International Transactions on Electrical Energy Systems - 2021 - Hamza - Impact and assessment of the overvoltage.pdf

R E V I E W A R T I C L E
Impact and assessment of the overvoltage mitigation
methods in low-voltage distribution networks with
excessive penetration of PV systems: A review
Ebtsam A. Hamza | Bishoy E. Sedhom | Ebrahim A. Badran
Faculty of Engineering, Electrical
Engineering Department, Mansoura
University, Mansoura, Egypt
Correspondence
Bishoy E. Sedhom, Faculty of
Engineering, Electrical Engineering
Department, Mansoura University,
Mansoura 35516, Egypt.
Email: eng_bishoy90@mans.edu.eg
Handling Editor: Prof. Yao, Rui
Summary
This paper presents an overview of the impact of high penetration of photovoltaic
(PV) systems in low-voltage distribution networks (LVDNs). High integration of
solar PVs in the LVDNs has severe implications on the system parameters, effi-
ciency, and stability. This paper also introduces the methods that have been
driven to overcome these effects to preserve the steady-state conditions in the sys-
tem during excessive penetration of PV generation units. A comparison between
the contributions and shortcomings of the most recent researches for overvoltage
mitigation strategies has been driven. Also, it includes comparing different over-
voltage mitigation methods to handle the impact of the overvoltage under high
penetration of PV units in the LVDNs. Besides, it presents a comparison between
overvoltage mitigation methods based on their pros and cons.
K E Y W O R D S
high penetration of PV systems, impact of high penetration of PV, low voltage distribution
network, overvoltage mitigation
1 | INTRODUCTION
The need for renewable energy resources (RERs) becomes popular, especially the integration of distributed generators
(DGs) such as PV generation units (PVGUs), wind turbines (WTS), and hydraulic energy (HG) due to the
nonsustainable fossil fuel resources, harmful emissions, concurrent pollution,1
and the high loss across transmission
lines.2
The low-voltage distribution networks (LVDNs) topology included renewable power plants, MV/LV trans-
formers, and PV inverters.3
Also, renewable power plants can be mixed solar-PVs and wind turbines to advance system
reliability and achieve consumption mode during peak hours.4
The most integrated DGs are rooftop photovoltaic (PVs)
that are more concerned issue.5
Although solar PVs are considered as cleaning energy, the integration faces problems
as output energy from these power plants depends on weather conditions changing (sun irradiance)6
; also, the excessive
penetration of PVGUs has its negative sides on LVDNs behavior.2
Distribution systems may be considered as a bidirectional system due to the reversing power flow from the excessive
connection of PVs,7
which led to an overvoltage challenge that occurred at the point of common coupling (PCC).8
Also,
the solar irradiance may cause overloading at the components of distribution systems9
; this may lead to an imbalance
system between generation and loads sides in LVDNs and voltage unbalance (VU). Hence, the most study share is over-
voltage and VU.10
Overvoltage is related to the performance of the LVDNs.11
It has different impacts on the overall sys-
tem aspects such as; stability and efficiency,12
power quality,13
frequency oscillation,3
and accordingly the system
inertia.14
Other researchers present the mitigation strategy for the overvoltage challenge.9
These strategies can be
Received: 2 July 2021 Revised: 20 September 2021 Accepted: 3 October 2021
DOI: 10.1002/2050-7038.13161
Int Trans Electr Energ Syst. 2021;31:e13161. wileyonlinelibrary.com/journal/etep © 2021 John Wiley & Sons Ltd. 1 of 31
https://doi.org/10.1002/2050-7038.13161

classified as traditional methods and optimization-based methods to enhance system performance during the excessive
penetration of PVGUs.15
Due to the high penetration of the RERs in the LVDNs, the control and energy management of the system is not
straightforward. There are different control and management techniques have been applied to obtain an optimal opera-
tion condition in presence of the RERs. The demand-side management based on two-level particle swarm optimization
(PSO) based method for optimal operation of the system load appliances has been represented in Reference 16. Also,
consensus algorithm-based coalition game theory has been performed for an optimal demand management scheme in
Reference 17. While in Reference18, a new supervisor fuzzy nonlinear sliding mode control method has been used for
energy management with the high penetration of RERs. On the other hand, the frequency control method based on dif-
ferent meta-heuristics algorithms has been investigated in presence of the system nonlinearities in Reference 19. Also,
in Reference 20 a control method based on multiagent systems (MASs) has been introduced for optimal control method
on the internet of energy paradigm. In Reference 21, the system voltage and frequency have been regulated while
improving the system power quality based on a multistage H-infinity controller. Also, in Reference 22, load frequency
control based on the model predictive control (MPC) method has been applied for a nonlinear multiarea power system.
In Reference 23, the harmony search-based H-infinity control method is investigated to adjust the system voltage and
frequency in presence of high penetration of RERs. While in Reference 24, the MPC control method has been applied
to regulate the system frequency and voltage in presence of the integration of wave energy.
Excessive penetration of the PVGUs may influence the performance of the LVDNs, whether at the generation side
or load side.25
These impacts can affect the power quality, voltage profile, system inertia, frequency oscillation, imbal-
anced system, and system reliability.26
There are different strategies used to overcome these effects and to detect the
negative impacts, including reconfiguration enhancement,27
the Flexible AC Transmission System (FACTS)
integration,28
energy storage installation,29
output active power support,30
on-load tap changer implementation,31
or by
coordination both strategies to improve the system efficiency during the operation. At the same time, the most used
overvoltage mitigation techniques are the control approach, whether centralized or distributed structure.9
Also, the
optimization methods that achieve better system reliability are used and applied to improve the system efficiency.32
On
the other hand, there are papers review on the FACTs installation,19
moreover, some cases based on suggesting hybrid
methods as the main strategy with the main technique of using energy storage system,29
also brief comprehensive
review presents the impacts of PVGUs with highly host capacity of PVs and the mitigation methods.25
Also, a brief
study focuses on the economic sides while installation regulation or compensation devices.33
This paper focuses on the impacts of the excessive penetration of PVGUs and reviews the overvoltage mitigation strate-
gies. A comparison between contributions and shortcomings of most recent researches concerning the overvoltage mitiga-
tion strategies is performed. The comparison between the overvoltage mitigation methods concerning the overvoltage in the
LVDNs and the comparison between overvoltage mitigation methods based on their pros and cons are also implemented.
The contributions of the paper can be summarized as follows:
1. Introducing the impacts of the excessive penetration of PV systems in LVDNs.
2. Representing the various methods for overvoltage mitigation in the LVDNs.
3. Investigating the most recent researches that apply the overvoltage mitigation methods in LVDNs.
4. Performing a comparison between the different overvoltage mitigation methods based on pros and cons.
5. Performing a comparison among the overvoltage mitigation methods concerning the impact of the excessive pene-
tration of PV units in LVDNs.
6. Representing the most recent new trends in the overvoltage mitigation methods for high penetration of PV units in LVDNs.
The rest of the paper can be summarized as follows: Section 2 presents the impact of excessive penetration of PV system
in LVDNs, Section 3 indicates the overvoltage mitigation methods in LVDNs with high penetration of PV systems, Sec-
tion 4 discusses the comparison between the overvoltage mitigation methods, and Section 5 predicts the new trends for
overvoltage mitigation in LVDNs.
2 | IMPACT OF EXCESSIVE PENETRATION OF PV SYSTEMS IN LVDNS
The high penetration of the PV systems in the LVDNs can be shown in Figure 1. There are many effects of the extensive
integration of PV systems in LVDNs. These impacts have been presented in the following sections.
2 of 31 HAMZA ET AL.

