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1.智慧能源工程技术研究中心,华南理工大学电力学院,广东省广州市 510640
2.广东工业大学自动化学院,广东省广州市 510006
陈伯达(1993—),男,硕士研究生,主要研究方向:能源互联网优化运行、新能源及微电网。E-mail:919046909@qq.com
林楷东(1995—),男,通信作者,硕士研究生,主要研究方向:能源互联网优化运行、负荷预测。E-mail:596875439@qq.com
苏洁莹(1997—),女,硕士研究生,主要研究方向:能源互联网优化运行。E-mail:1004918817@qq.com
收稿日期:2019-08-20,
修回日期:2019-11-24,
网络出版日期:2020-04-01,
纸质出版日期:2020-05-25
移动端阅览
陈伯达,林楷东,苏洁莹等.基于鲁棒规划的综合能源微网孤岛划分方法[J].电力系统自动化,2020,44(10):32-40.
CHEN Boda,LIN Kaidong,SU Jieying,et al.Robust Planning Based Method for Integrated Energy Microgrid Island Partition[J].Automation of Electric Power Systems,2020,44(10):32-40.
陈伯达,林楷东,苏洁莹等.基于鲁棒规划的综合能源微网孤岛划分方法[J].电力系统自动化,2020,44(10):32-40. DOI: 10.7500/AEPS20190820001.
CHEN Boda,LIN Kaidong,SU Jieying,et al.Robust Planning Based Method for Integrated Energy Microgrid Island Partition[J].Automation of Electric Power Systems,2020,44(10):32-40. DOI: 10.7500/AEPS20190820001.
针对综合能源微网系统孤岛划分问题,考虑可再生能源和电气热负荷需求的不确定性,将微能源网的能源转换和储存设备作为调度资源,以故障发生后最优化孤岛划分方案为目标,建立了考虑孤岛持续运行的鲁棒孤岛划分模型。在该模型中,以违背停电最短通知时间约束为目标函数惩罚项
为负荷预留一定的故障应对时间,以及避免孤岛负荷因源荷功率波动导致重复接入和切除的问题。基于鲁棒离散优化理论,将不确定性约束转化为确定性约束,构建了混合整数线性规划模型,利用全局鲁棒调节系数改善鲁棒优化的保守性,平衡好孤岛划分方案的经济性和可操作性,以满足不同决策需求。最后通过算例验证了所提模型和求解方法的有效性。
Considering the uncertainty of renewable energy and electricity
gas and heat load
this paper discusses the island partition of integrated energy microgrid system and establishes a robust island partition model based on continuous operation of island. This model uses energy conversion and storage equipment of integrated energy microgrid as scheduling resources
and targets to optimize islanding partition scheme after fault occurrence. In this model
the shortest notification time constraint against the blackout is taken as the target penalty term and a certain response time is reserved for the load to some extent. Meanwhile
it avoids repeated access and removal of island load caused by source power and load fluctuation. The robust discrete optimization theory transforms uncertain constraints into certain constraints
and a mixed integer linear programming model is constructed. Global robust tuning coefficient is used to improve the conservativeness of robust optimization. The economy and operability of the islanding scheme are well balanced to meet different decision-making needs. Finally
the case verifies the effectiveness of the proposed model and solutions.
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