Routing and Scheduling of Mobile Power Sources for Distribution System Resilience Enhancement

• Published in: IEEE transactions on smart grid Vol. 10; no. 5; pp. 5650 - 5662
• Main Authors: Lei, Shunbo, Chen, Chen, Zhou, Hui, Hou, Yunhe
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.09.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Distribution system; Electric power distribution; Energy storage; Integer programming; Meteorology; mobile power sources; Optimization; Power sources; Power system reliability; Reliability; Resilience; Restoration; Roads; Routing; routing and scheduling; Scheduling; service restoration; Storage systems; Survivability; System effectiveness; Weather
• ISSN: 1949-3053; 1949-3061
• DOI: 10.1109/TSG.2018.2889347

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.