Charge Control and Operation of Electric Vehicles in Power Grids: A Review
Abstract
:1. Introduction
2. Background
3. Control and Operation of Electric Vehicles
3.1. Deterministic Control Approaches
3.1.1. Centralized Charging Control
- The need for large investment in the communication infrastructure, especially at the distribution level.
- An enormous number of messages needs to be communicated within a very limited period of time, which might cause communication issues, such as high latency and low quality of service.
- High computation burden for processing a large amount of data.
- Loss of the main communication link or problems with the central controller might have severe consequences on the system integrity.
- User privacy issues since the central controller has access to the data of all users.
3.1.2. Decentralized Charging Control
- They do not always ensure optimality and best use of resources.
- They may result in a rebound effect, which can be harmful to the system.
- They have a limited ability in participating in ancillary service markets.
- They are vulnerable to changes in customers’ behavior.
3.1.3. Autonomous Charging Control
- Lack of the optimal operation of the system.
- Lack of ability to participate in ancillary service markets.
- May result in a rebound effect.
- Vulnerable to changes in customers’ behavior.
3.2. Real Time and Stochastic Operation Approaches
3.2.1. Day-Ahead Scheduling with Uncertainties
3.2.2. Real Time Dispatching
4. Open Research Problems
5. Conclusions
Author Contributions
Conflicts of Interest
References
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Model | Type | Capacity (kWh) | Charging Rate (kW) | Electric Range (miles) | Price ($) |
---|---|---|---|---|---|
Nissan Leaf | BEV | 30 | 6.6 | 107 | $29,000 |
Tesla model S | BEV | 100 | 10 | 315 | $71,000 |
Chevrolet Bolt | BEV | 60 | 7.2 | 238 | $37,500 |
Toyota Prius | PHEV | 9 | 3.3 | 25 | $28,000 |
Ford Fusion Energy | PHEV | 7 | 3.3 | 19 | $33,900 |
Charging Level | Vehicle Range Added per Charging Time and Power | Supply Power | Unit Cost Range Per (Single Port) |
---|---|---|---|
AC Level 1 | 4 miles/h @ 1.4 kW | 120 V/20 A (14–16 A continuous) | $300–$1500 |
6 miles/h @ 1.9 kW | |||
AC Level 2 | 10 miles/h @ 3.4 kW | (208/240) VAC (16–80 A continuous) | $400–$6500 |
20 miles/h @ 6.6 kW | |||
60 miles/h @ 19.2 kW | |||
DC Fast Charging | 24 miles/h @ 24 kW | (208/240) VAC 3-phase ~(20–400 A AC) | $10,000–$40,000 |
50 miles/h @ 50 kW | |||
90 miles/h @ 90 kW |
Ref. Number | Technique Used | Bidirectional Battery Flow | Utility Constraints Consideration |
---|---|---|---|
Centralized Techniques | |||
[22] | Rolling Scheduling Using Linear Programming | ✓ | ✓ |
[23] | Tie-Line Bias Control | ✓ | ✗ |
[24] | Tie-Line Bias Control | ✓ | ✗ |
[25] | Linear Programming | ✓ | ✗ |
[30] | Multi-Objective Optimization Using Particle Swarm | ✗ | ✗ |
[31] | Non-Linear Programming Using GAMS | ✗ | ✓ |
[32] | Linear Programming | ✗ | ✗ |
[33] | Quadratic Optimization | ✗ | ✗ |
[34] | Linear Programming | ✗ | ✓ |
[35] | Additive Increase, Multiplicative Decrease Algorithm | ✗ | ✓ |
[37] | Fuzzy Control | ✗ | ✗ |
[38] | Linear Programming | ✗ | ✓ |
[39] | Receding Horizon Using Linear Programming | ✗ | ✓ |
Decentralized Techniques | |||
[4] | Gradient Optimization | ✗ | ✓ |
[40] | Fuzzy Control | ✓ | ✓ |
[41] | Artificail Neural Networks- Wavelet Transform | ✓ | ✗ |
[42] | Hybrid-PSO& Linear Programming | ✗ | ✗ |
[44] | Linear Programming | ✗ | ✗ |
[45] | Linear Programming | ✗ | ✓ |
[46] | Congestion Pricing Algorithm | ✓ | ✓ |
[47] | Game Theory | ✗ | ✗ |
[48] | Non-Cooperative Game Theory | ✗ | ✗ |
[49] | Game Theory | ✗ | ✗ |
[50] | Game Theory | ✗ | ✗ |
[51] | Non-Cooperative Game Theory | ✗ | ✗ |
[52] | Normalized Nash Game | ✗ | ✗ |
[53] | Stochastic Mean Field Game Theory | ✗ | ✗ |
[54] | Additive Increase, Multiplicative Decrease Algorithm | ✗ | ✗ |
[55] | Probability Theory | ✗ | ✓ |
[56] | Fuzzy Control | ✓ | ✓ |
[57] | Fuzzy Control | ✓ | ✓ |
[58] | Additive Increase, Multiplicative Decrease Algorithm | ✗ | ✓ |
Autonomous Techniques | |||
[59] | Linear Programming | ✗ | ✓ |
[60] | Droop Controller | ✓ | ✓ |
[61] | Droop Controller | ✓ | ✓ |
[62] | Droop Controller | ✗ | ✓ |
[63] | Droop Controller | ✓ | ✓ |
[64] | Droop Controller | ✓ | ✓ |
[65] | If-Then Rules | ✗ | ✓ |
[66] | Proportional Controlller | ✗ | ✓ |
[67] | Droop Controller | ✗ | ✓ |
[68] | Exponential Controller | ✗ | ✓ |
[69] | Exponential Controller | ✗ | ✓ |
[70] | Fuzzy Controller | ✗ | ✓ |
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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Faddel, S.; Al-Awami, A.T.; Mohammed, O.A. Charge Control and Operation of Electric Vehicles in Power Grids: A Review. Energies 2018, 11, 701. https://doi.org/10.3390/en11040701
Faddel S, Al-Awami AT, Mohammed OA. Charge Control and Operation of Electric Vehicles in Power Grids: A Review. Energies. 2018; 11(4):701. https://doi.org/10.3390/en11040701
Chicago/Turabian StyleFaddel, Samy, Ali T. Al-Awami, and Osama A. Mohammed. 2018. "Charge Control and Operation of Electric Vehicles in Power Grids: A Review" Energies 11, no. 4: 701. https://doi.org/10.3390/en11040701
APA StyleFaddel, S., Al-Awami, A. T., & Mohammed, O. A. (2018). Charge Control and Operation of Electric Vehicles in Power Grids: A Review. Energies, 11(4), 701. https://doi.org/10.3390/en11040701