# Impact of Electric Vehicle Charging on Voltage Unbalance in an Urban Distribution Network

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## Abstract

During the last few years, assessment and evaluation of power quality index due to large-scale penetration of electric vehicles in the system have gained significant attention. Voltage unbalance in the low voltage distribution network is amongst the main power quality issues caused by electric vehicles and therefore it has been quantified and analyzed in this paper. A CIGRE benchmark model of low voltage distribution network is taken as test network and simulations are performed on a sample urban power distribution network. An electric vehicle grid integration and its charging model is implemented in Simulink. Results for two charging strategies including uncontrolled charging and tariff based electric vehicle charging under different electric vehicle penetration levels and uneven charging scenarios have been obtained. The presented results show that an uneven EV charging scenario can cause significant voltage unbalance that goes beyond its allowed limit of 2 %.

## Keywords

Electric vehicle charging Distribution network Power quality Power converters## Introduction

A typical electric vehicle (EV) is equipped with a battery bank which stores energy of some tens of kWh [1, 2]. Furnishing EVs with required amount of power may start from 1.6 kW single phase on-board charging at home to tens of kW for fast charging [3]. In case of charging an EV at home indicates most probable addition of heavy single phase loads in the residential low voltage (LV) distribution network. Nonetheless, a large-scale penetration of EVs may negatively affects distribution network multifariously because of their high demand of electrical energy and it may lead to unwanted peaks in the power consumption and consequent power quality issues including increased power flow in power cables, transformer overloading, voltage drop, voltage unbalance (VU), harmonic contamination and etc [4, 5].

Recently, some considerations have been made to discuss limitations of power system for EVs charging [6, 7, 8, 9, 10, 11, 12, 13] and it can be considered in terms of technical as well as economic concerns where, deterioration of the power system components represent economic issues. There are different power quality parameters to be quantified including, voltage unbalances, harmonic contamination, frequency variations, voltage drop/dip [14] and their indexes are restricted by a number of relevant standards.

Nature of voltage unbalance can be conceptualized as unequal magnitudes or phase angles of voltages in a three phase system (under-voltages or over-voltages) and it can occur in both; an urban residential distribution network, where heavy single phase loads are imposed, and in rural distribution system with fairly long power distribution lines [15, 16]. Presence of negative sequence voltage components leads to large amount of current unbalance of the order of 6–10 times of voltage unbalance percent due to low negative sequence impedance in a power circuit [17]. Consequently, an excessive flow of phase currents may cause circuits of overload-protection to trip and it may also deteriorate cable insulation which results in latter’s reduced lifespan [18]. Some of its common effects include increased losses, extra heating effects, vulnerability of the system to faults because an unbalanced system might not be capable of feeding loads properly [19]. Therefore, it becomes quite important to identify and determine the presence of VU in a circuit in order to deal with it timely for trouble free operation of the power system and the connected loads.

This paper aims at summarizing and determining a power quality index, voltage unbalance in a three phase distribution system, associated with uneven EV charging. Focus of this paper is on an urban residential LV distribution network. The distribution system is based on the CIGRE LV European benchmark configuration. The distribution network is analyzed and tested under uncontrolled charging scheme and tariff based charging strategy with different penetration levels of EVs under two different Scenarios A and B. In the tariff based EV charging strategy an EV is assumed to be recharged during off-peak hours and uncontrolled EV charging is carried out on “whenever and wherever needed” basis. Additionally, a substantial increase in the load on distribution network may certainly cause a need of network reinforcements to bear the EV charging load with minimum power quality problem and thus a suggestion for network reinforcement is also given in the paper. In view of complex charging and discharging characteristics of battery, it is important to design the battery model accurately which could ensure reliable operation of the battery. This paper presents EV charging model implemented in Simulink. The EV charging is controlled via a DC/DC converter employed with constant voltage strategy.

