TY - JOUR
T1 - Routing and Scheduling of Mobile Power Sources for Distribution System Resilience Enhancement
AU - Lei, Shunbo
AU - Chen, Chen
AU - Zhou, Hui
AU - Hou, Yunhe
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/1
Y1 - 2018/9/1
N2 - 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.
AB - 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.
KW - Distribution system
KW - mobile power sources
KW - resilience
KW - routing and scheduling
KW - service restoration
UR - https://www.scopus.com/pages/publications/85058990381
U2 - 10.1109/TSG.2018.2889347
DO - 10.1109/TSG.2018.2889347
M3 - 文章
AN - SCOPUS:85058990381
SN - 1949-3053
VL - 10
SP - 5650
EP - 5662
JO - IEEE Transactions on Smart Grid
JF - IEEE Transactions on Smart Grid
IS - 5
ER -