2.1 | Frequency oscillation
The PVGUs have significant effects that influence the features of the power system. It can be integrated into the utility grid
to supply the connected load demand in system faults. The high integration of the PVGUs to the utility can affect the sys-
tem frequency and active power. The system frequency has oscillated with the increase in the active power output from the
PVGUs.3
According to the matching between the output power from the PVGUs and the connected system load.
In the literature, authors in Reference 34 applied FACTS controller such as Static Synchronous Compensator
(STATCOM) to damp the frequency oscillations. Authors in Reference 35 proposed a tracking method of using an
unscented-Kalman filter (UKF) based on a decentralized dynamic estimation of the generator frequency for regulating
frequency oscillation and enhancing the power deviation due to solar power variety irradiance. In Reference 36, the
authors presented the automatic generation control (AGC) method for improving system stability and increasing system
efficiency. In Reference 37, the authors proposed an advanced form of (p-f) droop control to regulate the frequency
deviation that results from the integration of PVGUs. Figure 2 describes the strategy to enhance the system frequency
oscillations.3
2.2 | Rotor angle (RA) stability
Oscillatory instability of the RA is associated with low frequencies because of the lack of damping torque.38
The RA
instability can be divided into two types: local and global RA instability. The first is local RA instability (local plant
mode) related to the oscillations at the generators RA against the rest of the system. The second is global RA instability
associated with the interaction of the generator's parts that leads to system blackout.3
Authors in Reference 39 proposed multiple-model adaptive control (MMAC) based probability calculations for system
oscillatory improvement to deal with the sudden changes in system operation due to integrating the PVGUs into LVDNs.
While authors in Reference 40 presented a proposed controller based on STATCOM for the PVGUs called PV-STATCOM
to provide fast frequency response and ensure damping in power oscillation to enhance system stability. Authors in
FIGURE 1 Schematic diagram of the high penetration of PV systems in LVDNs
HAMZA ET AL. 3 of 31

Reference 41 improved the system stability by integrating the DGs in the LVDNs based on an adaptive Jacobian matrix to
solve the differential equations of the connected DGs to support active power and eliminate disturbance. In Reference 42, a
novel frequency regulation method is introduced based on the droop control and virtual inertia control to improve the sys-
tem stability, enhance the frequency response, and obtain convenient accuracy and tracking speed.
2.3 | Power flow
Due to the excessive penetration of the PVGUs in the system, the power balancing is affected due to the mismatching
between the connected units and the system load demand.3
The high integration of the PVGUs in the system leads to
reverse power flow (RPF) at transmission lines in the grid.43
In the literature, authors in Reference 10 proposed a strategy based on active power curtailment (APC) using a
droop controller to limit the output power of the PVGUs with considering a reduction in the system power loss. In Ref-
erence 44, the authors applied an energy storage system (ESS) to regulate the mismatching between the connected load
demand and the output power generated from the PVGUs. Also, authors in Reference 45 presented an enhanced con-
trol method based on a centralized master salve controller for power flow control in single line converters in the distri-
bution system while improving the system power quality and regulating the PCC voltage across. However, authors in
Reference 46 presented a predictive based on the APC method to reduce the system power loss by considering the high
penetration of PVGUs in the LVDNs. In Reference 7, the authors investigated the scenarios of RPF occurrence in the
system based on a voltage variation analysis, fault analysis, and reverse power fluxes analysis at the integration of
PVGUs into the utility grid. Figure 3 shows the steps to detect the reverse power flow.
2.4 | Power quality
The integration of excessive PVGUs with the LVDNs through power electronic devices (PEDs) influences the system
voltage profile. Hence, the system power quality is affected due to the harmonics produced from the PEDs and voltage
variation.3
The PVGUs are connected to the LVDNs through inverters based on PEDs.13
These inverters can inject the
grid with the required power to ensure the satisfaction of the system-connected load. However, using PEDs in the
LVDNs has many effects: voltage increase at the system and ancillary services, harmonic distortion to the voltage and
current profile, and resonance existence due to the connected capacitances and inductances.8
Also, PEDs affect the sys-
tem with the circulating current due to the magnetic components' saturation, increasing the temperature, and produc-
ing pulsating torque that leads to transformer reactive power loss.47
Authors in Reference 8 proposed a reactive power control (RPC) technique based on a consensus algorithm to deter-
mine the compensated reactive power required to regulate the system voltage. In Reference 47, authors investigated
modular multilevel converter (MMC) behavior under the unbalance condition in the PVGUs and unbalanced system
FIGURE 2 Strategy to enhance the system frequency oscillations3
FIGURE 3 Steps to detect the reverse power flow

conditions while ensuring that the circulating current and voltage ripples are within their limited values. In Reference
48, the authors presented a method based on dual voltage source inverters (DVSI) to enhance system reliability and
improve system power quality. Authors in Reference 49 described a new controlling method based on virtual imped-
ance (VI) to limit harmonics at PCC due to the integration of PEDs. Authors in Reference 50 proposed a technique to
eliminate the second-order harmonic component of the AC current using a high-frequency transformer and also miti-
gate the negative sequence harmonic component using a low pass filter (LPF).
2.5 | Voltage profile and reactive power
The most crucial challenge that results from the integration of excessive PVGUs with the LVDNs is the voltage varia-
tion.11
Overvoltage (OV) phenomena of voltage fluctuation occurred at PCC due to the integration of PVGUs to the util-
ity grid when the output power from the PVGUs exceeds the system load demand.51
In the literature, authors in Reference 52 proposed an automated control method to mitigate the overvoltage of inte-
grating the PVGUs in the LVDNs. Authors in Reference 53 investigated different strategies based on RPC to limit volt-
age rise at PCC, reduce power losses, and improve system stability. While in Reference 54, the authors presented an
optimal reactive power control to limit voltage violation due to the high existing of PVGUs and to reduce the depen-
dency of using the regulation devices such as on-load tap changer for a long operation life. The applied strategy is based
on forecasting the income of PVs and supporting the feeder's voltage by the maximum power point tracking (MPPT)
controller. In Reference 55, the authors presented an adaptive RPC method based on a droop controller to regulate volt-
age profile and enhance the power transfer of a weak grid. In Reference 56, the microgenerators are considered as smart
agents to measure their certain voltage value and share the value with other agents as a cyber layer into feedback,
hence the injected reactive power was maintained to minimize power loss and to regulate the system voltage. Authors
in Reference 57, proposed a control strategy based on the coordination between the active and reactive power control-
lers to mitigate the overvoltage at the PCC with high integration of PVGUs in the LVDNs. In Reference 58, authors pro-
posed a method to minimize the voltage fluctuation and improve the system efficiency based on coordination between
using an on-load tap changer (OLTC) and the inverter regulation method. Authors in Reference 59 applied a Volt/Var
control method with conservation voltage reduction and Var management for enhancing the system power loss and
reduce the voltage violation with the high penetration of the PVGUs in the LVDNs. Figure 4 represents the reactive
power control diagram.
2.6 | System reliability
Due to the integration of extra PVGUs in the LVDNs, the system reliability must be satisfied to ensure the system's sta-
ble operation. The system load requirements must be supplied to ensure system reliability.3
Authors in Reference 60 indicated that an optimal location for PVGUs, ESS, and demand response (DR) in the
LVDNs by using a mixed-integer second-order cone programming model to reduce the energy cost and enhance the sys-
tem reliability. Also, in Reference 61, the authors proposed a modified strategy for inverters based on loss balance pulse
width modulation (LBPWM) to improve system reliability. Authors in Reference 62 proposed a control method to
FIGURE 4 Reactive power control diagram

