Optimal routing and power management of electric vehicles in coupled power distribution and transportation systems

被引:21
作者
Aghajan-Eshkevari, Saleh [1 ]
Ameli, Mohammad Taghi [1 ,2 ]
Azad, Sasan [1 ,2 ]
机构
[1] Shahid Beheshti Univ, Dept Elect Engn, Tehran, Iran
[2] Shahid Beheshti Univ, Elect Network Inst, Tehran, Iran
关键词
Electric vehicles; Active and reactive power management; Distribution network; Transportation system; Trip chain; Optimal routing;
D O I
10.1016/j.apenergy.2023.121126
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
With the increasing penetration level of electric vehicles (EVs) in the transportation network, it is necessary to control the charging and discharging process of EVs to avoid operational issues in the power grid. Therefore, in this paper, a two-stage framework is presented for EVs optimal routing and their active and reactive power control in the distribution grid. In the first stage, the EVs mobility in the transportation system is taken into consideration. On this basis, EV daily trips in the transportation network are modelled using the trip chain method. Also, the Dijkstra algorithm is utilized for optimal routing with the shortest travel time between the origin and the destination node. Furthermore, the effects of ambient temperature, traffic congestion and road type on the EVs energy consumption are assessed. In the second stage, optimal active and reactive power exchange of EVs with the distribution grid is carried out. Thus, a mixed-integer linear programming (MILP) model is proposed that simultaneously considers EV owners' and the distribution network operator's benefits as the optimization goals. The EV battery degradation cost due to the discharging of active power is also integrated into the objective function of the optimization problem. The proposed framework is implemented on a standard IEEE 33-bus system coupled with a 30-node transportation network. The simulation results show that the presented method can reduce the loss cost of the distribution grid and benefit EV owners compared to different charging strategies. In addition, with the battery technology development, the proposed framework can significantly improve the distribution system operation, decrease environmental issues, and reduce EV owner's costs.
引用
收藏
页数:20
相关论文
共 40 条
[1]  
Aghajan-Eshkevari S, 2022, ELECT VEHICLE INTEGR, P129
[2]   Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies [J].
Aghajan-Eshkevari, Saleh ;
Azad, Sasan ;
Nazari-Heris, Morteza ;
Ameli, Mohammad Taghi ;
Asadi, Somayeh .
SUSTAINABILITY, 2022, 14 (04)
[3]  
Ameli MT, 2021, Energy storage in energy markets, P235
[4]   Probabilistic reliability evaluation of distribution systems considering the spatial and temporal distribution of electric vehicles [J].
Anand, M. P. ;
Bagen, Bagen ;
Rajapakse, Athula .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2020, 117
[5]  
[Anonymous], 2021, Electric Vehicle Outlook 2021 BNEF
[6]  
[Anonymous], 2012, The iv formulation and linear approximations of the ac optimal power flow problem, DOI DOI 10.1287/OPRE.49.2.235.13537
[7]   Value of optimal trip and charging scheduling of commercial electric vehicle fleets with Vehicle-to-Grid in future low inertia systems [J].
Blatiak, Alicia ;
Bellizio, Federica ;
Badesa, Luis ;
Strbac, Goran .
SUSTAINABLE ENERGY GRIDS & NETWORKS, 2022, 31
[8]   Spatio-Temporal Model for Evaluating Demand Response Potential of Electric Vehicles in Power-Traffic Network [J].
Chen, Lidan ;
Zhang, Yao ;
Figueiredo, Antonio .
ENERGIES, 2019, 12 (10)
[9]   Charging Load Prediction and Distribution Network Reliability Evaluation Considering Electric Vehicles' Spatial-Temporal Transfer Randomness [J].
Cheng, Shan ;
Wei, Zhaobin ;
Shang, Dongdong ;
Zhao, Zikai ;
Chen, Huiming .
IEEE ACCESS, 2020, 8 :124084-124096
[10]   A unit commitment model for optimal vehicle-to-grid operation in a power system [J].
Egbue, Ona ;
Uko, Charles ;
Aldubaisi, Ali ;
Santi, Enrico .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2022, 141