The paper is organized as follows; types of EV charging schemes including uncontrolled EV charging scheme and tariff based charging strategy are described in “Uncontrolled EV Charging” and “Tariff Based EV Charging” section respectively. Suggested network reinforcement for connection of EVs while possibly containing voltage violation is given in “Network Reinforcement for Connecting EVs” section. Explanation of the system under study, urban residential low-voltage distribution network, is given in “System Description” section. EV charging model and corresponding control strategy are explained in “EV Battery Charging Model and its Control”. “Voltage Unbalance and Relevant Standards” contains description of voltage unbalance, its relevant standards and EV penetration scenarios. Simulation results are given in “Simulations” and the paper is concluded with discussion in “Discussion and Conclusion” section.

## Uncontrolled EV Charging

In the uncontrolled charging strategy, EV charging can be freely done without any incentives and penalty for charging and restrictions respectively. In this charging plan, EVs can be connected and charged on the basis of “whenever and whenever needed”. In this charging mode EVs owner assumes electricity tariff to be constant for all day/night. Because, they are not given advantage of economic tariff during valley hours even when the grid operating conditions are flexible for bearing increase in the economic energy consumption. In case of large scale penetration of EVs, an uncontrolled charging strategy is likely to arouse voltage unbalance and other aforementioned power quality issues.

*d*is the distance covered by an EV during a day and

*AER*represents all ranges of EV.

As it is assumed that EV charging can be done at any point any time during 24 h so an EV may be charged at home, work place/offices and public places. Maximum number of EVs that can be charged simultaneously at all the available charging points in the power distribution system can be formulated as:

*h*can be found as given in Eq. (2):

*h*, \(EV_{C_{t(h)}}^{HS}\) is the EV charging at home at hour

*h*, \(EV_{C_{t(h)}}^{WP}\) is the EV charging at work place/commercial center at hour

*h*, \(EV_{C_{t(h)}}^{PP}\) is the EV charging at public place at hour

*h*, and \(EV_{PL}\) is the EV penetration level.

## Tariff Based EV Charging

In this EV charging strategy an EV is assumed to be recharged when grid operating conditions are some favourable, on contrary of uncontrolled charging in which EVs were free to be recharged anywhere, any time. As price of electricity is not fixed all the time, so EV owners can be informed about the instant tariff so that they are attracted to recharge their vehicles during valley hours. However, optimality of this charging strategy depends on EVs driver’s willingness that whether they are attracted by low tariff policy or not and in this way a part of the load of EV charging may be shifted towards optimal operating conditions. An objective of the optimal charging strategy is to minimize likelihood of strain on the power grid by urging the EV drivers to recharge their vehicles during valley hours. In this charging strategy amount of power drawn at hour *h* could be preferably either less than the required total charging power (as compared with uncontrolled EV charging) or equal to that. In this charging strategy high price tariff is considered during peak hours between 13:00 and 20:00 h of a day and low tariff is observed for the rest of time of 24 h [21].

*h*, amount of power required to recharge all ranges of EVs at a residential unit and public points is given in Eqs. (5, 6) and total power drawn from an LV distribution network for charging \(EV_{Nr(max)}\) can be expressed as given in Eq. (7).

## Network Reinforcement for Connecting EVs

## System Description

The sample system under consideration for measuring the content of unbalanced voltage in the LV distribution network is based on low-voltage European distribution systems devised by CIGRE Task Force C6.04.02 [21]. Two scenarios are taken into account with unequal distribution of EVs load on each phase of the 3-phase power system. As per low-voltage European distribution systems, sample systems include an urban residential distribution system. The benchmark LV distribution network represents a real world LV distribution system which is more user friendly and flexible for testing and analysis of distributed energy resources integration. The benchmark system consists of three distinct feeders including residential, commercial and industrial, however, this paper deals with only LV residential feeder.

### Urban Residential Distribution System

*CF*stands for coincidence factor. The coincidence factor is computed using Eq. (10).

