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Study on Multiobjective Modeling and Optimization of Offshore Micro Integrated Energy System considering Uncertainty of Load and Wind Power

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  • Jun Wu
  • Baolin Li
  • Jun Chen
  • Qinghui Lou
  • Xiangyu Xing
  • Xuedong Zhu

Abstract

Offshore micro integrated energy systems (OMIESs) are the basis of offshore oil and gas engineering and play an important role in developing and utilizing marine resources. By introducing offshore wind power generation, the carbon emissions of offshore micro integrated energy systems can be effectively reduced; however, greater challenges have been posted to the reliable operation due to the uncertainty. To reduce the influence brought by the uncertainty, a multiobjective optimization model was proposed based on the chance-constrained programming (CCP); the operating cost and penalty cost of natural gas emission were selected as objectives. Then, the improved hybrid constraints handling strategy based on nondominated sorting genetic algorithm II (IHCHS-NSGAII) was introduced to solve the model efficiently. Finally, the numerical studies verified the efficiency of the proposed algorithm, as well as the validity and feasibility of the proposed model in improving the economy of OMIES under uncertainty.

Suggested Citation

  • Jun Wu & Baolin Li & Jun Chen & Qinghui Lou & Xiangyu Xing & Xuedong Zhu, 2020. "Study on Multiobjective Modeling and Optimization of Offshore Micro Integrated Energy System considering Uncertainty of Load and Wind Power," Complexity, Hindawi, vol. 2020, pages 1-13, December.
  • Handle: RePEc:hin:complx:8820332
    DOI: 10.1155/2020/8820332
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    Cited by:

    1. Wiegner, J.F. & Andreasson, L.M. & Kusters, J.E.H. & Nienhuis, R.M., 2024. "Interdisciplinary perspectives on offshore energy system integration in the North Sea: A systematic literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).

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