obtain the maximum power output from the PVGUs considering partially shading conditions and ensure system reli-
ability. While in Reference 63, the authors proposed a control strategy based on droop control and distributed control to
obtain an optimal charging and discharging condition for the ESS considering maximum output power from the PVGUs
and peak load demand.
2.7 | System inertia
The mismatching between the system load demand and the output power from the connected sources results in a devia-
tion in system frequency. The violation in system frequency depends on the size of the disturbance that occurs, system
inertia, the response of the frequency controller.64
The system inertia is affected by integrating nonsynchronous genera-
tors such as PV units and wind turbines due to the connected electronic devices as converters. The system with high
shares of the PVs can reduce system inertia, affect the voltage unbalance, increase the rate of change of frequency, and
disturbances in active power.14
The system inertia enables the system to withstand the disturbances, and hence it pre-
vents the entire system from any sudden changes that may affect the system stability.65
In the literature, authors in Reference 65 proposed a controlled strategy based on virtual inertia control for DC/DC
and DC/AC converters. Also, the system stability analysis was performed depending on the analysis of the eigenvalues.
Authors in Reference 66 presented a power-based double synchronous controller (DSC) to ensure the system's stable
operation with the high penetration of PVGUs in LVDNs, enhancing the system inertia and obtaining the proper active
and reactive power-sharing. While authors in Reference 67 presented a stochastic fractal optimizer (SFO) to control sys-
tem frequency under high penetration of PVGUs, a coordination control between the system inertia and the energy
storage system is presented. In Reference 68, authors proposed a proactive reserve technique that depends on probabi-
listic error modeling for enhancing the oscillatory dynamics of system inertia with high integration of the PVGUs.
Authors in Reference 69 introduced a planning strategy for the energy storage system to improve the rate of frequency
change and hence support the system inertia.
2.8 | Unbalance of LVDNs
Randomly system load connection and high integration of the PVGUs may lead to unbalance in the entire system.
Hence, many negative impacts may be accomplished, such as increasing system power loss, affecting voltage stabil-
ity, and reducing system efficiency.12
Also, with the excessive penetration of PVGUs, the power flow was reversed
and resulted in system unbalance. Hence, it could lead to an unbalance current and short lifetime of the existing
source.70
In the literature, authors in Reference 71 presented a joint optimization method based on a static reactive power
compensator connected in Y and Δ to mitigate the system unbalance and improve the power loss in the LVDNs. In
Reference 72, the authors proposed modified coordination between centralized and distributed methods based on
supporting the inverter's reactive power to limit the system unbalance and improve the system voltage regulation
with the high penetration of PVGUs in the LVDNs. Authors in Reference 73 presented an advanced strategy based
on decoupling a double synchronous reference frame (DDSRF) to compensate for the unbalanced voltage in the
islanded microgrid. Meanwhile, in Reference 74, the authors proposed a demand response-based technique to miti-
gate the voltage unbalance, minimize the loss in the network, and reduce the demand response cost with a high
penetration level of PVGUs. In Reference 75, the authors represented an online voltage control algorithm formed as
a convex quadratic programming problem to overcome the unbalance in the multiphase LVDNs with the high
shares of the PVGUs.
2.9 | Protective devices (PDs)
The integration of PVGUs into LVDNs may result in misoperation in the protective devices (PDs) because of the revers-
ing power flow. The integration of these sources causes an overcurrent and reversing power flow, and hence, the PDs
must be able to discriminate between the normal and abnormal conditions.76
The main impact of the high penetration
of PVGUs in the LVDNs is the delayed operation of the overcurrent relay due to the undetected fault current because of

the presence of the PEDs with the PVGUs that limit the fault current to twice the rated current.77
Also, the recloser
operation is affected by the PVGUs as the PVGUs must be disconnected before the recloser.77
Losing the protection
coordination of the PVGUs may results in mal-operation and blinding of the PDs as the PDs may become blind when
the relay sensitivity is reduced.78
Authors in Reference 79 proposed a coordination technique based on a genetic algorithm (GA) for directional
overcurrent (DOC) protection. In Reference 80, the authors presented a protection method based on local measure-
ment of the current signal, voltage signal, and the real and reactive power for accurate relay decisions to enhance
the system's reliability. While in Reference 81, the authors proposed an advanced protection method based on
monitoring the system topology to detect any changes in the system configuration. Hence, the setting of the DOC
relay is adjusted using a micro-genetic algorithm. In Reference 82, authors proposed a fast detection and identifica-
tion scheme for the encountered system faults based on multiagent overcurrent protection in case of high penetra-
tion of PVGUs in the LVDNs.
2.10 | System flexibility
System flexibility is defined as the ability of the system to overcome any variation in the system load and the connected
DGs. The system flexibility must ensure system security and the balancing between the generation and demand.83
The
system flexibility is necessary to enhance the safe operation of the system in the presence of PVGUs uncertainties. Also,
it can eliminate the negative impacts of the high penetration of PVGUs in LVDNs.84
Many technologies can enhance
system flexibility, such as flexible generators, demand response, energy storage system, network reconfiguration, and
optimal, efficient system operations.85
In Reference 86, authors proposed a flexibility metric that can estimate the considerable variation of the uncer-
tainties related to the high penetration of PVGUs in the LVDNs. Authors in Reference 87 presented a flexible frame-
work to enhance the operation issues, improve the power imbalance, and regulate the voltage deviation with the
integration of PVGUs in the LVDNs. At the same time, authors in Reference 88 proposed an advanced method for
enhancing the system flexibility with the high integration of the PVGUs in the utility grid based on optimizing the net-
work configuration design and strengthening the system operation strategy using fuzzy logic control. Authors in Refer-
ence 89 represented an enhancement for the generation flexibility based on market flexible ramp products (FRPs) to
overcome the system unbalance in the presence of system uncertainties associated with the high integration of the
PVGUs in the utility grid.
2.11 | Power loss
The amount of power loss indicates the efficient operation of the LVDNs and ensuring the proper power delivery from
the generating units to the customers. The power loss must not exceed a specific limit as it affects the system planning
and operation strategies.90
Also, the high integration of PVGUs in the system may influence the system performance
and increase power losses. The power losses are affected by the positioning and the sizing of the PVGUs installed in the
LVDNs,90
while loss sensitivity could be implemented as follows:
Pikloss ¼
ðPk
2
þ Qk
2

Rik
Vk
2 ð1Þ
Ploss ¼
X
n
k¼1
Rk Ik
2
ð2Þ
Ik ¼
Vi Vj
Rk þJXk
ð3Þ
where Pikloss is the loss along a line between nodes i and k, Ik is the current across the line, Vi and Vj are the voltage
across i, j and k is the node between these nodes, Rk, Xk are the resistance and reactance of kth line.

In the literature, authors in Reference 91 represented a nonsorted genetic algorithm (NSGA) for a smart inverter of
the PVGUs to reduce the power loss, minimize imported power from the grid, and reduce the voltage deviation.
Authors in Reference 92 proposed a gradient-based Volt/Var optimization method for smart inverters to minimize the
power loss with the high penetration of PVGUs in the LVDNs. While authors in Reference 93 introduced an advanced
strategy for loss reduction in the LVDNs in PVGUs based on optimal allocation and sizing of the battery energy storage
units. This method can also reduce the total error in the LVDNs. In Reference 94, the authors presented a strategy to
allocate the optimal location for renewable power plants based on fuzzy logic to reduce power loss and increase system
reliability.
2.12 | Voltage regulation
The integration of PVGUs in LVDNs is limited due to the voltage regulation issue. The voltage regulation is affected
due to the bidirectional power flow resulting from the integration of the PVGUs in the grid.95
Also, the system with
high shares of the PVGUs may result in voltage rise challenges that affect the system balancing,96,97
while the voltage
across PCC could be implemented by the following equation:
Vpcc ¼ Vgrid þI Z ð4Þ
ΔV Vpcc ¼ P RþQX ð5Þ
Pmax ¼
ΔVmax Vpcc QX
R
ð6Þ
where Pmax maximum active power that can be injected into the grid accordingly the increase in voltage ΔVmax, Vpcc
the voltage across PCC, Z equivalent impedance, and Vgrid grid voltage.
In the literature, authors in Reference 98 proposed a robust model predictive control method for enhancing the
system voltage regulation with excessive penetration of PVGUs in the utility grid. The improvement of the voltage
regulation was based on optimal coordination between the reactive power output from the RESs, BESS, and the
on-load tap changers. Authors in Reference 99 represented a generalized bender decomposition (GBD) algorithm
for optimal scheduling the voltage regulators and the PVGUs over a time horizon window. In Reference 100,
authors introduced coordination between the voltage regulators and the inverter controller to enhance the system
voltage regulation with the increased integration of the PVGUs in the LVDNs. While authors in Reference 101 pro-
posed a virtual complex impedance-based P-V droop controller for enhancing the active and reactive power shar-
ing, eliminating the impact of line impedance mismatches, and restoring the system voltage after any violations in
the operating conditions.
2.13 | Islanding detection
Islanding occurs when a portion of an electrical power system becomes isolated from the utility grid still feeding with
the connected PVGUs to supply the system loads.102
The islanding may occur due to scheduled maintenance, load shed-
ding, or unpredicted conditions such as tripping and failure of system devices.103
Islanding detection methods can be
classified as passive, active, and hybrid methods.
In literature, authors in Reference 102 proposed an anti-islanding detection method based on modified Sandia fre-
quency shift (SFS) to protect the connected PVGUs after being isolated from the utility grid. In Reference 104, the
authors introduced a passive islanding detection method based on the total variation filtering (TVF) approach to tackle
the islanding problem in the presence of PVGUs connected to the utility grid. In Reference 105, authors represented a
passive islanding detection method that depends on an improved adaptive boosting algorithm to overcome the nonde-
tection zone (NDZ) and enhance the system power quality in the LVDNs with the high shares of PVGUs. Authors in
Reference 106 proposed an islanding detection method using the discrimination of the voltage profile based on periodic
maxima of superimposed voltage components to ensure an appropriate system balancing in the presence of PVGUs con-
nected to the LVDNs. Figure 5 shows the islanding detection methods.103

