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Under the low-carbon energy development, a large number of distributed generation (DG) and new controllable resources are widely integrated into the distribution network. This transformation turns the distribution network into a more complex active distribution network (ADN), posing new challenges for the optimal operation of the distribution network. Consequently, the demand for efficient optimization of large-scale ADN is becoming increasingly urgent. This paper proposed an efficient optimization algorithm for large-scale and based on C++. First, the optimization model of complex ADNs considering the integration of DG and energy storage systems (ESS) is established based on second-order cone programming (SOCP) theory. Then, a modular and extensible algorithm program based on the C++ language is designed and implemented. Finally, the algorithm’s accuracy, effectiveness, and computational efficiency are analyzed and verified using the IEEE 33-bus test system and several large-scale modified test cases. This research provides a new method and practical tool for the optimization of large-scale ADN, holding theoretical and practical implications.

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Research and Implementation of Efficient Large-Scale Optimization Algorithms for Operation of Active Distribution Systems

  • 会议论文

  • 发表日期：

    2025年

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  • Xinhao Lin,
  • Zerui Yuanlv,
  • Shuyin Duan,
  • Lei Yu,
  • Hao Yang,
  • Xupeng Liu,
  • Zhaoyuan Wang,
  • Jie Jian

摘要

Under the low-carbon energy development, a large number of distributed generation (DG) and new controllable resources are widely integrated into the distribution network. This transformation turns the distribution network into a more complex active distribution network (ADN), posing new challenges for the optimal operation of the distribution network. Consequently, the demand for efficient optimization of large-scale ADN is becoming increasingly urgent. This paper proposed an efficient optimization algorithm for large-scale and based on C++. First, the optimization model of complex ADNs considering the integration of DG and energy storage systems (ESS) is established based on second-order cone programming (SOCP) theory. Then, a modular and extensible algorithm program based on the C++ language is designed and implemented. Finally, the algorithm’s accuracy, effectiveness, and computational efficiency are analyzed and verified using the IEEE 33-bus test system and several large-scale modified test cases. This research provides a new method and practical tool for the optimization of large-scale ADN, holding theoretical and practical implications.