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电工材料电气绝缘全国重点实验室(西安交通大学),陕西省西安市 710049
卞艺衡(1994—),男,博士,助理教授,主要研究方向:弹性电力系统、电力系统优化规划与运行。E-mail:byh0xyz@xjtu.edu.cn
张迪(2002—),男,硕士研究生,主要研究方向:弹性电力系统规划与恢复优化。E-mail:zhangdi487571339@stu.xjtu.edu.cn
张舜尧(2001—),男,硕士研究生,主要研究方向:弹性电力系统。E-mail:ZSYzsy@stu.xjtu.edu.cn
李更丰(1984—),男,通信作者,博士,教授,主要研究方向:电力系统可靠性与弹性、综合能源系统与主动配电网技术。E-mail:gengfengli@xjtu.edu.cn
收稿:2024-12-20,
修回:2025-03-18,
网络出版:2025-05-30,
纸质出版:2025-08-10
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卞艺衡,张迪,张舜尧等.综合脆弱度与故障影响的电-气耦合系统关键元件强化策略[J].电力系统自动化,2025,49(15):65-73.
BIAN Yiheng,ZHANG Di,ZHANG Shunyao,et al.Reinforcement Strategy for Key Components of Electricity-Gas Coupling Systems Considering Combined Influences of Vulnerability and Failure[J].Automation of Electric Power Systems,2025,49(15):65-73.
卞艺衡,张迪,张舜尧等.综合脆弱度与故障影响的电-气耦合系统关键元件强化策略[J].电力系统自动化,2025,49(15):65-73. DOI: 10.7500/AEPS20241220008.
BIAN Yiheng,ZHANG Di,ZHANG Shunyao,et al.Reinforcement Strategy for Key Components of Electricity-Gas Coupling Systems Considering Combined Influences of Vulnerability and Failure[J].Automation of Electric Power Systems,2025,49(15):65-73. DOI: 10.7500/AEPS20241220008.
电-气耦合系统对支撑能源高效利用、提升电力安全具有重要价值。文中提出了综合脆弱度及故障影响的电-气耦合系统关键元件强化优化策略。在规划阶段,对电力杆塔、输气管道进行差异化强化,实现极端事件后系统失负荷最小。首先,以同时对电力和天然气系统有破坏作用的地震灾害为例,构建了灾害模型及多类型强化措施下的故障场景。其次,采用预排序-随机规划两阶段方法进行决策,第1阶段基于科普兰德排序方法模拟抢修优先次序,第2阶段考虑配电网重构、有限人员数量下故障抢修等恢复措施开展多等级强化随机规划。通过两阶段决策解决了多等级强化规划难以考虑抢修调度过程的难题,并提升求解效率。最后,采用逐步对冲算法完成随机规划求解,通过算例验证了强化策略的有效性。
The electricity-gas coupling system is of great value in supporting the efficient use of energy and improving electricity safety. This paper proposes a reinforcement optimization strategy for key components of the electricity-gas coupling system with combined influences of vulnerability and failures. In the planning stage
power poles and gas pipelines are differentiated for reinforcement to minimize the system loss of load after extreme events. Firstly
taking the earthquake disaster that has a destructive effect on both the power and natural gas systems as an example
a disaster model and fault scenarios under multiple types of reinforcement measures are constructed. Secondly
a two-stage method of pre-ranking-stochastic programming is used to make decisions. In the first stage
the repair priority is simulated based on the Copeland ranking method. In the second stage
the multi-level reinforcement stochastic programming is carried out considering the restoration measures such as distribution network reconstruction and fault repair under limited number of crews. The two-stage decision-making solves the problem that it is difficult to consider the repair scheduling process in multi-level reinforcement planning
and improves the solution efficiency. Finally
the progressive hedging algorithm is used to complete the stochastic programming solution
and the effectiveness of the strategy is verified by cases.
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