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Design and analysis of a renewable energy power system for shale oil exploitation using hierarchical optimization

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  • Yang, Xiyun
  • Liu, Siqu
  • Zhang, Le
  • Su, Jianzheng
  • Ye, Tianze

Abstract

The exploitation of shale oil resources has attracted the wide attention. Using traditional fossil fuel as power supply for shale oil in-situ electric heating mining has an impact on the environment. In this paper, we propose a renewable energy microgrid system as a power supply for in-situ heating mining system of shale oil. A hierarchical optimization model was developed to optimize the capacity allocation of the microgrid components, which employs HOMER to initial optimization, then an improved multi-objective particle swarm algorithm with the lowest the economic cost function and the annual load shortage rate index of the system is implemented. A hierarchical hybrid strategy game method is used to screen the generated Pareto set to meet the different preferences of decision-makers. The sensitivity analysis of system reserve capacity, wind resources, and wind turbine prices was carried out. The simulation results using data from a demonstration project in China verified that the proposed method optimized the use of renewable energy, reduced the operating costs and produced positive environmental benefits. The results of this study provide a useful reference for decision-makers to plan the power supply scheme of shale oil extraction by in-situ electric heating.

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  • Yang, Xiyun & Liu, Siqu & Zhang, Le & Su, Jianzheng & Ye, Tianze, 2020. "Design and analysis of a renewable energy power system for shale oil exploitation using hierarchical optimization," Energy, Elsevier, vol. 206(C).
    • Handle: RePEc:eee:energy:v:206:y:2020:i:c:s0360544220311853
    DOI: 10.1016/j.energy.2020.118078
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    Cited by:

    1. Yinghao Shan & Liqian Ma & Xiangkai Yu, 2023. "Hierarchical Control and Economic Optimization of Microgrids Considering the Randomness of Power Generation and Load Demand," Energies, MDPI, vol. 16(14), pages 1-23, July.
    2. Wu, Kunming & Li, Qiang & Chen, Ziyu & Lin, Jiayang & Yi, Yongli & Chen, Minyou, 2021. "Distributed optimization method with weighted gradients for economic dispatch problem of multi-microgrid systems," Energy, Elsevier, vol. 222(C).
    3. Demirci, Alpaslan & Öztürk, Zafer & Tercan, Said Mirza, 2023. "Decision-making between hybrid renewable energy configurations and grid extension in rural areas for different climate zones," Energy, Elsevier, vol. 262(PA).

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