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Economic-emission–constrained multi-objective hybrid optimal energy flow of integrated energy systems

Author

Listed:
  • Binning Fan
  • Longji Hu
  • Zhiguo Fan
  • Aifeng Liu
  • Lijun Yan
  • Fengjuan Xie
  • Zhenyu Liu

Abstract

The energy flow optimization is important to the operation, planning and trading of integrated energy systems. Based on the energy hub (EH) model, this paper establishes a multi-objective hybrid optimal energy flow model for integrated energy systems that consider operation economy and pollution gas emissions. Power grid constraints, gas grid constraints and EH constraints are involved in the proposed model. The non-dominated improved genetic algorithm (NSGA-II) and particle swarm optimization algorithm combined solution method is used to solve the proposed multi-objective hybrid optimal energy flow model. The results show that the proposed model can balance the operation economy and pollution gas emission according to the difference of energy price and load demand. It can flexibly change the transformation and utilization mode of natural gas to provide more operation solutions for operators and realize more rational utilization of energy.

Suggested Citation

  • Binning Fan & Longji Hu & Zhiguo Fan & Aifeng Liu & Lijun Yan & Fengjuan Xie & Zhenyu Liu, 2023. "Economic-emission–constrained multi-objective hybrid optimal energy flow of integrated energy systems," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 18, pages 265-272.
    • Handle: RePEc:oup:ijlctc:v:18:y:2023:i::p:265-272.
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    References listed on IDEAS

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    3. Daniel De Wolf & Yves Smeers, 2000. "The Gas Transmission Problem Solved by an Extension of the Simplex Algorithm," Management Science, INFORMS, vol. 46(11), pages 1454-1465, November.
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