考虑储能与动态重构的柔性互联配电系统两阶段鲁棒优化

doi:10.12204/j.issn.1000-7229.2022.09.010

电力建设 ›› 2022, Vol. 43 ›› Issue (9): 94-103.doi: 10.12204/j.issn.1000-7229.2022.09.010

• 新型电力系统下配电网规划与运行优化关键技术研究及应用·栏目主持王守相教授、赵倩宇博士· • 上一篇下一篇

考虑储能与动态重构的柔性互联配电系统两阶段鲁棒优化

梁栋¹^,²(), 郭育威¹, 王笑雪¹, 刘琪³, 王守相³

1.省部共建电工装备可靠性与智能化国家重点实验室(河北工业大学),天津市 300130
2.石家庄科林电气股份有限公司河北省智能配用电装备产业技术研究院,石家庄市 050222
3.教育部智能电网重点实验室(天津大学),天津市 300072

收稿日期:2022-01-21 出版日期:2022-09-01 发布日期:2022-08-31
通讯作者: 梁栋 E-mail:liangdong@hebut.edu.cn
作者简介:郭育威(1995),男,硕士研究生,主要研究方向为柔性互联配电系统鲁棒优化;
王笑雪(1991),女,博士,讲师,硕士生导师,主要研究方向为智能配电网分布式电压控制;
刘琪(1992),男,博士研究生,主要研究方向为交直流配电网优化控制;
王守相(1973),男,博士,教授,博士生导师,主要研究方向为分布式发电与智能配电网。
基金资助:
河北省自然科学基金资助项目(E2021202053);河北省省级科技计划资助项目(20311801D);中国博士后基金面上项目(2019M660966)

Two-Stage Robust Optimization for Flexible Interconnected Distribution Systems Considering Energy Storages and Dynamic Reconfiguration

LIANG Dong¹^,²(), GUO Yuwei¹, WANG Xiaoxue¹, LIU Qi³, WANG Shouxiang³

1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment(Hebei University of Technology),Tianjin 300130, China
2. Hebei Smart Electrical Distribution and Utilization Equipment Industry Technology Institute, Shijiazhuang Kelin Electric Corporation, Shijiazhuang 050222, China
3. Key Laboratory of the Ministry of Education on Smart Power Grids(Tianjin University), Tianjin 300072, China

Received:2022-01-21 Online:2022-09-01 Published:2022-08-31
Contact: LIANG Dong E-mail:liangdong@hebut.edu.cn
Supported by:
Natural Science Foundation of Hebei Province province(E2021202053);S&T Program of Hebei Province(20311801D);China Postdoctoral Science Foundation(2019M660966)

摘要/Abstract

摘要：

强波动性分布式电源的大量接入给配电系统可靠安全运行带来了挑战。为此,提出了一种考虑储能与动态重构的柔性互联配电系统两阶段鲁棒优化调度方法。首先,建立了综合考虑柔性配电开关、储能与动态重构的柔性互联配电系统两阶段鲁棒优化数学模型,其中第一阶段考虑日前分布式电源出力预测的不确定性以及网络拓扑和储能的时序相关性进行全局优化,第二阶段基于第一阶段的决策方案和准确的超短期预测信息,在各时段对柔性配电开关进行实时调度;其次,采用改进的列与约束生成算法对模型进行求解,通过辅助变量和对偶变量交替迭代,显著提高子问题的求解效率;最后,通过33和69节点系统进行测试,验证了所提调度模型和求解算法的有效性。

关键词: 柔性互联配电系统, 鲁棒优化, 动态重构, 不确定性

Abstract:

Large scale integration of intermittent distributed generation (DG) challenges the reliable and secure operation of distribution systems. Therefore, this paper proposes a two-stage robust scheduling method for flexible interconnected distribution systems considering energy storage and dynamic reconfiguration. Firstly, a two-stage robust scheduling model for flexible interconnected distribution systems is established, considering flexible distribution switches (FDSs), energy storage and dynamic reconfiguration. In the first stage, the network topologies and energy storage outputs are globally optimized considering their temporal correlation and day-ahead forecasting uncertainties of the DG outputs. In the second stage, the FDS power in each time slot is dispatched according to the decisions of the first stage and ultra-short-term DG forecast. Then, an improved column and constraint generation algorithm is adopted to solve the robust model, where an alternating direction process is used to accelerate the sub-problem. Finally, the effectiveness of the proposed robust scheduling model and algorithm is verified using the 33-node and 69-node distribution systems with promising results.

Key words: flexible interconnected distribution systems, robust optimization, dynamic reconfiguration, uncertainty

中图分类号:

TM732

梁栋, 郭育威, 王笑雪, 刘琪, 王守相. 考虑储能与动态重构的柔性互联配电系统两阶段鲁棒优化[J]. 电力建设, 2022, 43(9): 94-103.

LIANG Dong, GUO Yuwei, WANG Xiaoxue, LIU Qi, WANG Shouxiang. Two-Stage Robust Optimization for Flexible Interconnected Distribution Systems Considering Energy Storages and Dynamic Reconfiguration[J]. ELECTRIC POWER CONSTRUCTION, 2022, 43(9): 94-103.

图/表 19

图1 算法流程图

Fig.1 Algorithm flowchart

图2 33节点配电系统

Fig.2 33-node distribution system

图3 DG出力波动区间

Fig.3 DG output bounds

表1 不同Г下目标函数

Table 1 Objectives under different Г

表2 网络拓扑决策方案

Table 2 Scheduling results of network topologies

图4 储能剩余电量曲线

Fig.4 Remaining energy of energy storages

表3 蒙特卡罗抽样测试结果

Table 3 Results of Monte Carlo sampling tests

图5 FDS日前调度参考值(理想场景, DA-RO)

Fig.5 Day-ahead FDS scheduling reference value (ideal scenario, DA-RO)

图6 FDS日内调度结果(理想场景, DA-RO+IDO)

Fig.6 Intra-day FDS scheduling results (ideal scenario, DA-RO+IDO)

图7 DA-RO决策下的IDO前后对比

Fig.7 Comparison before and after IDO based on DA-RO

图8 日前所有节点电压参考值(恶劣场景, DA-DO)

Fig.8 Day-ahead voltage reference curves of all nodes (worst scenario, DA-DO)

图9 日内所有节点电压(恶劣场景, DA-DO+IDO)

Fig.9 Intra-day voltage curves of all nodes (worst scenario, DA-DO+IDO)

图10 FDS功率日前参考值(恶劣场景, DA-RO)

Fig.10 Day-ahead FDS scheduling reference value (worst scenario, DA-RO)

图11 FDS日内调度结果(恶劣场景, DA-RO+IDO)

Fig.11 Intra-day FDS scheduling results (worst scenario, DA-RO+IDO)

图12 日前所有节点电压(恶劣场景, DA-RO+IDO)

Fig.12 Day-ahead voltage value of all nodes (worst scenario, DA-RO+IDO)

表4 测试方案

Table 4 Test plans

表5 算例运行结果

Table 5 Test results of different scenarios

表6 不同系统计算时间对比

Table 6 CPU time comparison of different systems

表7 不同DG数量下的计算时间

Table 7 CPU time under different DG numbers

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考虑储能与动态重构的柔性互联配电系统两阶段鲁棒优化

Two-Stage Robust Optimization for Flexible Interconnected Distribution Systems Considering Energy Storages and Dynamic Reconfiguration

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