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福州大学电气工程与自动化学院,福建省福州市 350108
张亚超(1985—),男,博士,讲师,主要研究方向:含新能源电力系统优化调度。E-mail:yczhang@fzu.edu.cn
谢仕炜(1993—),男,通信作者,博士,讲师,主要研究方向:主动配电网与交通网耦合规划。E-mail:Shiwei_Xie@126.com
收稿日期:2021-01-21,
修回日期:2021-03-25,
网络出版日期:2021-06-11,
纸质出版日期:2021-09-25
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张亚超,谢仕炜.面向配电网弹性提升的多时间尺度恢复策略协调优化框架[J].电力系统自动化,2021,45(18):28-34.
ZHANG Yachao,XIE Shiwei.Coordinated Optimization Framework of Multi-timescale Restoration Strategies for Resilience Enhancement of Distribution Networks[J].Automation of Electric Power Systems,2021,45(18):28-34.
张亚超,谢仕炜.面向配电网弹性提升的多时间尺度恢复策略协调优化框架[J].电力系统自动化,2021,45(18):28-34. DOI: 10.7500/AEPS20210121003.
ZHANG Yachao,XIE Shiwei.Coordinated Optimization Framework of Multi-timescale Restoration Strategies for Resilience Enhancement of Distribution Networks[J].Automation of Electric Power Systems,2021,45(18):28-34. DOI: 10.7500/AEPS20210121003.
针对小概率、高损失极端灾害事件对配电网安全稳定运行的影响,提出了一种面向配电网弹性提升的多时间尺度恢复策略协调优化框架。首先,针对检修人员调度问题,建立考虑极端灾害下时间不确定性的故障修复模型。其次,在配电网三相不平衡运行条件下,构建结合分布式电源和联络开关进行网络重构的负荷恢复模型。然后,以故障元件修复状态作为耦合变量,基于上述2种不同时间尺度的模型构建协调优化框架,并建立两阶段鲁棒优化模型采用列约束生成方法进行迭代求解。最后,考虑检修人员时间不确定性、多种恢复策略关联性以及求解时间步长等因素构建不同场景,通过算例验证了所提模型及求解方法的有效性。
Aiming at the impact of the low-probability and high-loss extreme disasters on the safe and stable operation of distribution networks
this paper proposes a coordinated optimization framework of multi-timescale restoration strategies for resilience enhancement of distribution networks. Firstly
a fault restoration model considering time uncertainty in extreme disasters is established for the problem of maintainers staff dispatch. Secondly
the load restoration model combining distributed generators and contact switches for network reconfiguration is constructed under the three-phase unbalanced operation condition of the distribution network. Then
a coordinated optimization framework is constructed based on the above two models with different time scales using the repair state of fault component as the coupling variable
and a two-stage robust optimization model is established using a column-and-constraint generation method for iterative solution. Finally
different scenarios are constructed considering the time uncertainty of maintainers staff
the correlation of multiple recovery strategies and the solution time step
and the effectiveness of the proposed model and solution method is verified by examples.
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