Two-Stage Stochastic Optimization for the Pre-Position and Reconfiguration of Microgrid Defense Resources against Natural Disasters.
Two-Stage Stochastic Optimization for the Pre-Position and Reconfiguration of Microgrid Defense Resources against Natural Disasters.
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微电网自然灾害防御资源预置与重构的两阶段随机优化
DOI：
10.3390/s22166046
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发表时间：
2022-08-12
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随着全球变暖的加剧和演变，飓风等自然灾害发生更加频繁，对大规模电力系统提出了巨大挑战。因此，利用移动储能车（MEV）和受损场景联络线对微电网防御资源进行预置和重构越来越受到人们的关注。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，以根据负载的比例优先级最小化卸载负载和负载的停电持续时间。第一阶段，在自然灾害发生前决定增设联络线和预置MEV；第二阶段，根据自然灾害发生后的具体受损情况，操作联络线和原有线路的开关，将MEV从集结地调配到分配节点。所提出的负载恢复方法利用 MEV 和微电网形成联络线的优势来承受更关键的负载。采用渐进对冲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总线测试用例上验证了所提出模型和应用算法的有效性和优越性。
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.
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