3 | OVERVOLTAGE MITIGATION METHODS IN LVDNS WITH HIGH
PENETRATION OF PV SYSTEMS
Overvoltage is one of the main challenges that occurred while integrating the high penetration of PVs due to reversing
the power flow path from load feeders to the transformer. Hence, the following methods prevent this challenge and
limit unbalance network and tripping within the connection of PVs or DG with a low voltage distribution system. Volt-
age rise is considered one of the major concerns that need methods to overcome, especially within high PV penetration.
Figure 6 shows the overvoltage mitigation strategies.
3.1 | Energy storage systems
Distributed energy storage systems (ESSs) were applied to be a reliable-connected source in distribution systems such
as batteries to store excess energy during the integration of high penetration of PVs and low load levels.107
Also, the
integration of ESSs keeps the distribution system more effective and reliable due to the power loss reduction and
achieving the load management by the capacity of ESSs.108
The energy storage types are battery energy storage, thermal
(heat) energy storage, thermochemical energy storage, kinetic energy storage, compressed air energy storage, pumped
FIGURE 6 Various types of overvoltage mitigation strategies
FIGURE 5 Islanding detection methods103

energy storage, magnetic energy storage, chemical and hydrogen energy storage.109
ESSs are economic techniques as
they are reliable sources to supply loads sides, store the surplus energy in backup sources, and have the ability to
smooth output energy.110
Figure 7 shows the schematic diagram of the ESSs connected to the PV system.111
Table 1 pre-
sents the contributions and the shortcomings of the most recent researches using the ESSs method.
3.2 | Load side management
Load side management (LSM) could be defined as a load controller done by the distribution network operator (DNO)
to support power flow and adjust power consumption from peak to off-peak. The strategy was based on collecting and
analyzing the whole data by the DNO to adjust power flow from and to the end-users. Also, LSM could be coordinated
with electrical ESSs to prevent voltage rise at PCC during the excessive penetration of PVs.26
The main advantages of
this strategy are making the load side more flexible to limit voltage-rise, reducing electricity bills, and a cost-effective
technique with low-penetration of PVs.17
On the other hand, the disadvantage of this method is that the LSM could
control and reshape the load side that made it unreliable.2
Figure 8 represents the flowchart of the energy schedule
check. Table 2 presents the contributions and the shortcomings of the most recent researches using the LSM method.121
3.3 | Reactive power support (RPS)
Reactive power support (RPS) would be defined as a strategy to control the amount of reactive power by PV inverters.
The control approach could be centralized and decentralized utilizing the droop control strategy. The RPS can be
divided into reactive power management (RPM) and RPC. The RPM is based on; the power factor as a function of
injected/absorbing active power and reactive power as a function of the voltage across PCC.2
While RPC used the PV
inverters' capability to limit reactive power, it is not a practical solution for mitigating voltage rise due to the high R/X
ratio feeders and required high costs in the existing high inverters size. On the other hand, adjusting reactive power
could be applied by using custom devices as distributed static synchronous compensator (D-STATCOM) and dynamic
voltage restorers as devices that are not related to active power.26
Table 3 presents the contributions and the shortcom-
ings of the most recent research using the RPS method.
Local reactive power control would be determined by obtaining the reactive power output accordingly to node volt-
age, while
Qinv ¼
Qmax, Vi V1
K Qmax, V1 ≤ Vi ≤ V4
Qmax, V4 Vi
8

:
ð7Þ
where Qinv is reactive power outputted from the inverter, Qmax is the maximum amount of reactive power from PV-
inverter, Vi represented node voltage, V1 and V4 are a limited range of voltage values across nodes, and K is the control
index.
FIGURE 7 ESSs connected to PV system111

TABLE 1 Contributions vs shortcomings of the most recent research using the ESSs method
Reference Contributions Shortcomings
110 Integrating an ESSs with PV system by asserting an indicator to evaluate
economic self-consumption of a hybrid system used.
• Excessive PV penetration is not
considered.
• System voltage is not regulated to its
nominal value.
• Stability analysis is not considered.
• Power quality improvement is not
considered.
111 Using ESSs to manage energy, while the used optimizations were single
criterion and multicriterion to handle the economic and technical
aspects to improve system efficiency.
• Regulating the system voltage is not
studied.
• Adjusting the system frequency does not
take into consideration.
• Stability analysis is not performed.
• The imbalance challenge is still occurred
due to the excessive penetration of PVs.
112 Presenting a local voltage control method based on adding a voltage
control capability of self-consuming through voltage-based battery
charging, reactive power control, and PV curtailed power.
• Minimizing power loss is not considered.
• Islanding detection is not concerned.
• Enhancing system balance does not take
into consideration.
• Adjusting system frequency is not
achieved.
113 Installing battery electric vehicles to limit voltage violation by applying a
Monte Carlo technique.
• Improving system stability is not
considered.
• Improving system quality is not
considered.
• Minimizing power loss does not take into
consideration.
114 Proposing a coordinated control approach for distributed ESSs to adjust
system voltage and regulate the ESSs state of charge in the LVDNs.
• Reducing frequency deviation is not
considered.
• Islanding detection does not take into
consideration.
• Achieving system balance is not
concerned.
115 Introducing a technique for optimal configuration of the ESSs and cyber
systems in the LVDNs with high penetration of the PV systems while
reducing the investment costs and improving system reliability.
• Islanding detection is not considered.
• Improving system frequency is not
considered.
116 Proposing a multipurpose controlling and planning method to modify the
state of charge, mitigate reversing power flow, peak shaving, and
coordinate with the installation between the OLTC and voltage
regulator to apply a suitable battery.
• Adjusting system frequency to its
nominal range does not take into
consideration.
• Islanding detection is not studied during
the operation of PVs.
• Achieving balance is still not studied.
117 Installing the battery systems to have the ability to store excess energy
during low loads, also controlling that based on model predictive
control for the state of charge to avoid battery capacity.
• Regulating system frequency is not
considered.
• Improving system stability is not studied.
• Handling the imbalance challenge is not
considered.
• Improving power quality is not studied.
118 Presenting the coordination of batteries energy storage systems to mitigate
the challenge of overvoltage, applying voltage sensitivity to get a long
lifetime for the used batteries, and evaluating the rate of change.
• Improving the system stability is not
considered.
(Continues)

3.4 | Active power curtailment (APC)
Active power curtailment (APC) is a specific solution for PV inverters to deal with a negative impact of voltage fluctua-
tion that resulted from power intermittency. This strategy is related to control the real output power by using the
volt-watt curve. This control approach reduces the signal error between voltage value at maximum power point (MPP)
and actual voltage by the existing PI controller. This is made by evaluating actual terminal voltage across inverters to
curtail output active power for regulating the system voltage.135
The flowchart of applying the APC method is
TABLE 1 (Continued)
considered.
119 Implementing the coordination of electric vehicles (EVs) as a stage for
node voltage regulation, also obtaining the optimal charging of EVs by
alternating direction method of multipliers in a decentralized approach.
• Adjusting system frequency to its
nominal value is not studied.
performed.
• System stability is not analyzed.
• Improving the system balance is not
studied.
consideration.
120 Performing a gradient projection strategy relied on a decentralized
controlling approach for charging control EVs, while the applied
solution was for supplying the feeder lines with the required energy.
• Maintaining the voltage value to its
nominal range is not the main
contribution.
• Adjusting the system frequency is not
studied.
• Enhancing the system balance is not
considered.
• Power quality enhancement is not
considered.
FIGURE 8 Flowchart of the energy schedule check121

