A Multi-Stage Optimization Approach for Active Distribution Network Scheduling Considering Coordinated Electrical Vehicle Charging Strategy | Zendy

Xiaojun Zhu | Zendy; Haiteng Han | Zendy; Shan Gao | Zendy; Qingxin Shi | Zendy; Hantao Cui | Zendy; Guoqiang Zu | Zendy

Open Access

A Multi-Stage Optimization Approach for Active Distribution Network Scheduling Considering Coordinated Electrical Vehicle Charging Strategy

Author(s) -

Xiaojun Zhu,

Haiteng Han,

Shan Gao,

Qingxin Shi,

Hantao Cui,

Guoqiang Zu

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2868606

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

The increasing integration of renewable resources and electric vehicles (EVs) presents new requirements for the construction of a current distribution network. As an alternative of conventional distribution network, active distribution network (ADN) has gained more interest for its flexibility and interactivity. However, the unpredictable behavior of ADN participants from source-side, network-side, and demand-side brings more challenges on ADN dispatch. Thus, it is urged to design an ADN optimal scheduling approach that can comprehensively regulate the ADN participants’ behavior. In this paper, an ADN performance assessment system is first established to provide a quantitative analysis on ADN’s scheduling in terms of active controllability, active manageability, and active economy, respectively. Then, according to the ADN assessment system, a multi-stage optimal scheduling approach for ADN considering coordinated EV charging strategy is proposed. It is able to not only smooth the fluctuations caused by the integration of intermittent power sources and EVs but also reconfigure the network topology. Therefore, this approach can be applied to day-ahead dispatches to help operators effectively manage the ADN. Simulation results verify the correctness and effectiveness of the proposed approach.

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