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Nonlinear active distribution network optimization for improving the renewable energy power quality and economic efficiency: a multi-objective bald eagle search algorithm

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Abstract

The active distribution network (ADN) integrated optimization is the optimization of the system using three optimization techniques: reconfiguration, reactive power optimization and optimal configuration of distributed generation. This study establishes an optimization model of the renewable energy ADN and proposes a novel multi-objective bald eagle search algorithm to optimize the model. This study integrates three techniques of network reconfiguration, reactive power optimization and optimal configuration of distributed power sources to establish a comprehensive optimization model of ADN, which aims to reduce ADN energy losses, improve active distribution network power quality and economic efficiency. The contributions are as follows: (1) a multi-objective bald eagle search algorithm is proposed to deal with the complex nonlinear ADN integrated optimization problem, and its superiority is verified; (2) an ADN integrated optimization model is established; and (3) multiple scenarios are established in the IEEE33 node system for comparison and validation to verify the effectiveness of the proposed model. The results show that the proposed model can effectively improve the ADN operation with power loss, node voltage deviation and system cost reduced by 86.34%, 83.12% and 30.27%. The proposed algorism improves the power quality of ADN and promotes economic production and sustainable energy development.

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Funding

The authors have not disclosed any funding.

Author information

Authors and Affiliations

  1. Hengshui Power Supply Branch of State Grid Hebei Power Co., Ltd, Hengshui, 053000, China

    Haiyue Yang

  2. Hengshui Electric Power Design Co. LTD, Hengshui, 053000, China

    Haiyue Yang

  3. College of Electrical Engineering, Yancheng Institute of Technology, Yancheng, 224051, China

    Jiarong Li

  4. Institute of Innovation and Circular Economy, Asia University, Taichung, Taiwan

    Ming-Lang Tseng

  5. Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan

    Ming-Lang Tseng

  6. UKM-Graduate School of Business, Universiti Kebangsaan Malaysia, 43000, Bangi, Selangor, Malaysia

    Ming-Lang Tseng

  7. Institute of Project Management, Department of Leisure Industry Management, National Chin-Yi University of Technology, Taichung, 41170, Taiwan

    Ching-Hsin Wang

  8. School of Electrical Engineering, Hebei University of Technology, Tianjin, 300401, China

    Junlin Xiong & Lingling Li

Authors
  1. Haiyue Yang
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  2. Jiarong Li
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  4. Ching-Hsin Wang
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  5. Junlin Xiong
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  6. Lingling Li
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Contributions

Conceptualization was contributed by HY and JL; software, final version editing were contributed by LLL and MLT; methodology was contributed by CHW and JX; writing—original draft preparation was contributed by LLL, HY, JL and MLT. Authors have read and agreed to the published version of the manuscript.

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Correspondence to Ming-Lang Tseng.

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Yang, H., Li, J., Tseng, ML. et al. Nonlinear active distribution network optimization for improving the renewable energy power quality and economic efficiency: a multi-objective bald eagle search algorithm. Soft Comput 27, 16551–16569 (2023). https://doi.org/10.1007/s00500-023-08913-3

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