TABLE 2 Contributions vs shortcomings of the most recent researches using the LSM method
2 Applying the thermal storage unit as a controlling method to balance PV units
and end-users' sides prevents voltage rise and reverse power flow.
• Excessive penetration of PVs is not
studied.
• System voltage is not adjusted to
its acceptable range.
• Regulating the system frequency is
not investigated.
• Mitigating the system unbalance is
not studied.
• Improving the system stability is
not performed.
• Islanding detection is not
considered.
121 Proposing a schedule strategy between generation and load sides as a
coordinated-effective strategy to manage energy and reduce electricity costs.
This coordinated method was based on dispatching power concerning the cost
reduction and evaluating an iterative-optimal process to restore power to
acceptable limits.
• Adjusting voltage profile to its
• Regulating the system frequency is
not considered.
122 Proposing an optimal reactive power control that depends on active power
characteristics, while the system parameters are optimally obtained based on
historical smart meter data.
• Improving system frequency does
not take into consideration.
considered.
• Improving system reliability is not
achieved.
123 Proposing an optimization algorithm for the integration of the ESSs to manage
the excess generated power and increase the operational savings.
• Improving system frequency is
considered.
• Islanding detection does not take
into consideration.
• Enhancing system stability is not
concerned.
124 Presenting a study of real-time power-consumption-reflective pricing to schedule
concurrent tasks and to manage the energy within the operation of PV and
storage systems.
concerned.
• Mitigation frequency oscillation is
not considered.
• Enhancing system balance is not
considered.
125 Controlling structure to manage energy by applying two stages technique of
flexible resources. The first level is used to reduce electricity bills, while the
second is devoted to the sense voltage across PCC to balance both sides of
generation and loads requirements.
• Frequency regulation to its
nominal value is not investigated.
• Improving power quality is not
considered.
• Ensuring the system balance is not
studied.
considered.
performed.
• Power loss reduction is not
considered.
126 Presenting an advanced strategy based on two approaches; implementing the
reinforcement-learning to deal with the applied loads' households to achieve
better performance and the fuzzy reasoning that is an integrated user feedback
process to schedule operation and shift controllable loads from peak to off-
peak periods.
• Regulating system frequency does
considered.
(Continues)

represented in Figure 9.130
Table 4 presents the contributions and the shortcomings of the most recent research using
the APC method.
3.5 | Grid reinforcement (GR)
Grid reinforcement (GR) is an overvoltage mitigation strategy based on changing the network structure to reduce the
voltage rise challenge. The main concept of this method is to replace the feeder of the distribution system with another
one that had lower resistance or high cross-section area to get a modified voltage value across PCC2
as voltage rise is
related to the length of the connected feeder.26
Otherwise, the system reinforcement strategy provided the capacity dur-
ing the high integration of PVs due to the connection of electric vehicles to minimize charging costs.140
This strategy
needs an expensive cost due to reshaping the network structure, especially in the radial system2
; hence this solution is
ineffective. Table 5 presents the contributions and the shortcomings of the most recent research using the GR method.
3.6 | On-load tap changer
On-load tap changer (OLTC) is an effective technique to mitigate voltage deviation in a LVDN due to the existence of a
grid transformer.26
This method is based on the turn ratio change of the transformer and getting the whole data from
buses using communication infrastructure (CI).2
The structure of taps' types could be as mechanical tap changer (MTC)
and electronic tap changer (ETC). The ETC is effective more than MTC as the MTC has a delayed operating time to
adjust the system voltage and needs a high maintenance cost. Also, the ETC can change the voltage for every cycle;
hence it is a fast type for voltage measurement.26,146
This method can coordinate with controlling strategies to improve
its flexibility.146
While strategy's disadvantages are frequent switching of OLTC leads to generate arc,146
and it depends
on collecting data from the specified feeders. Hence, information and communication technology (ICT) was needed;
therefore, costs are high.26
the OLTC method.
3.7 | Reactive power compensation (RPC)
This method depends on improving reactive power generation in the network to overcome the challenge of voltage rise
by using FACTS that are applied to administrate reactive power flow.152
FACTS devices include D-STATCOM, Static-
Var Compensator (SVC), Thyristor-Controlled Series Capacitor (TCSC), Static Synchronous Series Compensator
(SSSC), Unified Power Flow Controller (UPFC), and Synchronous Condenser (SC). D-STATCOM is a compensator
device used to adjust voltage systems by coupling with a voltage value of voltage source converter (VSC). This could be
maintained by exchanging the amount of reactive power. SVC is a shunt-connected static compensator that depends on
thyristor-controlled. It provides a lagging or leading power factor to regulate the voltage value and achieve high perfor-
mance in the presence of a high value of capacitances to modify reactive power.153
However, SVC would be adjusted
with a filtration loop approach to reduce network disturbances.154
Also, TCSC is a FACTS device consisting of a thyris-
tor and series capacitor connected to the transmission line to regulate the voltage system. It has the same advantage as
SVC.155
SSSC is also defined as a series compensation device that controls reactive power across the system by
maintaining output voltage and independent line current. SSSC could achieve high performance to generate or absorb
TABLE 2 (Continued)
127 Designing a developed EVs charging /discharging with a centrally coordinated
schedule approach of the charging and discharging modes to keep voltage
profile into steady-state mode and improve power quality will handle the users'
economic and grid constraints.
• Enhancing the system balance is
not studied.
• Adjusting the system frequency is
not considered.
• Analyzing the system stability is
not considered.

TABLE 3 Contributions vs shortcomings of the most recent research using the RPS method
55 Implementing an adaptive RPC to improve power transfer and adjust power
factor during injecting/absorption of reactive power under weak grid
conditions where short circuit ratio is close to 1. This strategy is also based
on a q-axis current to limit the voltage at PCC and to put it into the
accepted range.
• Mitigating the frequency oscillation
does not take into consideration.
achieved.
49 Applying a conservation voltage reduction technique with a VOLT/VAR
management to improve power factor and reduce network loss, this
strategy is estimated on the urban distribution system during low loads
and peak PV generation.
• Adjusting the system frequency to its
nominal range is not investigated.
• Islanding detection impact is not
considered.
128 Proposing Var control method for system voltage support in LVDNs with the
presence of high penetration of PV systems under different PV power
generation conditions.
• Mitigating system frequency deviation
is not considered.
• Improving system efficiency is not the
main purpose.
129 Introducing the using of MV/LV transformers to increase the hosting
capacity of the PV systems in LVDNs while eliminating the use of complex
and centralized controllers.
consideration.
• Reducing frequency oscillation is not
considered.
• Minimizing power loss is considered.
• Improving system balance is not
concerned.
130 Applying three levels of distributed voltage control by adjusting the reactive
power at a reference value improves the voltage quality. The first level was
the flicker control to get fast response could have occurred, the second
level was the local control to get the local data about each distributed
inverter which made this strategy characterize with low cost due to the
lack of communication infrastructure, and the third level was the
coordinated control with the active power curtailment to reduce system
losses.
• Islanding detection is not studied
during the excessive penetration
of PVs.
• Regulating the system frequency is not
studied.
• Stability enhancement is not studied.
131 Proposing a VOLT/VAR optimization strategy with a multiagent deep
reinforcement learning (DRL) to solve voltage unbalancing across the
distribution system, the proposed DRL framework could be extended to
keep up the modified voltage droop control smart inverters.
• Regulating the system frequency to its
• Islanding detection challenge is not
studied.
• High penetration of PVs is not
considered.
• Stability analysis is not performed.
132 Designing a new inverter control that is based on a learning grid and the
novel design is implemented as a multifunction learning problem to have
the ability to coordinate between inputs and outputs for voltage and
optimal power flow regulation.
• Adjusting the system frequency to its
• Analyzing the system stability is not
performed.
• Minimizing the system loss is not the
main contribution.
133 Defining the VOLT-VAR response by a mathematical equation and
analyzing the integration PV units to identify which phases integrated
with PVs absorbed much reactive power, incorporating the proposed
strategy with a consensus algorithm to overcome imbalance cases.
• Power loss reduction is not studied.
• Adjusting system frequency is not
considered.
• Improving the system stability is not
achieved.
134 Presenting three modes of RPS local voltage controller of PVs inverters to
evaluate current node voltage and get a set point of reactive power.
• Power loss minimization is not
studied.
• Frequency regulation does not take
into consideration.
(Continues)

