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Multi-Objective Optimal Operation for Steam Power Scheduling Based on Economic and Exergetic Analysis

Author

Listed:
  • Yu Huang

    (Department of Automation, North China Electric Power University, Baoding 071003, China)

  • Weizhen Hou

    (Department of Automation, North China Electric Power University, Baoding 071003, China)

  • Yiran Huang

    (Department of Engineering Electronics and Communication Engineering, North China Electric Power University, Baoding 071003, China)

  • Jiayu Li

    (Department of Automation, North China Electric Power University, Baoding 071003, China)

  • Qixian Li

    (Department of Automation, North China Electric Power University, Baoding 071003, China)

  • Dongfeng Wang

    (Department of Automation, North China Electric Power University, Baoding 071003, China)

  • Yan Zhang

    (Department of Automation, North China Electric Power University, Baoding 071003, China)

Abstract

Steam supply scheduling (SSS) plays an important role in providing uninterrupted reliable energy to meet the heat and electricity demand in both the industrial and residential sectors. However, the system complexity makes it challenging to operate efficiently. Besides, the operational objectives in terms of economic cost and thermodynamic efficiency are usually contradictory, making the online scheduling even more intractable. To this end, the thermodynamic efficiency is evaluated based on exergetic analysis in this paper, and an economic-exergetic optimal scheduling model is formulated into a mixed-integer linear programming (MILP) problem. Moreover, the ε -constraint method is used to obtain the Pareto front of the multi-objective optimization model, and fuzzy satisfying approach is introduced to decide the unique operation strategy of the SSS. In the single-period case results, compared with the optimal scheduling which only takes the economic index as the objective function, the operation cost of the multi-objective optimization is increased by 4.59%, and the exergy efficiency is increased by 9.3%. Compared with the optimal scheduling which only takes the exergetic index as the objective function, the operation cost of the multi-objective optimization is decreased by 19.83%, and the exergy efficiency is decreased by 2.39%. Furthermore, results of single-period and multi-period multi-objective optimal scheduling verify the effectiveness of the model and the solution proposed in this study.

Suggested Citation

  • Yu Huang & Weizhen Hou & Yiran Huang & Jiayu Li & Qixian Li & Dongfeng Wang & Yan Zhang, 2020. "Multi-Objective Optimal Operation for Steam Power Scheduling Based on Economic and Exergetic Analysis," Energies, MDPI, vol. 13(8), pages 1-18, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:8:p:1886-:d:344850
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    References listed on IDEAS

    as
    1. Ahmadi, Gholamreza & Toghraie, Davood & Akbari, Omidali, 2019. "Energy, exergy and environmental (3E) analysis of the existing CHP system in a petrochemical plant," Renewable and Sustainable Energy Reviews, Elsevier, vol. 99(C), pages 234-242.
    2. Luo, Xianglong & Zhang, Bingjian & Chen, Ying & Mo, Songping, 2011. "Modeling and optimization of a utility system containing multiple extractions steam turbines," Energy, Elsevier, vol. 36(5), pages 3501-3512.
    3. Zeng, Yujiao & Xiao, Xin & Li, Jie & Sun, Li & Floudas, Christodoulos A. & Li, Hechang, 2018. "A novel multi-period mixed-integer linear optimization model for optimal distribution of byproduct gases, steam and power in an iron and steel plant," Energy, Elsevier, vol. 143(C), pages 881-899.
    4. Zhao, Liang & You, Fengqi, 2019. "A data-driven approach for industrial utility systems optimization under uncertainty," Energy, Elsevier, vol. 182(C), pages 559-569.
    5. Dorotić, Hrvoje & Pukšec, Tomislav & Duić, Neven, 2019. "Economical, environmental and exergetic multi-objective optimization of district heating systems on hourly level for a whole year," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    6. Luo, Xianglong & Zhang, Bingjian & Chen, Ying & Mo, Songping, 2013. "Operational planning optimization of steam power plants considering equipment failure in petrochemical complex," Applied Energy, Elsevier, vol. 112(C), pages 1247-1264.
    7. Yu Huang & Shuqin Li & Peng Ding & Yan Zhang & Kai Yang & Weiting Zhang, 2019. "Optimal Operation for Economic and Exergetic Objectives of a Multiple Energy Carrier System Considering Demand Response Program," Energies, MDPI, vol. 12(20), pages 1-21, October.
    8. Douglas, Tamunosaki & Big-Alabo, Akuro, 2018. "A generic algorithm of sustainability (GAS) function for industrial complex steam turbine and utility system optimisation," Energy, Elsevier, vol. 164(C), pages 881-897.
    9. Morosuk, Tatiana & Tsatsaronis, George, 2019. "Advanced exergy-based methods used to understand and improve energy-conversion systems," Energy, Elsevier, vol. 169(C), pages 238-246.
    10. Sun, Li & Gai, Limei & Smith, Robin, 2017. "Site utility system optimization with operation adjustment under uncertainty," Applied Energy, Elsevier, vol. 186(P3), pages 450-456.
    11. Wang, Jiangjiang & Chen, Yuzhu & Lior, Noam & Li, Weihua, 2019. "Energy, exergy and environmental analysis of a hybrid combined cooling heating and power system integrated with compound parabolic concentrated-photovoltaic thermal solar collectors," Energy, Elsevier, vol. 185(C), pages 463-476.
    12. Sun, Li & Shen, Jiong & Hua, Qingsong & Lee, Kwang Y., 2018. "Data-driven oxygen excess ratio control for proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 231(C), pages 866-875.
    13. Ahmadi, Pouria & Dincer, Ibrahim, 2010. "Exergoenvironmental analysis and optimization of a cogeneration plant system using Multimodal Genetic Algorithm (MGA)," Energy, Elsevier, vol. 35(12), pages 5161-5172.
    14. Sevinchan, Eren & Dincer, Ibrahim & Lang, Haoxiang, 2019. "Energy and exergy analyses of a biogas driven multigenerational system," Energy, Elsevier, vol. 166(C), pages 715-723.
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