Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility Enhancement
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...
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MDPI AG
2025-02-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/3/694 |
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| author | Jie Fang Wenwu Li Dunchu Chen |
| author_facet | Jie Fang Wenwu Li Dunchu Chen |
| author_sort | Jie Fang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-d048447a77f848569dc49d5d5832704a |
| institution | DOAJ |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-d048447a77f848569dc49d5d5832704a2025-08-20T02:48:06ZengMDPI AGEnergies1996-10732025-02-0118369410.3390/en18030694Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility EnhancementJie Fang0Wenwu Li1Dunchu Chen2College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaCollege of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaCollege of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaWith 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.https://www.mdpi.com/1996-1073/18/3/694distributed generationsoft open pointelectric vehicleMonte Carlo samplingsecond-order cone programming |
| spellingShingle | Jie Fang Wenwu Li Dunchu Chen Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility Enhancement Energies distributed generation soft open point electric vehicle Monte Carlo sampling second-order cone programming |
| title | Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility Enhancement |
| title_full | Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility Enhancement |
| title_fullStr | Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility Enhancement |
| title_full_unstemmed | Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility Enhancement |
| title_short | Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility Enhancement |
| title_sort | electric vehicle and soft open points co planning for active distribution grid flexibility enhancement |
| topic | distributed generation soft open point electric vehicle Monte Carlo sampling second-order cone programming |
| url | https://www.mdpi.com/1996-1073/18/3/694 |
| work_keys_str_mv | AT jiefang electricvehicleandsoftopenpointscoplanningforactivedistributiongridflexibilityenhancement AT wenwuli electricvehicleandsoftopenpointscoplanningforactivedistributiongridflexibilityenhancement AT dunchuchen electricvehicleandsoftopenpointscoplanningforactivedistributiongridflexibilityenhancement |