reactive power flow at specific values of capacitances, but it recorded a high performance at specific values of capaci-
tances.156
A UPFC is an advanced device among FACTS to solve the existing disturbance in power flow and voltage pro-
file. It is based on coordination between series and parallel converters that leads to high cost. A SC is a rotating-
synchronous machine that can inject or absorb reactive power in the system by using an automatic exciter circuit to
support the grid with a specific reactive power. However, it is rare to use because of the high-power loss and inadequate
response.157
Table 7 presents the contributions and the shortcomings of the most recent research using the RPC
method.
3.8 | Hybrid methods
Hybrid methods (HMs) are an effectively used technique to overcome voltage rise challenges that resulted in high
excessive integration of PV power plants. This technique coordinates strategies to provide a better performance and
improve system efficiency.26
the HMs.
TABLE 3 (Continued)
studied.
performed.
FIGURE 9 Flowchart of applying APC strategy130

TABLE 4 Contributions vs shortcomings of the most recent research using the APC method
46 Proposing a short-term forecasting technique for PV generation due to the
high losses that resulted from traditional curtailed power. This strategy
required modeling the PV unit's performance using Kalman filter theory
to deal with generated power to regulate voltage.
• Frequency regulation is not
considered.
• Stability improvement is not the
main contribution challenge.
• Islanding detection is not studied.
• Voltage is not adjusted to its nominal
value.
• Power quality improvement does not
91 Presenting an intelligent strategy based on modern inverters to reduce losses
to get the optimal setting and reduce computational complexity, this
technique is also based on a nonsorted genetic algorithm controlling
active power injection.
• Adjusting the system frequency is
not studied.
considered.
• Improving the voltage balance is not
studied.
• System stability improvement is not
performed.
considered.
130 Applying the robust response using local and coordinated voltage control
techniques enhances node voltage and supports reactive power capability.
• Improving frequency profile is not
studied.
studied.
• System balance enhancement is not
considered.
136 Proposing artificial neural networks techniques for active power curtailment
through PV inverts to mitigate voltage rise in LVDNs.
considered.
• Islanding detection is not a concern.
137 Applying centralized coordination between appliances of EVs and
mitigation controlling strategy to overcome the negative impacts of
integration of both EVs and PVs, the proposed technique is based on a
mixed-integer quadratic programming (MIQP) approach.
• Frequency is not regulated to its
nominal range.
• Ensuring the system balance is not
considered.
• Achieving better system stability is
not studied.
• Islanding detection is not performed.
investigated.
138 Supporting grid functions by a methodology of the activated inverters to
estimate the output power from the volt-watt curve curtailed from the
required customer consumption during operation time for voltage
regulation.
considered.
considered.
139 Presenting an active power and reactive power injection method to deal
with voltage sensitivity for voltage regulation, minimizing voltage
deviation, and improving efficiency.
• Regulating frequency profile is not
performed.
implemented.
considered.
applied.

4 | COMPARISON BETWEEN THE OVERVOLTAGE MITIGATION
METHODS
In this section, a comparison between the different overvoltage mitigation methods is performed based on their ability
to overcome the impact of the overvoltage under high penetration of PV units in the LVDNs. Table 9 presents the com-
parison between the overvoltage mitigation methods concerning the overvoltage in the LVDNs. Furthermore, Table 10
shows a comparison between overvoltage mitigation methods based on their pros and cons.
TABLE 5 Contributions vs shortcomings of the most recent research using the GR method
131 Proposing the deep reinforcement learning based on VOLT-VAR
optimization to regulate voltage in the distribution system, the
applied approach was implemented on a deep-Q network to overcome
various time conditions during operation.
• Mitigating the oscillation in the system
frequency is not considered.
• System stability is not studied.
performed.
• Voltage profile is not regulated to its
nominal value.
141 Using the infrastructure reinforcement to restructure the connected
feeders in the low-voltage distribution system, hence over-voltage
mitigation, the applied strategy based on a Monto-Carlo approach to
increase the hosting capacity in the system by adding available
electrical vehicles.
• Power loss reduction is not studied.
• Islanding detection is not studied with
the high penetration of PVs.
• System frequency is not regulated with
the high penetration of PVs.
• Unbalance due to the high penetration of
PVs is not considered.
studied.
142 Integrating network reinforcement and distribution system in a
competitive market using a DSO capacity signal in multistage
programming to confirm system security.
• System frequency regulating is not
studied.
• Islanding detection is not performed
under the PV-high penetration in
LVDNs.
143 Applying an optimization reinforcement at load side and renewable
energy sources by a mixed-integer nonlinear programming model
reduces life cycle costs.
• System voltage is not maintained to its
nominal value.
• Obtaining a balanced system is not
studied.
• System frequency regulation is not
considered.
• System stability under the integration of
PVs is not studied.
144 Presenting an algorithm of real-time incentive-based demand response
based on reinforcement learning and deep neural network for smart
grid systems to predict and avoid future challenges and balance load
and generation sides considering the energy demands.
• System frequency regulation is not
investigated.
• System stability is not analyzed and
improved.
considered.
145 Implementing a model-free deep reinforcement learning (DRL) method
to control optimizes the battery energy during a degradation mode to
maintain the charging /discharging period to address electricity
prices.
• System frequency regulation does not
• Unbalance occurred due to the high
penetration of PVs is not considered.

5 | NEW TRENDS FOR OVERVOLTAGE MITIGATION IN LVDNS
Nowadays, there are various trends for overvoltage mitigation in the LVDNs that can be summarized as follows:
• Improving the performance of the overvoltage mitigation schemes using recent optimization algorithms. Many opti-
mization algorithms can be applied to obtain optimal parameters and system sizing in the presence of excessive pene-
tration of the PV systems in the LVDNs. The global optimization problems can be solved using different meta-
heuristic optimization algorithms. The main idea of any optimization algorithm is the simulating of the artificial and
natural tool while performing the exploration and exploitation search to obtain the optimal solution over a defined
search space. Several meta-heuristic techniques have been proposed to solve different problems. Nowadays, many
researchers design new optimization techniques or make modifications to the existing methods to obtain competitive
results of the different optimization problems.
• Studying the impact of using demand response with the overvoltage mitigation schemes. The demand response pro-
vides all the modifications for the customer's electricity consumption. Also, it includes the incentive payments that
TABLE 6 Contributions vs shortcomings of the most recent research using the OLTC method
58 Coordinating strategies between the existing inverters and OLTC using
fuzzy controlling to track maximum power point, achieve optimal
power flow, and adjust voltage profile at each feeder, the coordination
based on a multilayer feed-forward neural network technique
(MFFNT) to maintain voltage across feeder.
applied during the high integration
of PVs.
nominal value.
147 Implementing a novel case of the OLTC approach to avoid voltage error
with an MPC, the applied coordination based on centralized control to
minimize power loss.
• System unbalance is not improved.
• Islanding detection with excessive
penetration of PVs is not studied.
• Frequency oscillation is not regulated.
• System stability is not a concern.
148 Using closed-loop conservation voltage reduction (CVR) by a voltage
regulator as OLTC and capacitor bank to optimize active power flow
at the three phases and achieve a normal CVR operation.
• System voltage regulation is not studied.
performed.
• Achieving a balanced system is not a
concern.
149 Proposing an OLTC as a tap operation at an imbalance network to keep
voltage value into an accepted limit, the proposed approach is based
on using mixed-integer linear programming as an optimization
method for controlling reactive power of the connected inverters.
• Frequency regulation is not studied.
• Islanding detection is not applied.
considered.
150 Applying a multi-period voltage control approach by integrating an
energy storage system with OLTC, while the proposed algorithm is
based on a decentralized layered multi-agent coordination to maintain
the system performance during the injection/absorption of reactive
power and adjust the challenge of the voltage profile.
• Frequency oscillation is not mitigated.
151 Modeling the distributed system for obtaining an approximation
calculation of voltage profile by estimating the reactive and active
power injection and connecting OLTC to handle voltage sensitivity.
• Power loss minimization is not a
concern.
applied.

