Collaborative Planning of Community Charging Facilities and Distribution Networks
The construction of community charging facilities and supporting distribution networks based on the predicted results of electric vehicle (EV) charging power in saturation year has resulted in a large initial idleness of the distribution network and a serious waste of assets. To solve this problem,...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-05-01
|
| Series: | World Electric Vehicle Journal |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2032-6653/14/6/143 |
| _version_ | 1797592258635104256 |
|---|---|
| author | Xiao-Hong Diao Jing Zhang Rui-Yu Wang Jiang-Wei Jia Zhi-Liang Chang Bin Li Xuan Zhao |
| author_facet | Xiao-Hong Diao Jing Zhang Rui-Yu Wang Jiang-Wei Jia Zhi-Liang Chang Bin Li Xuan Zhao |
| author_sort | Xiao-Hong Diao |
| collection | DOAJ |
| description | The construction of community charging facilities and supporting distribution networks based on the predicted results of electric vehicle (EV) charging power in saturation year has resulted in a large initial idleness of the distribution network and a serious waste of assets. To solve this problem, this paper proposes a collaborative planning method for urban community charging facilities and distribution networks. First, based on the load density method and occupancy rate to predict the base electricity load in the community, the Bass model and charging probability are used to predict the community’s electric vehicle charging load. Taking the minimum annual construction and operation costs of the community distribution network as the objective function, the power supply topology of the distribution network for a new community is optimized by using Prim and single-parent genetic algorithms. Finally, the proposed scheme is verified by using the actual community data of a certain city in China as an analysis example, and the scheme of one-time planning of the distribution network and yearly construction of charging facilities is given. |
| first_indexed | 2024-03-11T01:48:54Z |
| format | Article |
| id | doaj.art-4487edb235b5432cacc3443f96b49cfd |
| institution | Directory Open Access Journal |
| issn | 2032-6653 |
| language | English |
| last_indexed | 2024-03-11T01:48:54Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj.art-4487edb235b5432cacc3443f96b49cfd2023-11-18T13:06:23ZengMDPI AGWorld Electric Vehicle Journal2032-66532023-05-0114614310.3390/wevj14060143Collaborative Planning of Community Charging Facilities and Distribution NetworksXiao-Hong Diao0Jing Zhang1Rui-Yu Wang2Jiang-Wei Jia3Zhi-Liang Chang4Bin Li5Xuan Zhao6Beijing Laboratory, Beijing Engineering Technology Research Center of Electric Vehicle Charging/Battery Swap, China Electric Power Research Institute, Beijing 100192, ChinaBeijing Laboratory, Beijing Engineering Technology Research Center of Electric Vehicle Charging/Battery Swap, China Electric Power Research Institute, Beijing 100192, ChinaNanyang Feilong Power Supply Service Co., Ltd., Xinye County Branch, Nanyang 473500, ChinaSchool of Electrical Engineering, Tiangong University, Tianjin 300387, ChinaSchool of Electrical Engineering, Tiangong University, Tianjin 300387, ChinaBeijing Laboratory, Beijing Engineering Technology Research Center of Electric Vehicle Charging/Battery Swap, China Electric Power Research Institute, Beijing 100192, ChinaBeijing Laboratory, Beijing Engineering Technology Research Center of Electric Vehicle Charging/Battery Swap, China Electric Power Research Institute, Beijing 100192, ChinaThe construction of community charging facilities and supporting distribution networks based on the predicted results of electric vehicle (EV) charging power in saturation year has resulted in a large initial idleness of the distribution network and a serious waste of assets. To solve this problem, this paper proposes a collaborative planning method for urban community charging facilities and distribution networks. First, based on the load density method and occupancy rate to predict the base electricity load in the community, the Bass model and charging probability are used to predict the community’s electric vehicle charging load. Taking the minimum annual construction and operation costs of the community distribution network as the objective function, the power supply topology of the distribution network for a new community is optimized by using Prim and single-parent genetic algorithms. Finally, the proposed scheme is verified by using the actual community data of a certain city in China as an analysis example, and the scheme of one-time planning of the distribution network and yearly construction of charging facilities is given.https://www.mdpi.com/2032-6653/14/6/143collaborative planningcharging facilitydistribution networkelectric vehiclecharging load forecastingcommunity |
| spellingShingle | Xiao-Hong Diao Jing Zhang Rui-Yu Wang Jiang-Wei Jia Zhi-Liang Chang Bin Li Xuan Zhao Collaborative Planning of Community Charging Facilities and Distribution Networks World Electric Vehicle Journal collaborative planning charging facility distribution network electric vehicle charging load forecasting community |
| title | Collaborative Planning of Community Charging Facilities and Distribution Networks |
| title_full | Collaborative Planning of Community Charging Facilities and Distribution Networks |
| title_fullStr | Collaborative Planning of Community Charging Facilities and Distribution Networks |
| title_full_unstemmed | Collaborative Planning of Community Charging Facilities and Distribution Networks |
| title_short | Collaborative Planning of Community Charging Facilities and Distribution Networks |
| title_sort | collaborative planning of community charging facilities and distribution networks |
| topic | collaborative planning charging facility distribution network electric vehicle charging load forecasting community |
| url | https://www.mdpi.com/2032-6653/14/6/143 |
| work_keys_str_mv | AT xiaohongdiao collaborativeplanningofcommunitychargingfacilitiesanddistributionnetworks AT jingzhang collaborativeplanningofcommunitychargingfacilitiesanddistributionnetworks AT ruiyuwang collaborativeplanningofcommunitychargingfacilitiesanddistributionnetworks AT jiangweijia collaborativeplanningofcommunitychargingfacilitiesanddistributionnetworks AT zhiliangchang collaborativeplanningofcommunitychargingfacilitiesanddistributionnetworks AT binli collaborativeplanningofcommunitychargingfacilitiesanddistributionnetworks AT xuanzhao collaborativeplanningofcommunitychargingfacilitiesanddistributionnetworks |