Energy Management Method for Fast-Charging Stations with the Energy Storage System to Alleviate the Voltage Problem of the Observation Node
Abstract
:1. Introduction
2. Problem Formulation
2.1. FCS Model
2.2. Impact on the Radial Distribution Network
2.3. Optimization Model
3. Analytical Assessment Model of the Nodal Voltage Change
3.1. The Radial Distribution Network Model
3.2. The AMM
3.3. The Control Characteristic of βo
4. The VCOM
Algorithm 1: Calculate |
1: INPUT: This algorithm knows the acceptable probability of the nodal voltage change at the observation node () at time interval κ, the initial nodal load at each node at time interval κ, the adjustment step size of (∆), basic information of the distribution network, which can be used to calculate power flow by using traditional Newton power flow method. |
2: OUTPUT: = [, ,…, ] |
3: PROCEDURE: |
4: Obtain the nodal voltage at each node by using traditional Newton power flow method. |
4: for o = 1 to n do |
5: Obtain according to Equation (31) |
6: Obtain Foκ(.) according to Equation (32) |
7: for I = 1 to N do |
8: if (.) ≥ |
9: ←—∆ |
10: Update Foκ(.) by plugging into Equation (32) |
11: else |
12 ← |
13: end if |
14: end for |
15: end for |
5. Case Study and Discussion
5.1. The Performance of the AMM
5.2. The Effect of the Proposed Day-Ahead ESS Strategy
- (i)
- Case 1: the traditional PV-ESS complementarity strategy is used for the ESS.
- (ii)
- Case 2: the strategy proposed in this paper is used for the ESS.
6. Conclusions
- A voltage change optimization model (VCOM) considering the randomness of the EV load is constructed to alleviate the voltage change problem caused by EV fast charging and it can be easily solved by traditional intelligent algorithms, such as GA.
- An analytical assessment model (AAM) of the nodal voltage change with shorter computational time and higher reliability is proposed.
Author Contributions
Funding
Conflicts of Interest
Nomenclature
Total grid load at the FCS j at κth time interval. | |
Expectation of . | |
. | Standard change of |
Output power of the PV at the FCS j at κth time interval. | |
Charge–discharge active power of the ESS at the FCS j at κth time interval. | |
The NFCL at the node j with the FCS at κth time interval. | |
The EV’s charging load at the FCS j at κth time interval. | |
Expectation of . | |
Standard deviation of . | |
Rated capacity of the service transformer at the FCS j. | |
Nodal voltage change limit at the observation node o at κth time interval. | |
Shape parameters for the nodal voltage change at observation node o at κth time interval. | |
Control parameter for the nodal voltage change at observation node o at κth time interval. | |
xκ | Optimization variable at κth time interval. |
pp | Initial population number. |
Us | Phase voltage at the source node s. |
Ud | Phase voltage at the load node d. |
Uo | Phase voltage at the observation node o. |
Conjugate complex draw power at node d. | |
Conjugate phase voltage at node d. | |
Zod | Shared impedance between node d and observation node o from the source node s. |
Rated upper limit of the charge-discharge active power of the ESS at the FCS j. | |
Rated lower limit of the charge-discharge active power of the ESS at the FCS j. | |
Dynamic lower limit of the charge-discharge active power of the ESS at the FCS j at the κth time interval. | |
. | Active power output of the ESS at the FCS j at κth time interval. |
A preset constant for restraining . | |
SOC | State of charge. |
The initial SOC of the ESS at the FCS j at the beginning of the day. | |
A preset constant for restraining the SOC for the FCS j. | |
Rated upper limit of the SOC. | |
Rated lower limit of the SOC. | |
Value of the SOC of the ESS at the FCS j at κth time interval. | |
Γ(.) | Gamma function. |
Φ(.) | Normal probability distribution function. |
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Parameter | Description | Unit | Value |
---|---|---|---|
STrans | Rated capacity of the service transformer. | kVA | 1000 |
SPV | Rated capacity of the PV. | kWp | 50 |
PS+ | Rated upper boundary of the charge-discharge active power of the ESS. | kW | 250 |
PS− | Rated lower boundary of the charge-discharge active power of the ESS. | kW | −250 |
SOC0 | The initial SOC for the ESS at the beginning of the day. | % | 50 |
SOC+ | Rated upper boundary of the SOC of the ESS. | % | 30 |
SOC− | Rated lower boundary of the SOC of the ESS. | % | 80 |
ES | Rated capacity of the ESS. | kWh | 1000 |
κ | The EV Load at κth Time Interval/kW | |||
---|---|---|---|---|
1~4 | N(789,1922) | N(532,2182) | N(167,1212) | E(40) |
5~8 | E(40) | E(40) | N(223,402) | N(108,742) |
9~12 | N(107,952) | N(190,1322) | N(294,1592) | N(406,1532) |
13~16 | N(547,1442) | N(572,1692) | N(575,1852) | N(352,1982) |
17~20 | N(207,1632) | N(306,1452) | N(312,1632) | N(309,1802) |
21~24 | N(328,1802) | N(350,1432) | N(494,1542) | N(690,1802) |
κ | The EV Load at κth Time Interval/kW | |||
---|---|---|---|---|
1~4 | N(789,1922) | N(532,2182) | N(167,1212) | E(40) |
5~8 | E(40) | E(40) | E(40) | N(108,742) |
9~12 | N(107,952) | N(190,1322) | N(294,1592) | N(406,1532) |
13~16 | N(547,1442) | N(572,1692) | N(575,1852) | N(352,1982) |
17~20 | N(207,1632) | N(306,1452) | N(312,1632) | N(309,1802) |
21~24 | N(328,1802) | N(350,1432) | E(40) | N(690,1802) |
Observation Node | The Correlation Coefficient | |||||||
---|---|---|---|---|---|---|---|---|
2~9 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 |
10~17 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 |
18~25 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 |
26~33 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 |
Methods | Average Time, s | CPU, % |
---|---|---|
MCPFL | 1.527 | 2 |
AMM | 20.313 | 11 |
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Ye, R.; Huang, X.; Yang, Z. Energy Management Method for Fast-Charging Stations with the Energy Storage System to Alleviate the Voltage Problem of the Observation Node. World Electr. Veh. J. 2021, 12, 234. https://doi.org/10.3390/wevj12040234
Ye R, Huang X, Yang Z. Energy Management Method for Fast-Charging Stations with the Energy Storage System to Alleviate the Voltage Problem of the Observation Node. World Electric Vehicle Journal. 2021; 12(4):234. https://doi.org/10.3390/wevj12040234
Chicago/Turabian StyleYe, Rui, Xueliang Huang, and Zexin Yang. 2021. "Energy Management Method for Fast-Charging Stations with the Energy Storage System to Alleviate the Voltage Problem of the Observation Node" World Electric Vehicle Journal 12, no. 4: 234. https://doi.org/10.3390/wevj12040234