Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters
Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters
复制标题
移动应急发电机预先定位和实时分配，灵活应对自然灾害
DOI：
10.1109/tsg.2016.2605692
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发表时间：
2018-05-01
影响因子：
9.6
通讯作者：
Hou, Yunhe
中科院分区：
文献类型：
--
作者：
Lei, Shunbo;Wang, Jianhui;Hou, Yunhe
车载移动应急发电机(MEGS)是配电系统(DSS)对自然灾害做出弹性应急反应的重要灵活性资源。然而，它们目前没有得到充分利用。为了更好地利用电网资源，本文提出了将兆级电网作为分布式电源调度到决策支持系统中，通过形成多个微电网来恢复临界负荷。针对路网上Megs的出行时间对关键负荷停运持续时间影响较大的问题，提出了由预定位和实时分配组成的两阶段调度框架，并通过车辆路径问题来考虑交通问题。预定位在自然灾害发生前将Megs放置在准备位置，而实时分配在自然灾害发生后通过在DSS中形成MG从准备位置发送Megs来恢复关键负载。具体地说，考虑到负荷的优先级和需求大小，以最小化负荷的预期停运持续时间为目标，通过基于场景的两阶段随机优化问题来进行预定位，其中第一阶段预定位决策通过与所考虑的DS损坏和RN损坏/拥堵的场景相对应的第二阶段实时分配问题来评估。提出了一种场景分解算法来解决这个问题。算例验证了所提调度方案和算法的有效性。
Truck-mounted mobile emergency generators (MEGs) are critical flexibility resources of distribution systems (DSs) for resilient emergency response to natural disasters. However, they are currently under-utilized. For better utilization, this paper proposes dispatching MEGs as distributed generators in DSs to restore critical loads by forming multiple microgrids (MGs). As the travel time of MEGs on road networks (RNs) can greatly influence the outage duration of critical loads, a two-stage dispatch framework consisting of pre-positioning and real-time allocation is introduced, and the traffic issue is considered via the vehicle routing problem. Pre-positioning places MEGs in staging locations prior to a natural disaster, while real-time allocation sends MEGs from staging locations to restore critical loads by forming MGs in DSs after the natural disaster strikes. Specifically, with the objective of minimizing the expected outage duration of loads considering their priorities and demand sizes, pre-positioning is done via a scenario-based two-stage stochastic optimization problem, in which the first-stage pre-positioning decisions are evaluated by numbers of second-stage real-time allocation problems corresponding to considered scenarios of DS damage and RN damage/congestion. A scenario decomposition algorithm is applied to solve this problem. Illustrative cases demonstrate the effectiveness of the proposed dispatch scheme and algorithm.