Distribution System Operation with Electric Vehicle Charging Schedules and Renewable Energy Resources
Abstract
:1. Introduction
2. Mathematical Formulation
2.1. Objective Function
2.2. First-Step Restrictions Stage
2.3. Second-Step Restrictions Stage
3. Numerical Study and Results
3.1. Numerical Study
- Charging efficiency is 85% for all EVs.
- Minimum and maximum SoC is 0.2 and 1, respectively.
- The bidirectional capability of EVs (V2G), to inject power to the network has not been considered. EV charging can only be carried out at the owner's residence.
- The BMW i3 and Tesla S vehicles include the BMW i wallbox and Tesla wall connectors, respectively, which increase charge power capacity.
- The EVs are loaded to their maximum SoC.
3.2. Case Study and Results
3.2.1. Base Case Study Comparison with Cases 2, 3, and 4
3.2.2. Base Case Study Comparison with Cases 5, 6 and 7
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Nomenclature
Distributed generation index | |
Electrical vehicle index | |
Node index | |
Connection point index with the upstream network | |
Photovoltaic farm index | |
Scenario index | |
Time (in hours) index | |
Arrival time index | |
Linear partitions index in the linearization process | |
Power Index () | |
Wind farm index | |
Unit generation cost | |
EV battery charging efficiency (%) | |
EV battery capacity (kW) | |
Regulation cost in the day-ahead and real-time markets | |
Daily distance traveled by EV (km) | |
Upper limit in quadratic flow discretization (kVA) | |
EV driving efficiency (km/kWh) | |
Maximum current capacity in the line | |
Planned active and reactive power, respectively | |
Market compensation price | |
EV power charging (kW) | |
Probability of each scenario | |
Maximum power capacity of each | |
Day-ahead, and real-time markets regulation, respectively | |
Distribution line resistance and inductance, respectively | |
Maximum, minimum and nominal voltage, respectively | |
Current flow, and quadratic current flow, for the day-ahead and real-time markets, respectively (A) | |
Active and reactive power that flows in upstream direction in the day-ahead and real-time markets, respectively (kW) | |
Active power in the day-ahead and real-time markets, respectively | |
Active and reactive power that flows in downstream direction in the day-ahead and real-time markets, respectively (kW) | |
Reactive power in the day-ahead and real-time markets, respectively | |
EV state-of-charge | |
Power factor | |
Voltage, and quadratic voltage, for the day-ahead and real-time markets, respectively (V) |
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Generator | Power (kW) | |
---|---|---|
1 (Bus 05) | 23.00 | 230.00 |
2 (Bus 13) | 69.00 | 690.00 |
3 (Bus 14) | 46.00 | 460.00 |
EV Model | Battery Capacity (kWh) | Charging Power (kW) | Electrical Driving Efficiency (km/kWh) | EV number |
---|---|---|---|---|
Chevrolet Volt | 16.00 | 3.50 | 3.75 | 01; 06; 11; 16; 21; 26; 31; 36; 41; 46 |
Nissan Leaf | 24.00 | 4.00 | 6.70 | 02; 07; 12; 17; 22; 27; 32 37; 42; 47 |
BMW i3 | 22.00 | 11.00 | 7.20 | 03; 08; 13; 18; 23; 28; 33; 38; 43; 48 |
Tesla S | 60.00 | 11.00 | 6.70 | 04; 09; 14; 19; 24; 29; 34; 39; 44; 49 |
Renault Zoe | 22.00 | 3.50 | 6.70 | 05; 10; 15; 20; 25; 30; 35; 40; 45; 50 |
Time (h) | BUS | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | |
06:00 a.m. | - | - | - | - | - | - | - | - | - | - | - | - | ||
07:00 | - | - | - | - | - | - | - | - | ||||||
08:00 | - | - | ||||||||||||
09:00 | - | - | - | - | - | - | ||||||||
10:00 | - | - | - | - | - | - | - | - | ||||||
11:00 | - | - | - | - | - | - | - | - | - | - | - | - | ||
12:00 a.m. | - | - | - | - | - | - | - | - | - | - | - | - | - | |
01:00 p.m. | - | - | - | - | - | - | - | - | - | - | - | - | - | |
02:00 | - | - | - | - | - | - | - | - | - | - | - | - | ||
03:00 | - | - | - | - | - | - | - | - | - | - | - | |||
04:00 | - | - | - | - | - | - | - | - | - | - | ||||
05:00 | - | - | - | - | ||||||||||
06:00 | - | - | - | - | - | - | - | |||||||
07:00 | - | - | - | - | - | - | - | - | - | |||||
08:00 | - | - | - | - | - | - | - | - | ||||||
09:00 p.m. | - | - | - | - | - | - | - | - | - | - | - |
Case | Penetration (# of EVs) | Controlled/Uncontrolled |
---|---|---|
1 (base case) | 0 | - |
2 | 15 | uncontrolled |
3 | 30 | uncontrolled |
4 | 50 | uncontrolled |
5 | 15 | controlled |
6 | 30 | controlled |
7 | 50 | controlled |
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Osório, G.J.; Shafie-khah, M.; Coimbra, P.D.L.; Lotfi, M.; Catalão, J.P.S. Distribution System Operation with Electric Vehicle Charging Schedules and Renewable Energy Resources. Energies 2018, 11, 3117. https://doi.org/10.3390/en11113117
Osório GJ, Shafie-khah M, Coimbra PDL, Lotfi M, Catalão JPS. Distribution System Operation with Electric Vehicle Charging Schedules and Renewable Energy Resources. Energies. 2018; 11(11):3117. https://doi.org/10.3390/en11113117
Chicago/Turabian StyleOsório, Gerardo J., Miadreza Shafie-khah, Pedro D. L. Coimbra, Mohamed Lotfi, and João P. S. Catalão. 2018. "Distribution System Operation with Electric Vehicle Charging Schedules and Renewable Energy Resources" Energies 11, no. 11: 3117. https://doi.org/10.3390/en11113117