar, A. Kruse, R. Mares, K. Oguchi, H. Sato, I. Stocker, O. Sifner, Y. Takaishi, I. Tanishita, J. Trubenbach, T. Willkommen, The IAPWS Industrial Formulation 1997 for the Thermodynamic Properties of Water and Steam, J. Eng. Gas Turbines Power 122(2000) 150-182.
[28] F.K. Hwang, On steiner minimal trees with rectilinear distance, SIAM J. Appl. Math. 30(1) (1976) 104-114.
[29] H. Singh, Minimisation of Flue Gas Emissions for Chemical Process Industries, Ph. D. Thesis, UMIST, U.K., 1997.
[30] M.Z. Stijepovic, P. Linke, Optimal waste heat recovery and reuse in industrial zones, Energy 36(7) (2011) 4019-4031.
[31] S. Huang, F. Sun, D. Sheng, H. Liu, S. Tu, J. Yang, S. Li, Y. Yang, Principles of steam Turbines, China Electric Power Press, Beijing, 2008.
[32] C.L. Chen, C.Y. Lin, Design of entire energy system for chemical plants, Ind. Eng. Chem. Res. 51(30) (2012) 9980-9996.
[33] J.Z. Ma, Y.F. Wang, X. Feng, Simultaneous optimization of pump and cooler networks in a cooling water system, Appl. Therm. Eng. 125(2017) 377-385.
[34] A. Brooke, D. Kendrick, A. Meeraus, GAMS: A user’s guide, Release 2.25, Technical Report. GAMS Development Corporation, Washington, DC (EUA), 1992.

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