Optimal Planning of Electric Vehicle Charging Stations Considering User Satisfaction and Charging Convenience
Abstract
:1. Introduction
2. Aernel Density Analysis
3. Electric Vehicle User Satisfaction Model
4. User Charging Convenience
5. Electric Vehicle Charging Station Site-Selection Model
5.1. Suppose
- (1)
- Each demand point only goes to the nearest charging station for charging;
- (2)
- Each demand point represents a small area of fixed area;
- (3)
- All electric vehicles have the same battery capacity and model;
- (4)
- While going to the charging station to charge, the driving speed of the electric vehicle remains constant;
- (5)
- In the study area, the demand for the demand point is the same every day, and the demand density is equal to the population density value expressed as a percentage.
5.2. Goals and Constraints
- -
- Objective function one: Maximize user satisfaction
- -
- Objective function two: Maximize the charging convenience
- (1)
- Each demand point can only correspond to one to-be-taken point.
- (2)
- Meeting priority conditions and charging needs of electric vehicles. Formula (13) indicates that the user satisfaction is satisfied under the condition that the charging convenience of the electric vehicle charging station is satisfied. Meanwhile, the charging demand of electric vehicles is met at the to-be-taken point .
- (3)
- Meeting demand points are allocated to corresponding charging stations. Formula (14) indicates that the built electric vehicle charging station meets the changing needs of all demand points.
- (4)
- Meeting the capacity requirements of the site-selection scheme. Formula (15) represents the number of charging stations in all site-selection schemes.
- (5)
- indicates that the user is satisfied with the electric vehicle charging station at the to-be-taken point . indicates that the user is not satisfied with the electric vehicle charging station at the to-be-taken point . indicates that the charging convenience of the electric vehicle charging station is high in the to-be-taken point . indicates that the charging convenience of the electric vehicle charging station is low at the to-be-taken point . Analyzing conditions are:
6. Optimized Immune Algorithm
7. Region and Points Are Selected
8. Simulation
8.1. Analysis of the Example
8.2. Algorithm Comparison
9. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Degree | Score |
---|---|
Big impact | 5 |
Greater impact | 4 |
General impact | 3 |
Lesser impact | 2 |
No impact | 1 |
Number of Sites Built | Average Satisfaction |
---|---|
51 | 60.63% |
52 | 65.82% |
53 | 74.7% |
54 | 79.94% |
55 | 83.18% |
56 | 85.04% |
Average Service Capacity | Average User Density | Average Charging Convenience | |
---|---|---|---|
Traditional site selection | 116 | 70% | 4195 |
Site-selection plan in this paper | 128 | 73% | 4657 |
Optimal Solution | Average Solution | Standard Deviation | |
---|---|---|---|
Traditional immune algorithm | 0.17493 | 0.21110 | 0.04843 |
Optimized immune algorithm | 0.16975 | 0.18391 | 0.01712 |
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Xu, D.; Pei, W.; Zhang, Q. Optimal Planning of Electric Vehicle Charging Stations Considering User Satisfaction and Charging Convenience. Energies 2022, 15, 5027. https://doi.org/10.3390/en15145027
Xu D, Pei W, Zhang Q. Optimal Planning of Electric Vehicle Charging Stations Considering User Satisfaction and Charging Convenience. Energies. 2022; 15(14):5027. https://doi.org/10.3390/en15145027
Chicago/Turabian StyleXu, Di, Wenhui Pei, and Qi Zhang. 2022. "Optimal Planning of Electric Vehicle Charging Stations Considering User Satisfaction and Charging Convenience" Energies 15, no. 14: 5027. https://doi.org/10.3390/en15145027
APA StyleXu, D., Pei, W., & Zhang, Q. (2022). Optimal Planning of Electric Vehicle Charging Stations Considering User Satisfaction and Charging Convenience. Energies, 15(14), 5027. https://doi.org/10.3390/en15145027