TY - JOUR

T1 - Routing and charging facility location for EVs under nodal pricing of electricity

T2 - A bilevel model solved using special ordered set

AU - Gonzalez, Sebastian

AU - Feijoo, Felipe

AU - Basso, Franco

AU - Subramanian, Vignesh

AU - Sankaranarayanan, Sriram

AU - Das, Tapas K.

N1 - Publisher Copyright:
IEEE

PY - 2022

Y1 - 2022

N2 - We consider the problem of identifying optimal location of electric vehicle (EV) charging stations, while accounting for (i) route optimization and (ii) charging cost optimization by the EV fleets, where the electricity price is obtained endogenously by an optimal power flow (OPF) model. We solve the problem using a bi-objective bilevel programming framework with the objectives being one of minimising travel time and the other of minimising EV charging cost. The upper level problem consists of the facility location and the transportation model and the lower level problem consists of the OPF model. After reformulating this computational hard problem as a mathematical program with equilibrium constraints (MPEC), we solve the problem using a special ordered sets-type 1 (SOS1)-based approach. We record the significant improvement in speed by our method, as opposed to the standard Big-M approach. Finally, we apply the technique to the Sioux Falls transportation network with the IEEE 14-bus electricity network embedded on it. We observe that solutions through our models results in as much 37% lower operating costs for the EVs.

AB - We consider the problem of identifying optimal location of electric vehicle (EV) charging stations, while accounting for (i) route optimization and (ii) charging cost optimization by the EV fleets, where the electricity price is obtained endogenously by an optimal power flow (OPF) model. We solve the problem using a bi-objective bilevel programming framework with the objectives being one of minimising travel time and the other of minimising EV charging cost. The upper level problem consists of the facility location and the transportation model and the lower level problem consists of the OPF model. After reformulating this computational hard problem as a mathematical program with equilibrium constraints (MPEC), we solve the problem using a special ordered sets-type 1 (SOS1)-based approach. We record the significant improvement in speed by our method, as opposed to the standard Big-M approach. Finally, we apply the technique to the Sioux Falls transportation network with the IEEE 14-bus electricity network embedded on it. We observe that solutions through our models results in as much 37% lower operating costs for the EVs.

KW - bilevel model

KW - charging facility.

KW - Charging stations

KW - Costs

KW - Electric vehicle charging

KW - Electricity network

KW - EV transportation network

KW - Load modeling

KW - Mathematical models

KW - Routing

KW - Special ordered set-Type1 (SOS1)

KW - Transportation

UR - http://www.scopus.com/inward/record.url?scp=85126674018&partnerID=8YFLogxK

U2 - 10.1109/TSG.2022.3159603

DO - 10.1109/TSG.2022.3159603

M3 - Article

AN - SCOPUS:85126674018

JO - IEEE Transactions on Smart Grid

JF - IEEE Transactions on Smart Grid

SN - 1949-3053

ER -