Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility Enhancement

Jie Fang (), Wenwu Li and Dunchu Chen
Additional contact information
Jie Fang: College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China
Wenwu Li: College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China
Dunchu Chen: College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China

Energies, 2025, vol. 18, issue 3, 1-15

Abstract: With the increasing penetration of distributed generation (DG), the supply–demand imbalance and voltage overruns in the distribution network have intensified, and there is an urgent need to introduce flexibility resources for regulation. This paper proposes co-planning of electric vehicles (EVs) and soft opening points (SOPs) to improve the flexibility of the active distribution network, thereby improving the economics and flexibility of the distribution network. Firstly, this paper establishes a charging pile day-ahead dispatchable prediction model and a real-time dispatchable potential assessment model through Monte Carlo sampling simulation. It replaces the traditional energy storage model with this model and then solves the EV and SOP collaborative planning model using a second-order conical planning algorithm with the objective function of minimizing the annual integrated cost. At the same time, the flexibility of the distribution network is analyzed by two indicators: power supply and demand balance and branch load margin. Finally, the optimization method proposed in this paper is analyzed and validated on an improved IEEE 33-node distribution system. Example results show that the planning method proposed in this paper can effectively reduce the annual comprehensive operating cost of distribution networks, meet the flexibility index, and be conducive to improving the economy and flexibility of distribution network operation.

Keywords: distributed generation; soft open point; electric vehicle; Monte Carlo sampling; second-order cone programming (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/3/694/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/3/694/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:3:p:694-:d:1582623

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().