Coordinated Control Strategy and Validation of Vehicle-to-Grid for Frequency Control
<p>An integrated validation system based on power hardware‒in‒the‒loop (PHIL) simulation for Vehicle‒to‒Grid (V2G) and microgrid at the Canadian Centre for Housing Technology (CCHT)‒V2G testing facility.</p> "> Figure 2
<p>Frequency data (<b>a</b>) collected from the input grid at the NRC campus at 08:30 for 100 min on 15 May 2018, and (<b>b</b>) rounded as for the inputs to the grid simulator for primary frequency control (PFC) simulation testing.</p> "> Figure 3
<p>Histogram of frequency data collected from the input grid at the NRC campus at 08:30 for 100 min on 15 May 2018.</p> "> Figure 4
<p>Droop-control characteristic designed for grid simulation on primary frequency control using V2G at the NRC‒CCHT.</p> "> Figure 5
<p>Normalized 2 h average standard deviation signal as a part of the 24 h frequency regulation duty cycle determined by Sandia National Laboratories [<a href="#B20-energies-14-02530" class="html-bibr">20</a>].</p> "> Figure 6
<p>Simulink model of single-vehicle-based vehicle-to-home/grid (V2H/V2G).</p> "> Figure 7
<p>(<b>a</b>) Simulation result of a neural network with one hidden layer and 6 neurons and (<b>b</b>) machine learning (ML)—based prediction of photovoltaic (PV) power generation profile for 24 h on 15 May 2012, at the CCHT facility in Ottawa, ON, Canada.</p> "> Figure 8
<p>Simulated house load profile (24 h).</p> "> Figure 9
<p>Combined primary and secondary frequency control droop loop and electric vehicle (EV) battery model.</p> "> Figure 10
<p>Simulink model of multi‒vehicle‒based vehicle‒to‒building/grid (V2B/V2G).</p> "> Figure 11
<p>Coordinated control algorithm for frequency control.</p> "> Figure 12
<p>(<b>a</b>) Frequencies produced by grid simulator in AC mains and monitored by power analyzer and (<b>b</b>) droop control-based AC target power for DCFC/EV and AC output actual power responding from DCFC/EV (positive: charging, negative: discharging) for PFC at the CCHT-V2G facility.</p> "> Figure 13
<p>Comparison of (<b>a</b>) AC output from DCFC/EV (positive: charging, negative: discharging), (<b>b</b>) frequency deviation without V2G or (<b>c</b>) with V2G, and (<b>d</b>) state of charge (SOC) variation obtained from empirical testing and simulation on the single-vehicle-based PFC for 100 min (starting SOC: 78.8%).</p> "> Figure 14
<p>Simulink-based Simulation of (<b>a</b>) AC output from DC fast charger (DCFC)/EV (positive: charging, negative: discharging) and (<b>b</b>) SOC variation obtained from empirical testing and simulation using a normalized 2 h average standard deviation signal on single-vehicle-based SFC operation for 2 h (starting SOC: 80.0%).</p> "> Figure 15
<p>Simulink-based simulation of (<b>a</b>) AC output from DCFC/EV (positive: charging, negative: discharging), (<b>b</b>) frequency deviation, (<b>c</b>) SOC variation, (<b>d</b>) PV power, (<b>e</b>) house load, (<b>f</b>) power flow from PV to the external grid after the supporting load and V2G, (<b>g</b>) power flow from combined PV and V2G to external grid, and (<b>h</b>) power flow from external grid to nanogrid for PFC operation in single-vehicle-based V2H/V2G (starting SOC: 80%, duration: 13 h from 06:00 to 19:00).</p> "> Figure 16
<p>Simulink-based simulation of (<b>a</b>) AC output from DCFC/EV (time interval: 5 min, positive: charging, negative: discharging), (<b>b</b>) frequency deviation, (<b>c</b>) SOC variation, (<b>d</b>) PV power, (<b>e</b>) building load demands, (<b>f</b>) power flow from PV to the external grid after the supporting load and V2G, (<b>g</b>) power flow from combined PV and V2G to the external grid, and (<b>h</b>) power flow from the external grid to microgrid for PFC operation using the coordinated control algorithm with 5 EVs (duration: 13 h from 06:00 to 19:00).</p> "> Figure 17
