Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/75970
Title: Distribution network electric vehicle hosting capacity maximization : a chargeable region optimization model
Authors: Zhao, J 
Wang, JH
Xu, Z 
Wang, C
Wan, C
Chen, C
Keywords: Adjustable uncertainty set
Chargeable region
Charging strategy
Distribution network
Electric vehicle
Hosting capacity
Robust optimization
Two-stage optimization
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on power systems, 2017, v. 32, no. 5, p. 4119-4130 How to cite?
Journal: IEEE transactions on power systems 
Abstract: 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.
URI: http://hdl.handle.net/10397/75970
ISSN: 0885-8950
EISSN: 1558-0679
DOI: 10.1109/TPWRS.2017.2652485
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