调度(生产过程)
计算机科学
整数规划
弹性(材料科学)
电力系统
数学优化
分布式计算
实时计算
功率(物理)
算法
数学
量子力学
热力学
物理
作者
Shunbo Lei,Chen Chen,Hui Zhou,Yunhe Hou
标识
DOI:10.1109/tsg.2018.2889347
摘要
Mobile power sources (MPSs), including electric vehicle fleets, truck-mounted mobile energy storage systems, and mobile emergency generators, have great potential to enhance distribution system (DS) resilience against extreme weather events. However, their dispatch is not well investigated. This paper implements resilient routing and scheduling of MPSs via a two-stage framework. In the first stage, i.e., before the event, MPSs are pre-positioned in the DS to enable rapid pre-restoration, in order to enhance survivability of the electricity supply to critical loads. DS network is also proactively reconfigured into a less impacted or stressed state. A two-stage robust optimization model is constructed and solved by the column-and-constraint generation algorithm to derive first-stage decisions. In the second stage, i.e., after the event, MPSs are dynamically dispatched in the DS to coordinate with conventional restoration efforts, so as to enhance system recovery. A novel mixed-integer programming model that resolves different timescales of MPS dispatch and DS operation, coupling of road and power networks, etc., is formulated to optimize dynamic dispatch of MPSs. Case studies conducted on IEEE 33-node and 123-node test systems demonstrate the proposed method's effectiveness in routing and scheduling MPSs for DS resilience enhancement.
科研通智能强力驱动
Strongly Powered by AbleSci AI