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Research on Multiobjective Optimization Strategy of Economic/Environmental Energy Management for Multi-energy Ship Based on MOEA/D

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Bio-inspired Computing: Theories and Applications (BIC-TA 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1159))

Abstract

The economic/environmental energy management (EEEM) for multi-energy ship is to optimize the output power of the generation devices in the power system to meet the load demand and navigation speed need as well as satisfy the practical constraints, while decreasing both operation cost and pollutants simultaneously. Aiming at the frequently changing problem of the optimization model of EEEM for multi-energy ship, this paper proposed an optimization method based on improved multiobjective evolutionary algorithm based on decomposition (MOEA/D) framework. To deal with various types of constraints in the practical EEEM problem, a constraints handling approach is suggested to replace the method utilized in original Non-dominated Sorting Genetic Algorithm II (NSGAII). Thereafter, the improved algorithm is applied to three typical EEEM for multi-energy ship with different combinations of power generation devices. The efficiency of the algorithm is verified and the simulation results obtained can meet the navigation speed requirements as well as reduce the operation cost and emissions.

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Author information

Authors and Affiliations

  1. China Ship Development and Design Centre, Wuhan, 430064, China

    Xi Chen & Qinqi Wei

  2. School of Energy and Power Engineering, Wuhan University of Technology, Wuhan, 430063, China

    Xin Li

Authors
  1. Xi Chen
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  2. Qinqi Wei
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  3. Xin Li
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Corresponding author

Correspondence to Xin Li .

Editor information

Editors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  2. Zhengzhou University, Zhengzhou, China

    Jing Liang

  3. Zhongyuan University of Technology, Zhengzhou, China

    Boyang Qu

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Chen, X., Wei, Q., Li, X. (2020). Research on Multiobjective Optimization Strategy of Economic/Environmental Energy Management for Multi-energy Ship Based on MOEA/D. In: Pan, L., Liang, J., Qu, B. (eds) Bio-inspired Computing: Theories and Applications. BIC-TA 2019. Communications in Computer and Information Science, vol 1159. Springer, Singapore. https://doi.org/10.1007/978-981-15-3425-6_12

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  • DOI: https://doi.org/10.1007/978-981-15-3425-6_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3424-9

  • Online ISBN: 978-981-15-3425-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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