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投稿时间：2022-08-31 修订日期：2023-01-09
投稿时间：2022-08-31 修订日期：2023-01-09
中文摘要: 近年来，在未来多能互补、综合能源系统的背景下，气电联合配网得到迅速的发展。然而，当前全球各地极端灾害频发，给能源系统的安全性带来了严峻的挑战。针对极端灾害对系统造成的失负荷影响，为兼顾系统的经济性与安全性，提出了一种考虑极端灾害下系统韧性约束的气电联合配网分布鲁棒扩展规划模型。首先，以规划成本与运行成本最小化为目标，建立考虑电动汽车充电站、分布式燃气机组和储能设备的气电联合配网扩展规划模型；然后，考虑极端灾害的作用，建立考虑韧性约束的气电联合配网分布鲁棒扩展规划模型，该模型包括基础场景与极端灾害最坏场景，其中基础场景考虑系统的经济性，以规划成本与基础场景运行成本最小为目标，极端灾害最坏场景则通过韧性约束保证系统的安全性，所提模型通过主问题–子问题迭代求解。最后，算例仿真发现：通过增加电动汽车充电站、分布式燃气机组和储能设备的规划投建，系统的经济性得到明显提升；而在面对极端灾害的影响下，通过分布式燃气机组的发电和电动汽车、储能设备的放电，系统失负荷情况得到减少，但随着系统韧性的增大所需单位规划成本会大幅增加。本文为在规划层面提升系统韧性提供了一种有效与实用的方法，为未来减小极端灾害对系统造成的影响的方案提供了一定参考。
Abstract:In recent years, under the background of multi energy complementation and integrated energy systems, the gas–electricity distribution network has been developed rapidly. However, the frequently occurrence of extreme disasters around the world has brought serious challenges to the security of the energy system. In order to reduce the impact of load shed caused by extreme disasters on the system, a distributionally robust expansion planning model of integrated gas–electricity distribution considering system resilience constraints under extreme disasters was proposed. First, taking the minimum planning cost and annual operating cost as the objective function, an expansion planning model of the integrated gas–electricity distribution system considering electric vehicle charging stations, distributed gas units and energy storage equipment was established. Secondly, considering the role of extreme disasters, a distributionally robust expansion planning model of the integrated gas–electricity distribution system considering resilience constraints was put forward. The model included the base scenario and the worst scenario for extreme disasters. Among them, the economy of the system was considered in the basic scenario, the minimum planning cost and the minimum operating cost of the basic scenario were taken as the objective function, the worst scenario for extreme disasters were realized through resilience constraints to ensure the resilience of the system. And the proposed model was finally solved by the structural iterative solution model of the main problem–sub-problem. Finally, the case simulation results showed that, by increasing the planning and construction of electric vehicle charging stations, distributed gas-fired units and energy storage equipment, the economy of the system could be effectively improved. In the face of extreme disasters, the system loss could be reduced through the discharge of electric vehicle charging stations, distributed gas-fired units and energy storage equipment, but the unit planning costs required will increase significantly as the system resilience increases. The paper provides an effective and practical plan for improving system resilience at the planning level, and provides a certain reference to reduce the impact of extreme disasters on the system in the future.
keywords: electric vehicle charging station distributed gas-fired units energy storage equipment extreme disaster resilience distributionally robust optimization
文章编号：202200937 中图分类号：TM74 文献标志码：
基金项目:国家自然科学基金项目（52007125）
| 作者 | 单位 | |
| 王沿胜 | 四川大学 电气工程学院，四川 成都 610065 | 2658864060@qq.com |
| 何川 | 四川大学 电气工程学院，四川 成都 610065 | |
| 刘绚 | 湖南大学 电气与信息工程学院，湖南 长沙 410082 | |
| 南璐 | 四川大学 电气工程学院，四川 成都 610065 | |
| 刘天琪 | 四川大学 电气工程学院，四川 成都 610065 |
作者简介:第一作者：王沿胜(1999-),男,硕士生.研究方向:综合能源系统优化运行.E-mail:2658864060@qq.com;通信作者：何川,副教授.E-mail:he_chuan@scu.edu.cn
引用文本：
王沿胜,何川,刘绚,南璐,刘天琪.考虑极端灾害下系统韧性约束的气电联合配网分布鲁棒扩展规划[J].工程科学与技术,2023,55(1):80-92.
WANG Yansheng,HE Chuan,LIU Xuan,NAN Lu,LIU Tianqi.Distributionally Robust Expansion Planning of Integrated Gas–electricity Distribution System Considering System Resilience Constraints Under Extreme Disasters[J].Advanced Engineering Sciences,2023,55(1):80-92.
引用文本：
王沿胜,何川,刘绚,南璐,刘天琪.考虑极端灾害下系统韧性约束的气电联合配网分布鲁棒扩展规划[J].工程科学与技术,2023,55(1):80-92.
WANG Yansheng,HE Chuan,LIU Xuan,NAN Lu,LIU Tianqi.Distributionally Robust Expansion Planning of Integrated Gas–electricity Distribution System Considering System Resilience Constraints Under Extreme Disasters[J].Advanced Engineering Sciences,2023,55(1):80-92.