College of Systems Engineering, National University of Defense Technology, Changsha 410073, China.
Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology, Changsha 410073, China.
Sensors (Basel). 2022 Aug 12;22(16):6046. doi: 10.3390/s22166046.
With the aggravation and evolution of global warming, natural disasters such as hurricanes occur more frequently, posing a great challenge to large-scale power systems. Therefore, the pre-position and reconfiguration of the microgrid defense resources by means of Mobile Energy Storage Vehicles (MEVs) and tie lines in damaged scenarios have attracted more and more attention. This paper proposes a novel two-stage optimization model with the consideration of MEVs and tie lines to minimize the shed loads and the outage duration of loads according to their proportional priorities. In the first stage, tie lines addition and MEVs pre-position are decided prior to a natural disaster; in the second stage, the switches of tie lines and original lines are operated and MEVs are allocated from staging locations to allocation nodes according to the specific damaged scenarios after the natural disaster strikes. The proposed load restoration method exploits the benefits of MEVs and ties lines by microgrid formation to pick up more critical loads. The progressive hedging algorithm is employed to solve the proposed scenario-based two-stage stochastic optimization problem. Finally, the effectiveness and superiority of the proposed model and applied algorithm are validated on an IEEE 33-bus test case.
随着全球变暖的加剧和演变,飓风等自然灾害发生得更加频繁,这对大规模电力系统构成了巨大挑战。因此,通过移动储能车(MEV)和联络线在受损场景下预先配置和重新配置微网防御资源引起了越来越多的关注。本文提出了一种新颖的两阶段优化模型,考虑了 MEV 和联络线,根据其比例优先级,最小化切负荷量和负荷停电时间。在第一阶段,在自然灾害发生之前,决定增加联络线和 MEV 的预定位;在第二阶段,根据自然灾害后的具体受损情况,操作联络线和原始线的开关,并从规划位置向分配节点分配 MEV。所提出的负荷恢复方法通过微网形成利用 MEV 和联络线的优势来接入更多关键负荷。采用渐进套期保值算法来解决所提出的基于场景的两阶段随机优化问题。最后,在 IEEE 33 母线测试案例上验证了所提出模型和应用算法的有效性和优越性。