are provided to the customers for time, total demand, and instantaneous demand changing. It ensures the system's
ability to match the customer demand and the system generation while improving the system flexibility and security.
TABLE 7 Contributions vs. shortcomings of the most recent researches using the RPC method
158 Presenting a PSO as a multipurpose planning algorithm to compensate
reactive power through a unified power quality conditioner (UPQC) and
minimize the system power loss.
• Frequency regulation is not a
concern.
• Improving system unbalance does
159 Implementing D-STATCOM to inject the optimal phase angle of the voltage,
also, the optimal location and the rating of D-STATCOM was obtained to
reduce power loss.
• Islanding detection is not a concern.
• Mitigating frequency oscillation is
not considered.
160 Implementing a D-STATCOM with finite control set MPC to adjust the
system voltage and reduce the harmonics distortion.
• System voltage regulation is not
concerned.
is not considered.
• Islanding detection under high
penetration of PVs is not
investigated.
• Power loss reduction does not take
into consideration.
• System unbalance due to the high
161 Applying the integration between both EV and STATCOM to support
system voltage for enhancing the system stability and reliability of the
grid.
implemented.
• Power loss reduction is not
considered.
• System stability enhancement is not
performed.
162 Proposing the optimal size for UPFC s required to ensure optimal power-
sharing between converters, while the technique of UPFC is based on
power angle control.
performed.
163 Presenting an integration between UPFC and controllable approach as
fuzzy logic to adjust the system voltage into an accepted limit and
improve power quality and the controlling technique was to tackle power
disturbance and mitigate voltage.
• Adjusting the system frequency is not
studied.
investigated.
• Power loss minimization is not
considered.
164 Performing UPFC with a predictive model control at imbalance system that
is based on multilevel to maintain voltage.
• Frequency regulation is not applied.
• Islanding protection is not
considered.
165 Implement the STATCOM with a genetic and bacteria foraging algorithm to
obtain better performance during changing PVs outputs due to weather
conditions.
considered
• Islanding detection does not take
into consideration
considered.
166 Installing the FACTS devices with cyber security of exchanging data about
wide-area controllable network, while the proposed method can indicate
the optimal placement of FACTS.
nominal range.
considered.

The demand response can be applied to enhance the system performance with the high penetration of PV systems in
LVDNs, hence tackle the problem of overvoltage occurrence in the time of connecting the excessive PV systems in
LVDNs.
• Applying machine learning and deep learning applications in the overvoltage mitigation schemes for multi-
interconnected microgrids. To mitigate the effect of the overvoltage that results from the excessive penetration of the
PV systems, different control methods and techniques can be applied. Machine learning and deep learning can be
used to improve the performance of the overvoltage mitigation-based control methods. Also, it can be applied for sys-
tem training to overcome the system uncertainties and disturbances that may occur during the system operation
under the high penetration of PV systems in the LVDNs.
TABLE 8 Contributions vs. shortcomings of the most recent research using the HMs
167 Presenting an effective concept of coordination reactive power control with
active power curtailment to obtain a better over-voltage mitigation
strategy, while increasing hosting capacity for each feeder.
• System frequency does not take into
consideration.
• Unbalanced challenge is not
considered.
168 Investigating the shortcomings of each APC and RPC separately and
providing the combination of two strategies to support voltage profile in
presence of grid-tied inverters.
• Improving system stability is not
considered.
• Regulation system frequency is not
achieved.
169 Integrating OLTC and battery energy storage systems to keep voltage value
into an allowable limit, while using batteries exceeded the power and
minimized the changes in transformer taps. A centralized controller was
used in the case of OLTC to collect information for each node. On the
other hand, this coordination is not a better usage for regulating voltage.
• Frequency regulation is not applied.
implemented.
studied.
• System balance improvement is not
considered.
• System stability analysis is not
investigated.
170 Presenting coordination between an OLTC to control voltage across nodes
and a battery storage system to ensure an optimal power flow, a dual-
interior point optimization algorithm was applied to provide an optimal
battery location.
• Islanding detection is also not
applied.
concerned.
171 Proposing coordination strategies between various types of storage systems
and APC to improve the active output power of PVs, to reduce the need
for capacitors, and to decrease losses that generated from the curtailment
method, this approach is based on dispatching the output power of
batteries to get an optimal allocation of the used batteries.
investigated.
172 Presenting a study of integration active power with reactive power control
by using PV's inverters, this approach is based on droop control to
regulate voltage profile and reduce losses.
• System frequency regulation does
investigated.
• Unbalance due to the high
173 Performing an optimal power flow model to adjust both active and reactive
power generated from three phases of the distributed generators to
balance the voltage variation across PCC.
• Frequency oscillation mitigation is
not considered.
174 Implementing the OLTC and STATCOM by a genetic algorithm to get an
optimal location for STATCOM for a reconfiguration of both voltage
control and energy savings.

T
A
B
L
E
9
Comparison
between
the
overvoltage
mitigation
methods
concerning
the
impact
of
the
overvoltage
in
LVDNs
ESSs
LSM
RPS
APC
GR
OLTC
RPC
HMs
Frequency
oscillation
42,67,135,138
26
40,155
Rotor
angle
stability
39
42
40
Power
flow
116
2,26
55,59,131,132
141
58,148
155,156
170,171,173
Power
quality
110,116
121,127
55
140,144
26,153,155-157,160-162
26,161,171,173
Voltage
profile
and
reactive
power
111
121,125
41,55,59,131,132
46,130,139
150
26,153,155-157,161,162,165
26,161,169,173
System
reliability
116
121
55,59
46
58
153,155-157,166
System
inertia
53,55,56
54,57
Unbalance
of
LVDNs
102
17,109
17
17,134,137
17,144
Protective
devices
68
137
66,67,69
System
flexibility
96,100
102
47
36
17,46
130
141,145
Power
loss
93,97,82
93,97,98
47,106,107
36,106,112
107,117
122,123
130,132,138
17,141,144,145
Voltage
regulation
93,97,98
17
2,17,44,47,106-110
36,78,106,111-114
17,107,116-118
17,46,121-124,126
17,31,128,130-135,138,139
17,134,140,141,144,145
Islanding
detection
93
102

