TY - JOUR
T1 - Robust Operation of Distribution Networks Coupled with Urban Transportation Infrastructures
AU - Wei, Wei
AU - Mei, Shengwei
AU - Wu, Lei
AU - Wang, Jianhui
AU - Fang, Yujuan
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/5
Y1 - 2017/5
N2 - We study the energy dispatch of power distribution networks (PDNs) coupled with urban transportation networks. The electricity demand at each charging/swapping facility is influenced by the arrival rates and charging requests of electric vehicles, which further depends on the spatial distribution of traffic flows over the entire transportation system. We consider the impact of the road congestion on route choices of vehicles from a system-level perspective. The traffic flow pattern in steady state is characterized by the Wardrop user equilibrium. We consider the PDN load perturbation caused by the traffic demand uncertainty, and propose a robust dispatch method that maintains the feasibility of an alternating current power flow constraints. By applying the convex relaxation to nonlinear branch power flow equations, the proposed model yields a two-stage robust convex optimization problem with an implicit uncertainty set. Moreover, a decomposition framework is proposed, in which the first phase determines the uncertainty set of electricity demand by solving two traffic assignment problems associated with the extreme scenarios, and the second phase solves a two-stage robust second-order cone program following a delayed constraint generation framework. Several issues regarding the scalability and conservatism are elaborated. Case studies corroborate the applicability and efficiency of the proposed method.
AB - We study the energy dispatch of power distribution networks (PDNs) coupled with urban transportation networks. The electricity demand at each charging/swapping facility is influenced by the arrival rates and charging requests of electric vehicles, which further depends on the spatial distribution of traffic flows over the entire transportation system. We consider the impact of the road congestion on route choices of vehicles from a system-level perspective. The traffic flow pattern in steady state is characterized by the Wardrop user equilibrium. We consider the PDN load perturbation caused by the traffic demand uncertainty, and propose a robust dispatch method that maintains the feasibility of an alternating current power flow constraints. By applying the convex relaxation to nonlinear branch power flow equations, the proposed model yields a two-stage robust convex optimization problem with an implicit uncertainty set. Moreover, a decomposition framework is proposed, in which the first phase determines the uncertainty set of electricity demand by solving two traffic assignment problems associated with the extreme scenarios, and the second phase solves a two-stage robust second-order cone program following a delayed constraint generation framework. Several issues regarding the scalability and conservatism are elaborated. Case studies corroborate the applicability and efficiency of the proposed method.
KW - Branch power flow (BPF)
KW - Distribution network
KW - Robust optimization
KW - Traffic flow
KW - uncertainty
KW - urban transportation network (UTN)
KW - wardrop equilibrium
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U2 - 10.1109/TPWRS.2016.2595523
DO - 10.1109/TPWRS.2016.2595523
M3 - Article
AN - SCOPUS:84992700179
SN - 0885-8950
VL - 32
SP - 2118
EP - 2130
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 3
M1 - 7524708
ER -