引用本文:王怡聪,柯方超,周航,林毓军,张东寅,杨东俊,苗世洪.基于ADMM-GBS考虑故障影响的互联微电网多时间尺度优化调度[J].电力自动化设备,2024,44(6):127-134,144.
WANG Yicong,KE Fangchao,ZHOU Hang,LIN Yujun,ZHANG Dongyin,YANG Dongjun,MIAO Shihong.Multiple time scale optimal scheduling of interconnected microgrids considering fault effects based on ADMM-GBS[J].Electric Power Automation Equipment,2024,44(6):127-134,144.
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基于ADMM-GBS考虑故障影响的互联微电网多时间尺度优化调度
王怡聪1, 柯方超1, 周航2,3, 林毓军2,3, 张东寅1, 杨东俊1, 苗世洪2,3
1.国网湖北省电力有限公司经济技术研究院,湖北 武汉 430077;2.华中科技大学 电气与电子工程学院 强电磁技术全国重点实验室,湖北 武汉 430074;3.电力安全与高效湖北省重点实验室,湖北 武汉 430074
摘要:
极端事件攻击微电网可能造成负荷电能供应不足导致大停电事故。针对互联微电网系统,提出了一种考虑极端事件的分布式多时间尺度故障优化调度策略。在故障条件下以系统用户侧削减负荷量最小为目标,建立了互联微电网系统日前-日内两阶段滚动调度模型;基于鲁棒思想,考虑极端事件的时空特性以及故障线路的不确定性,采用分层随机抽样形成故障集,将其作为初始数据确定系统最恶劣故障场景;针对该场景进行线路加固后,采取高斯回代交替方向乘子法(ADMM-GBS)得到最优故障调度策略。通过算例分析验证了所提模型和调度策略的有效性。
关键词:  互联微电网系统  极端事件  分布式调度  多时间尺度
DOI:10.16081/j.epae.202402001
分类号:
基金项目:国网湖北省电力有限公司科技项目(521538220007)
Multiple time scale optimal scheduling of interconnected microgrids considering fault effects based on ADMM-GBS
WANG Yicong1, KE Fangchao1, ZHOU Hang2,3, LIN Yujun2,3, ZHANG Dongyin1, YANG Dongjun1, MIAO Shihong2,3
1.State Grid Hubei Electric Power Company Limited Economic Research Institute, Wuhan 430077, China;2.State Key Laboratory of Advanced Electromagnetic Technology, Huazhong University of Science and Technology, Wuhan 430074, China;3.Hubei Electric Power Security and High Efficiency Key Laboratory, Wuhan 430074, China
Abstract:
Extreme events attacking microgrids may result in insufficient load power supply and blackout. A distributed multiple time scale optimal scheduling strategy considering extreme events for interconnected microgrids system is proposed. Under fault conditions, with the goal of minimizing the load reduction on the user side of the system, a day-ahead and intra-day two stage rolling scheduling model for interconnected microgrids system is established. Based on the idea of robustness, taking into account the spatiotemporal characteristics of extreme events and the uncertainty of fault lines, the fault set is formed by hierarchical random sampling, which is used as initial data to determine the worst fault scenario for the system. After line reinforcement for this scenario, the alternative direction multiplier method with Gaussian back substitution is used to obtain the optimal fault scheduling strategy. The effectiveness of the proposed model and scheduling strategy is verified by an example analysis.
Key words:  interconnected microgrids system  extreme events  distributed scheduling  multiple time scales

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