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Enhanced evolutionary multi-objective optimization-based dispatch of coal mine integrated energy system with flexible load

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  • Hu, Hejuan
  • Sun, Xiaoyan
  • Zeng, Bo
  • Gong, Dunwei
  • Zhang, Yong

Abstract

Integrated energy systems, especially park-level ones, have attracted great attention since such structures lay the foundation of multi-energy complementary and cascade utilization of energy. Integrated energy systems for industries with associated multiple energy generated during the production process have not been explored. Here, we focus on the integrated energy systems for mine industry due to its high ecological requirements, i.e., the associated underground wastewater, mine gas, ventilation air methane, and geothermal should be sufficiently recycled and released as little as possible into nature. To this end, we first present a structure for coal mine integrated energy systems by integrating these forms of associated energy together with some flexible load. The multi-objective dispatch model of the system is then derived by considering the economic cost, carbon transaction cost for environment protection and degree of customer dissatisfaction for reducible and translational load. An enhanced evolutionary multi-objective algorithm by considering the time-series constrictions of the flexible load is further explored to efficiently obtain a set of solutions of the multi-objective dispatch. The presented algorithm is applied to a coal mine with multiple scenarios, and the results demonstrate the feasibility of our model and the effectiveness of the evolutionary multi-objective algorithm-based dispatch.

Suggested Citation

  • Hu, Hejuan & Sun, Xiaoyan & Zeng, Bo & Gong, Dunwei & Zhang, Yong, 2022. "Enhanced evolutionary multi-objective optimization-based dispatch of coal mine integrated energy system with flexible load," Applied Energy, Elsevier, vol. 307(C).
    • Handle: RePEc:eee:appene:v:307:y:2022:i:c:s0306261921014070
    DOI: 10.1016/j.apenergy.2021.118130
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    References listed on IDEAS

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    Cited by:

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    3. Mingcheng Zuo & Yuan Xue, 2024. "Population Feasibility State Guided Autonomous Constrained Multi-Objective Evolutionary Optimization," Mathematics, MDPI, vol. 12(6), pages 1-24, March.
    4. Huang, Hongxu & Li, Zhengmao & Beng Gooi, Hoay & Qiu, Haifeng & Zhang, Xiaotong & Lv, Chaoxian & Liang, Rui & Gong, Dunwei, 2023. "Distributionally robust energy-transportation coordination in coal mine integrated energy systems," Applied Energy, Elsevier, vol. 333(C).
    5. Palani, Velmurugan & Vedavalli, S.P. & Veeramani, Vasan Prabhu & Sridharan, S., 2022. "Optimal operation of residential energy Hubs include Hybrid electric vehicle & Heat storage system by considering uncertainties of electricity price and renewable energy," Energy, Elsevier, vol. 261(PA).
    6. Dong, Yingchao & Zhang, Hongli & Ma, Ping & Wang, Cong & Zhou, Xiaojun, 2023. "A hybrid robust-interval optimization approach for integrated energy systems planning under uncertainties," Energy, Elsevier, vol. 274(C).
    7. Kalantari, Hosein & Ali Ghoreishi-Madiseh, Seyed, 2023. "Study of mine exhaust heat recovery with fully-coupled direct capture and indirect delivery systems," Applied Energy, Elsevier, vol. 334(C).
    8. Fengyuan Yan & Xiaolong Han & Qianwei Cheng & Yamin Yan & Qi Liao & Yongtu Liang, 2022. "Scenario-Based Comparative Analysis for Coupling Electricity and Hydrogen Storage in Clean Oilfield Energy Supply System," Energies, MDPI, vol. 15(6), pages 1-28, March.
    9. Friebe, Maximilian & Karasu, Arda & Kriegel, Martin, 2023. "Methodology to compare and optimize district heating and decentralized heat supply for energy transformation on a municipality level," Energy, Elsevier, vol. 282(C).
    10. Zhang, Anan & Zheng, Yadi & Huang, Huang & Ding, Ning & Zhang, Chengqian, 2022. "Co-integration theory-based cluster time-varying load optimization control model of regional integrated energy system," Energy, Elsevier, vol. 260(C).

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