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An Interval Optimization-Based Approach for Electric–Heat–Gas Coupled Energy System Planning Considering the Correlation between Uncertainties

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  • Wenshi Wang

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China)

  • Houqi Dong

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China)

  • Yangfan Luo

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China)

  • Changhao Zhang

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China)

  • Bo Zeng

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China)

  • Fuqiang Xu

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China)

  • Ming Zeng

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China)

Abstract

In this paper, a novel methodological framework for energy hub (EH) planning, considering the correlation between renewable energy source (RES) and demand response (DR) uncertainties, is proposed. Unlike other existing works, our study explicitly considers the potential correlation between the uncertainty of integrated energy system operations (i.e., wind speed, light intensity, and demand response). Firstly, an EH single-objective interval optimization model is established, which aims at minimizing investment and operation costs. The model fully considers the correlation between various uncertain parameters. Secondly, the correlation between uncertainties is dealt with by the interval models of multidimensional parallelism and affine coordinate transformation, which are transformed into a deterministic optimization problem by the interval order relationship and probability algorithm, and then solved by a genetic algorithm. Finally, an experimental case is analyzed, and the results show that the research method in this paper has good engineering practicability. At the same time, different correlations among uncertainties have different influences on integrated energy system planning. Correlation and influence are positively correlated.

Suggested Citation

  • Wenshi Wang & Houqi Dong & Yangfan Luo & Changhao Zhang & Bo Zeng & Fuqiang Xu & Ming Zeng, 2021. "An Interval Optimization-Based Approach for Electric–Heat–Gas Coupled Energy System Planning Considering the Correlation between Uncertainties," Energies, MDPI, vol. 14(9), pages 1-24, April.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:9:p:2457-:d:543428
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    References listed on IDEAS

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    1. Reuter, Wolf Heinrich & Szolgayová, Jana & Fuss, Sabine & Obersteiner, Michael, 2012. "Renewable energy investment: Policy and market impacts," Applied Energy, Elsevier, vol. 97(C), pages 249-254.
    2. Davide Borelli & Francesco Devia & Ermanno Lo Cascio & Corrado Schenone & Alessandro Spoladore, 2016. "Combined Production and Conversion of Energy in an Urban Integrated System," Energies, MDPI, vol. 9(10), pages 1-17, October.
    3. Habibollah Raoufi & Vahid Vahidinasab & Kamyar Mehran, 2020. "Power Systems Resilience Metrics: A Comprehensive Review of Challenges and Outlook," Sustainability, MDPI, vol. 12(22), pages 1-24, November.
    4. António Couto & Ana Estanqueiro, 2020. "Exploring Wind and Solar PV Generation Complementarity to Meet Electricity Demand," Energies, MDPI, vol. 13(16), pages 1-21, August.
    5. Hemmati, S. & Ghaderi, S.F. & Ghazizadeh, M.S., 2018. "Sustainable energy hub design under uncertainty using Benders decomposition method," Energy, Elsevier, vol. 143(C), pages 1029-1047.
    6. Xiaofeng Dong & Chao Quan & Tong Jiang, 2018. "Optimal Planning of Integrated Energy Systems Based on Coupled CCHP," Energies, MDPI, vol. 11(10), pages 1-27, October.
    7. Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.
    8. Liu, Wenxia & Huang, Yuchen & Li, Zhengzhou & Yang, Yue & Yi, Fang, 2020. "Optimal allocation for coupling device in an integrated energy system considering complex uncertainties of demand response," Energy, Elsevier, vol. 198(C).
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    Cited by:

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