吉林大学学报(信息科学版) ›› 2026, Vol. 44 ›› Issue (3): 505-512.

• • 上一篇    下一篇

计及需求响应的主动配电网低碳优化调度

高金兰,李 凯,徐 爽   

  1. 东北石油大学电气信息工程学院,黑龙江大庆163318
  • 收稿日期:2025-05-07 出版日期:2026-06-02 发布日期:2026-06-02
  • 作者简介:高金兰(1978— ), 女, 山西运城人, 东北石油大学副教授, 硕士生导师, 主要从事电力系统运行与稳定、 新能源发电 研究, (Tel)86-13674596089(E-mail)jinlangao@163. com。
  • 基金资助:
    黑龙江省自然科学基金资助项目(LH2019E016)

Low-Carbon Optimal Scheduling of Active Distribution Networks Considering Demand Response

GAO Jinlan, LI Kai, XU Shuang   

  1. School of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163318, China
  • Received:2025-05-07 Online:2026-06-02 Published:2026-06-02

摘要: 针对电网运行中能量调度不佳和如何实现低碳运行的问题首先引入阶梯式碳交易机制和需求响应参与度, 建立需求侧响应模型和碳交易模型然后针对白鲨算法收敛精度差等缺点引入混沌初始化、定向更新策略和余弦变异策略以提升算法的性能最后以电网运行成本最小为目标建立主动配电网优化调度模型并用改进的算法求解模型。 仿真结果验证了所提模型的准确性和算法的高效性有效解决了能量调度不佳和如何低碳运行的问题。

关键词: 主动配电网, 改进的白鲨优化算法, 碳交易, 需求响应

Abstract: With growing demands for energy efficiency and carbon reduction in power grid operation, addressing the shortcomings of traditional scheduling approaches has become increasingly urgent. A hierarchical carbon trading mechanism is integrated with user-side responsiveness to construct a demand-side response model under carbon constraints. To enhance the solution process, the white shark optimizer is improved through chaotic initialization, directional update, and cosine mutation strategies, mitigating issues such as limited convergence accuracy and susceptibility to local optima. An optimal scheduling model for the active distribution network is formulated, targeting the minimization of operational costs. The refined algorithm is employed to solve the model, with simulation outcomes demonstrating its effectiveness and accuracy. Experimental results indicate that the proposed method significantly improves energy scheduling performance while supporting low-carbon objectives, and holds potential for broader application in smart grids incorporating renewable energy sources.

Key words: active distribution network, improved white shark optimization algorithm, carbon trading,  demand response

中图分类号: 

  • TP302