Parameters and specifications of the underground cables in the distribution network are as follows; an average mutual impedance measured in \(\varOmega \big /Km\) between nodes R1 and R2, nodes R3 and R11 and nodes R9 and R17 are 0.1855+j0.1445, 0.3343+j0.3898 and 0.1905+j0.7557 respectively and the respective lengths of the line segments are 30, 35 and 30 m.

## EV Battery Charging Model and its Control

## Voltage Unbalance and Relevant Standards

In this paper, voltage unbalance factor (VUF), caused by uneven single phase EV charging, is studied and computed while considering two different EV penetration Scenarios A and B of unequal single-phase EV charging.

**Scenario A**: In this Scenario, load of EV charging on each phase is as follows; 50 % load is on phase “a”, phase “b” bears 30 % load and phase “c” is subjected to 20 % EV charging load.

**Scenario B**: In Scenario, distribution of load of EV charging on each phase is as follows; 80 % load is on phase “a”, phase “b” bears 20 % load and phase “c” has no EV charging load.

It may be noted that in the considered scenarios, it is about to demonstrate possible voltage unbalance problem that may appear due to any highly uneven distribution of EVs load on different phases in the LV distribution networks. Division of EVs charging load, on the load buses in the system, is taken in proportion to the number of households (consumer group) connected on the corresponding node.

Load parameters of the urban distribution system

Node | Number of households | Peak load (kVA) |
---|---|---|

R11 | 9 | 16 |

R15 | 25 | 33 |

R16 | 48 | 68 |

R17 | 09 | 14 |

R18 | 21 | 45 |

### Simulations

The system model is simulated in SimPowerSystems and PSCAD™/EMTDC™. The battery block is taken from the toolbox Library of Matlab. In the urban residential distribution system, presence of load on each load bus is assumed to be in accordance with previously specified loads in Table 1 before addition of EVs load. Effect on the load buses is investigated with addition of EVs load with penetration levels of 40, 50 and 60 % (connecting 24, 30 and 36 EVs respectively), in an uneven manner as per Scenario A.

VUF (%) at different load buses with EV penetration level of 40, 50 and 60 % under Scenario A

Node name | EVs phase | No. of EV PL: 40 % | VUF (%) | No. of EV PL: 50 % | VUF (%) | No. of EV 60 % | VUF (%) |
---|---|---|---|---|---|---|---|

R4 | a | 0 | 0 | 0 | |||

b | 0 | 0.91 | 0 | 0.95 | 0 | 0.96 | |

c | 0 | 0 | 0 | ||||

a | 1 | 1 | 1 | ||||

R11 | b | 1 | 1.24 | 1 | 1.45 | 1 | 1.51 |

c | 0 | 0 | 0 | ||||

a | 3 | 4 | 4 | ||||

R15 | b | 1 | 1.90 | 2 | 2.15 | 3 | 2.31 |

c | 0 | 1 | 1 | ||||

a | 6 | 7 | 8 | ||||

R16 | b | 3 | 1.61 | 4 | 2.05 | 4 | 2.20 |

c | 1 | 1 | 1 | ||||

a | 1 | 1 | 2 | ||||

R17 | b | 0 | 1.80 | 1 | 2.25 | 1 | 2.30 |

c | 0 | 0 | 1 | ||||

a | 4 | 5 | 6 | ||||

R18 | b | 2 | 1.86 | 2 | 2.31 | 2 | 2.54 |

c | 1 | 1 | 1 |

The number of households in the urban network is 112. As per assumed EV penetration level, according to which there would be 27 EVs in the urban area. Addition of EV charging load on each node is kept proportional to the previously connected load (before connection of EVs) and additional load. In fact, when the voltage decreases it causes load current to go higher and an then more voltage falls down further. Thus, it may result in excessive voltage drop and may limit the functionality of other sensitive loads. Additionally, rise in power consumption for a period of 24 h is illustrated in Fig. 8 for 50 and 60 % EV penetration level. It is observed that with 60 % EVs in the system, there is nearly 109 % increase in power consumption, as it changes from 23 to 49 kW. In view of obtained results, it could be noted that the network experiences a significant raise in peak load and it most likely to lead to excessive voltage drop and then voltage unbalance in the system.

