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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Main Authors: Jie Fang, Wenwu Li, Dunchu Chen
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Energies
Subjects:
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.
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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