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Co-optimization planning of integrated electricity and district heating systems based on improved quadratic convex relaxation

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  • Wang, Xu
  • Bie, Zhaohong
  • Liu, Fan
  • Kou, Yu

Abstract

The rapid growth of combined heat and power (CHP) units has led to the development of integrated electricity and district heating systems (IEHS). To support the design of a highly efficient energy supply system, this paper proposes a long-term co-optimization planning model for an IEHS. Not only CHP units, non-CHP thermal generators, wind farms and electric boilers but also transmission lines and heat pipelines are considered as investment candidates to meet electricity and heat demands. Nonlinear hydraulic conditions and thermal conditions are adopted to precisely capture the characteristics of the heating system. To make the planning model tractable, the nonlinear hydraulic conditions are approximated through piecewise linearization. Based on the introduction of auxiliary variables, the nonconvex thermal conditions are reformulated into linear constraints through quadratic convex relaxation. Hence, the planning model is converted into a large-scale mixed integer linear programming (MILP) problem. Since the planning model is formulated based on independent load blocks, a parallel Benders decomposition algorithm combined with the sequential bound-tightening procedure is proposed to efficiently obtain high-quality solutions. Numerical cases are studied based on two IEHSs of different scales to validate the effectiveness of the proposed co-optimization planning model and the feasibility of the proposed solution methods for solving this complicated planning model for an IEHS.

Suggested Citation

  • Wang, Xu & Bie, Zhaohong & Liu, Fan & Kou, Yu, 2021. "Co-optimization planning of integrated electricity and district heating systems based on improved quadratic convex relaxation," Applied Energy, Elsevier, vol. 285(C).
  • Handle: RePEc:eee:appene:v:285:y:2021:i:c:s0306261921000076
    DOI: 10.1016/j.apenergy.2021.116439
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    References listed on IDEAS

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    1. Liu, Xuezhi & Wu, Jianzhong & Jenkins, Nick & Bagdanavicius, Audrius, 2016. "Combined analysis of electricity and heat networks," Applied Energy, Elsevier, vol. 162(C), pages 1238-1250.
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    4. Blarke, Morten B., 2012. "Towards an intermittency-friendly energy system: Comparing electric boilers and heat pumps in distributed cogeneration," Applied Energy, Elsevier, vol. 91(1), pages 349-365.
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    Citations

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    Cited by:

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    2. Jona Maurer & Jochen Illerhaus & Pol Jané Soneira & Sören Hohmann, 2022. "Distributed Optimization of District Heating Networks Using Optimality Condition Decomposition," Energies, MDPI, vol. 15(18), pages 1-21, September.
    3. Chen, Zhang & Liu, Jun & Liu, Xinglei, 2022. "GPU accelerated power flow calculation of integrated electricity and heat system with component-oriented modeling of district heating network," Applied Energy, Elsevier, vol. 305(C).
    4. Huang, Yan & Ju, Yuntao & Ma, Kang & Short, Michael & Chen, Tao & Zhang, Ruosi & Lin, Yi, 2022. "Three-phase optimal power flow for networked microgrids based on semidefinite programming convex relaxation," Applied Energy, Elsevier, vol. 305(C).
    5. Zhang, Chaoyi & Jiao, Zaibin & Liu, Junshan & Ning, Keer, 2023. "Robust planning and economic analysis of park-level integrated energy system considering photovoltaic/thermal equipment," Applied Energy, Elsevier, vol. 348(C).
    6. Liu, Miaomiao & Liu, Ming & Chen, Weixiong & Yan, Junjie, 2023. "Operational flexibility and operation optimization of CHP units supplying electricity and two-pressure steam," Energy, Elsevier, vol. 263(PE).
    7. Ghaemi, Zahra & Tran, Thomas T.D. & Smith, Amanda D., 2022. "Comparing classical and metaheuristic methods to optimize multi-objective operation planning of district energy systems considering uncertainties," Applied Energy, Elsevier, vol. 321(C).
    8. Wang, Yongli & Huang, Feifei & Tao, Siyi & Ma, Yang & Ma, Yuze & Liu, Lin & Dong, Fugui, 2022. "Multi-objective planning of regional integrated energy system aiming at exergy efficiency and economy," Applied Energy, Elsevier, vol. 306(PB).

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