柴园园, 赵晓波, 吕超贤, 梁天龙, 董逸超. 基于Fisher时段划分的配电网源-网-荷-储多时间尺度协调优化调控策略[J]. 电网技术, 2024, 48(4): 1593-1601. DOI: 10.13335/j.1000-3673.pst.2023.0293
引用本文: 柴园园, 赵晓波, 吕超贤, 梁天龙, 董逸超. 基于Fisher时段划分的配电网源-网-荷-储多时间尺度协调优化调控策略[J]. 电网技术, 2024, 48(4): 1593-1601. DOI: 10.13335/j.1000-3673.pst.2023.0293
CHAI Yuanyuan, ZHAO Xiaobo, LÜ Chaoxian, LIANG Tianlong, DONG Yichao. Coordinated Multi-time Scale Optimal Regulation for Source-grid-load-storage of Distribution Network Based on Fisher Period Division[J]. Power System Technology, 2024, 48(4): 1593-1601. DOI: 10.13335/j.1000-3673.pst.2023.0293
Citation: CHAI Yuanyuan, ZHAO Xiaobo, LÜ Chaoxian, LIANG Tianlong, DONG Yichao. Coordinated Multi-time Scale Optimal Regulation for Source-grid-load-storage of Distribution Network Based on Fisher Period Division[J]. Power System Technology, 2024, 48(4): 1593-1601. DOI: 10.13335/j.1000-3673.pst.2023.0293

基于Fisher时段划分的配电网源-网-荷-储多时间尺度协调优化调控策略

Coordinated Multi-time Scale Optimal Regulation for Source-grid-load-storage of Distribution Network Based on Fisher Period Division

  • 摘要: 多元可控资源的联合优化调控对于提高配电网运行安全性和经济性意义重大,但同时大幅增加优化问题的复杂度,降低模型求解效率。基于此,提出了基于Fisher时段划分的配电网源-网-荷-储协调优化调控策略。首先,构建多时间尺度“源-网-荷-储”协调优化架构,包括日前优化、日内滚动和秒级监控3个阶段。其次,研究基于源荷功率区间数据的Fisher最优分割时段划分方法。然后,建立日前优化调控模型、日内滚动优化模型和区域自治优化模型,求解电网离散设备、需求响应负荷、光伏和储能等的最优调控指令。最后,以IEEE 33节点系统为例,对所提协调优化调控策略进行仿真验证。算例结果表明,所提方法能够大幅提高协调优化模型的计算效率,并保证电网运行安全性和经济性。

     

    Abstract: The joint optimal regulation of the multiple controllable resources is of great significance in improving the security and economy of the distribution network operation. But it also increases the complexity of the optimization models and greatly reduces the computational efficiency. For this reason, a coordinated optimal regulation for the source-grid-load-storage of the distribution network based on the Fisher period division is proposed in this paper. Firstly, a coordinated optimization architecture for source-grid-load-storage with multi-time scales is constructed. It includes three stages, the day-ahead optimization, the intraday rolling optimization and the second-level supervisory control. Secondly, based on the source and load power interval data, a Fisher optimal period division is presented. Then, the day-ahead optimization model, the intraday rolling optimization model and the regional autonomous optimization model are formulated to obtain the optimal regulation schemes for the discrete equipment, the demand response loads, the photovoltaics and the energy storages. Finally, taking the IEEE 33-node system as an example, the proposed coordinated optimization control strategy is verified by simulation. The numerical results show that the proposed method is able to effectively improve the computational efficiency of the coordinated optimization model, ensuring the security and economy of the power grid operation.

     

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