Charge Pricing Optimization Model for Private Charging Piles in Beijing
Abstract
:1. Introduction
2. Charge Pricing Factors of PEVs
2.1. Charging Probability of PEVs
2.2. Price Response of PEV Users
2.3. Charging Load Forecast of PCPs
2.4. Energy-Saving and Emission-Reduction Effects of PCPs
2.5. Economic Benefits of the Power System
3. Charge Pricing Model of PCPs
3.1. Constraints
3.2. Optimization Goals
3.3. Flow Chart of the Optimized Peak-Valley TOU Charging Price
4. Empirical Results
4.1. Initial Data of the Model
4.2. Optimization Results
4.3. Sensitivity Analysis
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Time | Probability | Time | Probability |
---|---|---|---|
0 | 0.0151 | 12 | 0.0383 |
1 | 0.0080 | 13 | 0.0568 |
2 | 0.0039 | 14 | 0.0774 |
3 | 0.0017 | 15 | 0.0987 |
4 | 0.0007 | 16 | 0.1110 |
5 | 0.0003 | 17 | 0.1169 |
6 | 0.0006 | 18 | 0.1129 |
7 | 0.0015 | 19 | 0.1001 |
8 | 0.0033 | 20 | 0.0815 |
9 | 0.0070 | 21 | 0.0608 |
10 | 0.0134 | 22 | 0.0417 |
11 | 0.0237 | 23 | 0.0262 |
Time | Load (MW) | Time | Load (MW) |
---|---|---|---|
0 | 9962.86 | 12 | 17,322.84 |
1 | 9369.53 | 13 | 17,228.38 |
2 | 8919.59 | 14 | 17,261.56 |
3 | 8643.24 | 15 | 17,316.02 |
4 | 8567.24 | 16 | 17,118.31 |
5 | 9066.06 | 17 | 16,306.82 |
6 | 10,450.95 | 18 | 15,813.80 |
7 | 12,571.51 | 19 | 16,056.32 |
8 | 14,914.15 | 20 | 16,239.37 |
9 | 16,413.02 | 21 | 15,380.58 |
10 | 17,297.23 | 22 | 13,709.11 |
11 | 17,366.19 | 23 | 11,860.02 |
Wind Power | Hydroelectric Power | Nuclear Power | Coal Power | |
---|---|---|---|---|
Installed capacity (MW) | 2000 | 4000 | 3000 | 10,000 |
Generation costs (yuan/MWh) | 248 | 120 | 80 | 270 |
Generation carbon emissions (t/MWh) | 0.298 a | 0.1733 b | 0.00675 b | 0.86252 b |
Time | Utilization Rate | Time | Utilization Rate |
---|---|---|---|
0 | 0.41 | 12 | 0.23 |
1 | 0.59 | 13 | 0.16 |
2 | 0.71 | 14 | 0.28 |
3 | 0.84 | 15 | 0.35 |
4 | 0.69 | 16 | 0.29 |
5 | 0.57 | 17 | 0.25 |
6 | 0.49 | 18 | 0.18 |
7 | 0.41 | 19 | 0.16 |
8 | 0.22 | 20 | 0.18 |
9 | 0.15 | 21 | 0.29 |
10 | 0.09 | 22 | 0.36 |
11 | 0.22 | 23 | 0.46 |
Period Division | Price (yuan/kWh) | |
---|---|---|
Peak period | 10:00–18:00 | 1.8 |
Average period | 7:00–10:00, 18:00–23:00 | 1 |
Valley period | 23:00–7:00 | 0.4 |
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Share and Cite
Zhang, X.; Liang, Y.; Zhang, Y.; Bu, Y.; Zhang, H. Charge Pricing Optimization Model for Private Charging Piles in Beijing. Sustainability 2017, 9, 2075. https://doi.org/10.3390/su9112075
Zhang X, Liang Y, Zhang Y, Bu Y, Zhang H. Charge Pricing Optimization Model for Private Charging Piles in Beijing. Sustainability. 2017; 9(11):2075. https://doi.org/10.3390/su9112075
Chicago/Turabian StyleZhang, Xingping, Yanni Liang, Yakun Zhang, Yinhe Bu, and Hongyang Zhang. 2017. "Charge Pricing Optimization Model for Private Charging Piles in Beijing" Sustainability 9, no. 11: 2075. https://doi.org/10.3390/su9112075