TABLE 10 Comparison between overvoltage mitigation methods based on their pros and cons
Method Pros Cons
ESSs • Managing the output energy by storing the excess energy
of the consumers.
• Regulating the system frequency.
• Smoothing the output of energy.
• Exporting the curtailed energy.107
• Having a better economic performance.2,116
• Damping the energy oscillations.109
• Preventing the revering power flow.116
• Some types of batteries had a shorter life cycle memory
effect.
• Having a complex recycling procedure.
• Lower energy density.
• Flat discharge curve.
• Installation was costly.107,111
• High overall costs for the centralized control approach.117
• Complex calculation of applying rotational neighboring
participation analysis using Jacobian analysis beyond
battery storage.118
LSM • Using to prevent voltage rise.26
• Coordination with ESSs to increase efficiency.26
• Optimal power flow in distribution system.26
• Reducing the electricity bill.26,126
• Reducing overall system costs.121
• Cost-effective in smart grids.125,126
• Effective strategy during only a low number of PVs.26
• Requiring a lot of iteration to keep voltage value into
accepted limit.121
RPS • Improving power factor.55
• Improving power transfer capability.55
• Using the conservation voltage reduction technique
helped reduce peak demand, improve power factor, and
achieve energy savings.59
• Adjusting the sudden change in voltage.26
• Having a Fast response to regulate voltage.139
• Reactive power capability was limited due to the amount
of real output power.26
• Does not adequate for the high R/X ratio.2,26
• Applying voltage control using reactive managing power
is not an effective solution for the transformer's furthest
point due to the high voltage deviation.2,130
APC • Improving the voltage regulation, adjust the power
factor.46
• Reducing the resulting power loss by applying to forecast
the PVs output power at a short time.46
• Effective solution for voltage-rise occurred due to the
excessive penetration of PVs at LVDNs where the high
ratio of R/X.130,137
• Voltage control by WATT/VOLT of smart inverters leads
to reducing in the installation of controlling devices;
hence, the approach reduces costs.135
• Applying traditional APC during excessive PVs
integration led to a high loss of power.130
• Applying the APC strategy with the appliance of EVs
would have the ability to reduce the optimization
model.137
GR • Using grid reinforcement resulted in achieving voltage
balance; also, the coordination with OLTC helped keep
the strategy more economical.26
• Reinforcement could handle the grid congestion by
reducing devices.140
• Enhancement grid using EVs could lead to cost reduction
of charging.140
• Providing services for consumers to purchase the needed
energy resources to eliminate power imbalance and
achieve system reliability.144
• Does not considered an economical-effective solution.26
• Does not considered an effective solution for radial
systems due to the installation of feeders to reduce
impedance feeders.2
OLTC • Increasing PV hosting capacity through MV/LV
transformer.2
• OLTC could be integrated with storage systems to reduce
stress at transformer and system loss.2
• Applying controlling strategies with OLTC may help to
reduce energy loss and adjust node voltage at set
points.147
• Highly costs strategy due to the need for communication
devices.2,26
• OLTC may lead to saturation of the MV/LV
transformer.26
• The strategy could not be an effective solution for the
challenge of voltage rise due to the limited lifespan of
TC.2
RPC • Independent of the generated active power.26
• Providing the power balance between the received and
the sending sides.153
• Helping in harmonics mitigation.154
• SSSC requires high costs to be installed.152
• SVC has a slow response to time delay.152
• STATCOM has a high loss compared to SVC at the same
rating range.152,153
(Continues)

• Applying the Internet of Things (IoT), Fog, and cloud platform to enhance system monitoring performance and
increases decision-making time. The main idea of the IoT is to connect billions of virtual and physical objects with
the internet. This may lead to generate a huge volume of data and information that may be difficult to manage and
process these data and information. Hence, the existence of fog and cloud may solve this issue by performing infra-
structure for information and data storage and processing. This intermittent platform provides appropriate real-time
monitoring for all system appliances and components with required sensors with a convenient communication
approach. With the large distribution network and excessive penetration of PV systems, the use of IoT, Fog, and
cloud computing platforms is required for system monitoring, data storage, and processing. This may facilitate the
decision-making time and ensure accurate system performance.
• Modifying the communication infrastructure network using the fifth-generation (5G) technology and beyond. The
communication infrastructure between different appliances and components in the LVDNs can be improved using
the 5G technology. It provides wireless communication between different system components with high-speed data
and information transferring and large bandwidth. It can be applied to ensure the smartness of the system in pres-
ence of high penetration of PV systems in LVDNs.
• Implement a model with a tri-level defender-attacker defender (DAD) model to evaluate the limited accepted range
without high voltage drop and enhance the system's cyber security. Due to any vulnerabilities in the system, any
cyber incidents can affect the operation's economic and physical impact. With the high penetration of PV systems in
the LVDNs and the increasing of the power electronic devices, any cyber-attacks may affect the performance and
operation of the power electronic devices in the system. These cyber-attacks affect the system data and information
availability and integrity. Hence, designing an appropriate cyber-security-based system is required to tackle these
problems.
6 | CONCLUSION
This paper presents the effect of the integration of excessive PVGUs at LVDN. Also, it reviews the proposed overvoltage
mitigation techniques in LVDN. This paper compares the various overvoltage mitigation methods, including their
shortcomings and contributions of the most recent research and the pros and cons of each strategy. Overvoltage
TABLE 10 (Continued)
Method Pros Cons
• Having a Fast response for controlling the system and
damping disturbances.155
• Reducing system loss, improve system stability, power
quality, voltage stability, and enhance the power transfer
capability.157
• Optimizing the system operation, improve line capacity
and load ability, and achieve better efficiency
increment.156,157
• Reducing resonance phenomenon.160
• Mitigating voltage unbalance.26,161
• Cost-effective devices for voltage support.161
• Reducing overall costs due to two connected power
converters by using the power angle control.162
• Improving the voltage deviation.165
• UPFC is a highly cost type of FACTS due to the
combination between SSSC and STATCOM.152
• The formation of the compensating devices that had
thyristor controllers resulted in resonance issues, unlike
the devices that were based on voltage source
converters.157
HMs • High system efficiency.26
• Coordination between hybrid methods could be an
alternative method in case of failure of any of them.26
• Minimizing power loss.26,171
• Integration BSSs with OLTC resulted in reducing the
stress of changer of OLTC; hence batteries would have a
long lifetime.169
• Adjusting the voltage profile to its nominal values.174
• High cost.171
• Frequency reduction in case of high range of real-time of
variation PVs power during calculation time of the
allocation model.171

mitigation challenge has the most study share by providing multiple effective methods such as EESs, LSM, reactive
power support, active power curtailment, GR, OLTC, reactive power compensation, and hybrid approaches.
In this paper, a comparison between each strategy has been summarized in terms of a fast, effective solution to solve
negative impacts and a comparison between overvoltage mitigation strategies. This comparison shows that:
i. ESSs are the common solution to prevent adverse impacts such as system loss reduction, adjusting system voltage,
enhancing system reliability, flexibility, power quality improvement, and islanding mode detection. However, this
method has high installation costs and cannot regulate system frequency.
ii. LSM is an effective solution for preventing overvoltage at unbalanced LV systems, editing power flow, enhancing
islanding detection, improving each power quality, system reliability, and flexibility. This strategy also helps
reduce electricity bills for end-users. On the other hand, this strategy is effective in the presence of a low number
of PVGUs and getting no involvement in maintaining rotor angle stability.
iii. RPS has a problem with adjusting system frequency and islanding detection. This method is not practical in the
case of a high R/X ratio. However, this method is an attractive solution for voltage control, imbalance system
detection, reversing power flow prevention, and reducing system loss.
iv. APC is the most attractive solution for modifying the poor impacts of excessive penetration of PVs with highly
R/X ratio, such as voltage flicker mitigation, frequency oscillation reduction, and system reliability enhancement.
However, the strategy cannot detect system imbalance.
v. GR is an enhanced solution for voltage regulation, loss reduction, imbalance elimination, and reverse power flow
detection. In contrast, this strategy is not economical due to the high costs and cannot mitigate the overall nega-
tive impacts.
vi. OLTC is an effective strategy to regulate system voltage and frequency, enhance system reliability, prevent revers-
ing power flow, and reduce system loss. At the same time, this strategy has problems improving system power
quality and islanding detection due to limited lifespan.
vii. RPC is considered FACTS installation to regulate the amount of reactive power to regulate voltage profile, leading
to power loss reduction, damping frequency oscillation, power quality improvement, maintaining unbalance sys-
tem, and improving system flexibility. Despite the high amount of contribution, the installation of the compensa-
tion devices led to high costs.
viii. HMs are an advanced-coordinated strategy that helps achieve higher efficiency, apply better system reliability,
and overcome the negative impacts. Integration FACTs can implement this method as STATCOM and batteries
storage systems, OLTC and storage systems, energy storage system and controlling techniques such as APC, and
coordination between APC and RPS.
PEER REVIEW
The peer review history for this article is available at https://publons.com/publon/10.1002/2050-7038.13161.
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available on request from the corresponding author. The data are
not publicly available due to privacy or ethical restrictions.
ORCID
Bishoy E. Sedhom https://orcid.org/0000-0001-9223-694X
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