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Regular Paper | Open Access

Joint Planning of Active Distribution Network and EV Charging Stations Considering Vehicle-to-Grid Functionality and Reactive Power Support

Yongheng Wang1Xinwei Shen1( )Yan Xu2
Institute for Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
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Abstract

This paper proposes a collaborative planning model for active distribution network (ADN) and electric vehicle (EV) charging stations that fully considers vehicle-to-grid (V2G) function and reactive power support of EVs in different regions. This paper employs a sequential decomposition method based on physical characteristics of the problem, breaking down the holistic problem into two sub-problems for solution. Subproblem I optimizes the charging and discharging behavior of autopilot electric vehicles (AEVs) using a mixed-integer linear programming (MILP) model. Subproblem II uses a mixed-integer second-order cone programming (MISOCP) model to plan ADN and retrofit or construct V2G charging stations (V2GCS), as well as multiple distributed generation resources (DGRs). The paper also analyzes the impact of bi-directional active-reactive power interaction of V2GCS on ADN planning. The presented model is tested in the 47-node ADN in Longgang District, Shenzhen, China, and the IEEE 33-node ADN, demonstrating that decomposition can significantly improve the speed of solving large-scale problems while maintaining accuracy with low AEV penetration.

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CSEE Journal of Power and Energy Systems
Pages 2100-2113

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Cite this article:
Wang Y, Shen X, Xu Y. Joint Planning of Active Distribution Network and EV Charging Stations Considering Vehicle-to-Grid Functionality and Reactive Power Support. CSEE Journal of Power and Energy Systems, 2024, 10(5): 2100-2113. https://doi.org/10.17775/CSEEJPES.2023.03930

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Received: 13 May 2023
Revised: 28 July 2023
Accepted: 27 September 2023
Published: 28 December 2023
© 2023 CSEE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).