<p>Simulink-based simulation of the total V2G power flow for PFC operation with or without the proposed coordinated control algorithm with 5 EVs.</p> ">
Abstract
:1. Introduction
2. Methodology
2.1. Vehicle-to-Grid (V2G) Testing Facility
2.2. Primary Frequency Control (PFC)
2.3. Secondary Frequency Control (SFC)
3. Modeling, Simulation, and Validation
3.1. Single-Vehicle-based Vehicle-to-Grid (V2G)
3.1.1. Simulated Profiles of Photovoltaic (PV) Renewables and House Loads
3.1.2. Primary and Secondary Frequency Control
3.2. Multi-Vehicle-Based V2G
3.2.1. Models
3.2.2. Coordinated Control Strategy and Algorithm
4. Results and Discussion
4.1. Experimental Frequency Control Testing and Simulation on Single-Vehicle-Based Frequency Control
4.2. Simulation of Multi-Vehicle-based Frequency Control
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Nomenclature
fk | Grid frequency at time k |
fo | Reference (nominal) frequency |
Δfk | Frequency deviation at time k |
ηac-to-dc | AC-to-DC conversion efficiency |
ηdc-to-ac | DC-to-AC conversion efficiency |
Ern | Rated capacity of the nth EV battery |
ΔEn | Energy variation of the nth EV battery |
SOCin | Initial state of charge of the nth EV battery |
SOCn,k | State of charge of the nth EV battery at time k |
Pcn | Constant scheduled charging power of the nth EV for achieving the charging demand |
Pn,k | V2G power at the nth EV at time k |
AGC | Automatic generation control |
tin | Plug-in time |
tout | Plug-out time |
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No | Conditions | EV-1 | EV-2 | EV-3 | EV-4 | EV-5 | Remarks |
---|---|---|---|---|---|---|---|
1 | Initial SOC (%) | 40 | 80 | 50 | 90 | 70 | - When EV is connected to DCFC |
2 | End SOC (%) | 60 | 80 | 80 | 70 | 60 | - Specified by EV driver for departure |
3 | ΔSOC | 20 | 0 | 30 | −20 | −10 | - End SOC (SOCe) minus Initial SOC (SOCi) |
4 | Departure time | 15:00 | 16:00 | 18:00 | 17:00 | 16:00 | - Specified by EV driver |
5 | EV battery energy capacity (kWh) | 24 | 30 | 40 | 24 | 30 | - Depending on EV model-year |
6 | Max. C-rate allowable | 0.5 | 2.0 | 1.0 | 0.5 | 0.8 | - Permitted by EV driver - Options 1/2/3/4: 0.5/0.8/1.0/2.0C |
7 | Max. usable charging/discharging battery energy capacity (kWh) | 10 | 15 | 15 | 10 | 15 | - Specified by EV driver for PFC/SFC |
No | Parameters | Values | Remarks |
---|---|---|---|
1 | Initial SOC (%) | 80 | - When EV is connected to DCFC |
2 | End SOC (%) | 90 | - For EV departure |
3 | Starting time of PFC operation | 9:00 | |
4 | Ending time of PFC operation | Same with starting time for charging EV | - Starting time for charging EV is determined by calculating minimum time to charge EV with allowable power for preparing EV departure. |
5 | EV departure time | 16:00 | |
6 | EV battery capacity (kWh) | 40 | |
7 | DCFC power rating (kW) | 10 | |
8 | EV charging power (kW) | 5 or 10 | - For SOC adjustment to prepare EV departure |
9 | Daily schedule on simulation | 6:00 ~ 19:00 | - 13 h |
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Yoo, Y.; Al-Shawesh, Y.; Tchagang, A. Coordinated Control Strategy and Validation of Vehicle-to-Grid for Frequency Control. Energies 2021, 14, 2530. https://doi.org/10.3390/en14092530
Yoo Y, Al-Shawesh Y, Tchagang A. Coordinated Control Strategy and Validation of Vehicle-to-Grid for Frequency Control. Energies. 2021; 14(9):2530. https://doi.org/10.3390/en14092530
Chicago/Turabian StyleYoo, Yeong, Yousef Al-Shawesh, and Alain Tchagang. 2021. "Coordinated Control Strategy and Validation of Vehicle-to-Grid for Frequency Control" Energies 14, no. 9: 2530. https://doi.org/10.3390/en14092530