VUF (%) at different load buses with EV penetration level of 15, 25 and 30 % under Scenario B

Node name | EVs phase | No. of EV PL: 15 % | VUF (%) | No. of EV PL: 25 % | VUF (%) | No. of EV PL: 60 % | VUF (%) |
---|---|---|---|---|---|---|---|

R7 | a | 0 | 0 | 0 | |||

b | 0 | 0.90 | 0 | 0.97 | 0 | 0.98 | |

c | 0 | 0 | 0 | ||||

a | 1 | 2 | 3 | ||||

R11 | b | 0 | 1.20 | 1 | 1.45 | 0 | 1.51 |

c | 0 | 0 | 0 | ||||

a | 3 | 3 | 5 | ||||

R15 | b | 0 | 1.60 | 0 | 2.30 | 1 | 2.50 |

c | 0 | 0 | 0 | ||||

a | 2 | 5 | 2 | ||||

R16 | b | 1 | 1.78 | 1 | 2.21 | 1 | 2.35 |

c | 0 | 0 | 0 | ||||

a | 1 | 2 | 3 | ||||

R17 | b | 1 | 1.95 | 1 | 2.35 | 1 | 2.30 |

c | 0 | 0 | 0 | ||||

a | 0 | 1 | 2 | ||||

R18 | b | 0 | 1.98 | 0 | 2.25 | 1 | 2.40 |

c | 0 | 0 | 0 |

It can always be observed that an uncontrolled EV charging is more likely to pose serious negative impact on the load buses rather a tariff based charging strategy could be of low detriment for the system. With the tariff based charging strategy, strain on the distribution system could be avoided to a limited extent, provided that off-peak hours are observed preferably in day-time or and within daily load diagram and EV drivers are attracted (by low tariff) and willing to recharge their EVs during valley hours. However, it should also be noted that an instantaneous increase in the number of EVs charging during the valley hours might also cause the system to overload, leading to provocation of technical issues in the distribution network.

The presented results shown in Figs. 11 and 12 show that employing tariff based charging helps contain the voltage unbalance factor within the standard allowed limits as the VUF is reduced to 2 % at the load nodes (NL) R16 and R17 under Scenario A and at R11, R15 and R17 in case of Scenario B.

## Discussion and Conclusion

In the first step, the distribution network is analyzed and tested under uncontrolled charging scheme with different penetration levels of EVs. It is detected that voltage unbalance content does not violate its limits till 50 % penetration level of EVs in the urban distribution system as per Scenario A. Then, the percentage of EV integration is increased by 10 % until the problem was detected. An assumption about critical mass of EVs is expected to increase until the distribution system continues to support it without exhibiting any technical violation. To prove it, another unbalanced scenario with higher number of EVs has been investigated. According to Scenario B, a technical violation is sought (voltage unbalance factor) beyond the limits when percentage of EVs of the total transportation system is only 25 %. It is noteworthy, that as no EV load in connected to load buses R4 and R7 so amount of voltage unbalance on them is within quite normal range, below 0.98 %. Considering two different charging strategies demonstrate that the tariff based charging strategy could be of low detriment for the system. The presented results show that, employing tariff based charging helps contain the voltage unbalance factor within the standard allowed limits. Additionally, it is found that the suggested technique for reinforcement of network for connection of EVs that is based on raised voltage level at certain segments of lines with insertion of appropriate transformers can help contain voltage violation to an extent and that is cost effective too as compared to traditional reinforcement strategies. It is important to consider that there may be a condition when the power distribution network is no longer able to support further EV charging load because of system parameters’ violation in the operation of network.

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