TY - JOUR
T1 - Distribution Network Electric Vehicle Hosting Capacity Maximization
T2 - A Chargeable Region Optimization Model
AU - Zhao, Jian
AU - Wang, Jianhui
AU - Xu, Zhao
AU - Wang, Cheng
AU - Wan, Can
AU - Chen, Chen
N1 - Publisher Copyright:
© 1969-2012 IEEE.
PY - 2017/9
Y1 - 2017/9
N2 - To coordinate electric vehicle (EV) charging, the EV aggregator (EVA) is usually assumed to obtain the privilege from EV owners (EVOs) to determine the EV charging profile, and complex communication between EVA and EVOs is demanded, which poses difficulties for practical applications. In contrast, this paper proposes the concept of an EV chargeable region to evaluate the distribution network (DN) EV hosting capacity, i.e., how much EV charging demand can be accommodated in a DN, within which the technical constraints of DN (e.g., voltage deviation) are guaranteed and EVOs' charging requests are maximally ensured. The optimization of the EV chargeable region is formulated as a two-stage robust optimization model with adjustable uncertainty set. The EV chargeable region and DN decision variables are optimized in the first stage and the feasibility in the real-time worst-case scenario is checked in the second stage, considering the uncertainty of EV charging demand and DN active and reactive power. A modified column and constraint generation and outer approximation method is adopted to address the proposed problem. Simulations on an IEEE 123-node DN demonstrate the effectiveness of the proposed model.
AB - To coordinate electric vehicle (EV) charging, the EV aggregator (EVA) is usually assumed to obtain the privilege from EV owners (EVOs) to determine the EV charging profile, and complex communication between EVA and EVOs is demanded, which poses difficulties for practical applications. In contrast, this paper proposes the concept of an EV chargeable region to evaluate the distribution network (DN) EV hosting capacity, i.e., how much EV charging demand can be accommodated in a DN, within which the technical constraints of DN (e.g., voltage deviation) are guaranteed and EVOs' charging requests are maximally ensured. The optimization of the EV chargeable region is formulated as a two-stage robust optimization model with adjustable uncertainty set. The EV chargeable region and DN decision variables are optimized in the first stage and the feasibility in the real-time worst-case scenario is checked in the second stage, considering the uncertainty of EV charging demand and DN active and reactive power. A modified column and constraint generation and outer approximation method is adopted to address the proposed problem. Simulations on an IEEE 123-node DN demonstrate the effectiveness of the proposed model.
KW - Adjustable uncertainty set
KW - chargeable region
KW - charging strategy
KW - distribution network
KW - electric vehicle
KW - hosting capacity
KW - robust optimization
KW - two-stage optimization
UR - https://www.scopus.com/pages/publications/85028840236
U2 - 10.1109/TPWRS.2017.2652485
DO - 10.1109/TPWRS.2017.2652485
M3 - 文章
AN - SCOPUS:85028840236
SN - 0885-8950
VL - 32
SP - 4119
EP - 4130
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 5
M1 - 7817888
ER -