Renewable Energy Focus 44 (2023) 139–173
Contents lists available at ScienceDirect
Renewable Energy Focus
journal homepage: www.elsevier.com/locate/ref
Power quality and stability improvement of microgrid through shunt
active filter control application: An overview
Buddhadeva Sahoo a,⇑, Mohammed M. Alhaider b, Pravat Kumar Rout c
a
Department of Electrical Engineering, Silicon Institute of Technology, Odisha, India
College of Engineering at Wadi Addawaser, Prince Sattam bin Abdulaziz University, 11991, Saudi Arabia
c
Department of Electrical and Electronics Engineering, Siksha ‘O’ Anusandhan University, Odisha, India
b
a r t i c l e
i n f o
Article history:
Received 20 May 2022
Revised 22 September 2022
Accepted 24 December 2022
Available online 2 January 2023
Keywords:
Shunt active filter
Power quality
Microgrid
Series active filter
DC-link voltage control
Synchroniser
a b s t r a c t
Owing to avoid harmonic and power quality issues, the concept of eliminating their impacts on microgrid
systems has gained a lot of interest. Incidentally, shunt active filters (SHAFs) is selected as the most reliable solutions against the concern problems and become the first choice of researchers. However, the performance of SHAF is strictly dependent upon the controller’s action, design, and stability. Looking at the
necessity, the detailed working of parallel/series filters for current and voltage source-based non-linear
load application is discussed and compared. This paper reviews and collects information related to various SHAF control techniques for improving microgrid performances. The effectiveness of the controller is
examined and justified by considering the non-linearity reduction, dc-link voltage balancing, current and
voltage regulation, and improving the synchronization techniques. In this review, the most advanced
control techniques are discussed and contrasted systematically to highlight their strengths and weaknesses. In addition to that, by considering different control architectures, the possible control outcomes
and shortfalls are also summarized in different tabular forms. The survey can hypothetically serve as a
standard and establishment of material for selecting the most significant methods for smoothening the
SHAF operation for complex microgrid systems.
Ó 2022 Elsevier Ltd. All rights reserved.
1. Introduction
appropriate integration and control solution for renewable
energy-based microgrid systems.
1.1. Importance of alternative source selection and motivation
Recently, the rise in population, household utilities, industries,
and digitalization has upsurged the power demand at a frightening
rate [1]. However, to meet the power demand, traditional power
sources such as coal, diesel, and fossil fuels are not sufficient.
Therefore, to support the backbone of energy generation, alternative sources such as wind, solar, and hydro-based power plants
are developed and gaining interest [2]. The use of alternative
sources, power electronic devices, distributed generations, battery
storage cells, increases the power quality and reliability standard
by reducing the transmission and distribution losses, cost, and size
[3]. The government also provides a lot of incentives and support
to install alternative sources-based plants for green energy production and reduce the burden on the national power plant [4]. The
facilities provided by the government, present needs, and sustainable solutions motivate the power engineers to develop an
⇑ Corresponding author.
E-mail address: buddhadeva14@gmail.com (B. Sahoo).
https://doi.org/10.1016/j.ref.2022.12.006
1755-0084/Ó 2022 Elsevier Ltd. All rights reserved.
1.2. Challenges during the integration, idea of power filters, and
motivation
In power industries, the proliferation of power electronic
device-based load and renewable energy-based distributed generators brings the attention of the research towards the harmonic
contained and frequency variations in power system applications
[5]. The presence of harmonic also creates power quality and stability issues in real-time microgrid applications by decreasing the
power factor from its rated value [6]. In addition to that, it creates
overheating problems, measurement errors, excess energy loss,
decrease in efficiency, voltage and frequency mismatch, and
instrument failure [7]. The persistence of challenges leads to a
stochastic and intermittent power supply. To limit the harmonic
effects and quality power supply, the latest international standard
i.e IEEE-519 is articulated and mentioned that the total harmonic
contained for current must be well within 5 % of the total current
[8]. Therefore, to maintain the international standard, appropriate
harmonic current regulation and compensation methods are
B. Sahoo, M.M. Alhaider and P.K. Rout
Renewable Energy Focus 44 (2023) 139–173
this survey is silent about the APF control action during unbalanced grid or non-linear load conditions and also not considered
the robust control strategies and optimization techniques. Further,
in [20], a control-oriented review paper is presented by considering traditional APF control algorithms till 2018, and to support
the above, in [21], a review article is presented without considering
the multi-agent method, model predictive control, and synchro
phasor operation till 2018. Therefore, there is a requirement to
analyze and discuss the most recent APF control action for complex
microgrid system applications during both balanced and load
conditions.
needed to improve the quality and reliability of the grid-connected
and islanded system application. Traditionally, passive power filters are used for harmonic compensation in microgrid applications
[9]. However, the bulky structure, excess switches requirement,
constant load application, and static compensation methods, the
preferences have been shifted towards active power filters. Active
power filters are capable to mitigate the high order harmonics,
providing reactive power support, balancing voltage and frequency, applicable for variable load applications, and also facilitating reduced switch multi-level inverter applications [10]. The
benefits prove their significance and motivate the researchers to
apply for alternative source-based microgrid applications.
1.5. Contribution
1.3. APF evolution, challenges, idea of control solutions, and
motivation
The major focus of the study is
1. Perform an inclusive assessment of different APF selection,
design, and working principles. In addition to that, a comparative analysis between the working principles of parallel/series
filters for current and voltage source non-linear load applications is also studied for a clear distinction and to justify the
importance.
2. Highlight the important shunt active filter (SAF) control techniques as non-linear extraction technique (NET), dc-voltage
control technique (DC-VCT), current regulation technique
(CRT), and synchronizer for real-microgrid system application.
3. SHAF control literature study categorized and coordinate the
research undertaken in balanced/unbalanced load-based microgrid application by emphasizing primary, secondary and tertiary methods.
4. The complete study of SHAF design and control with its significant merits and demerits makes this review different from
other papers.
5. To improve the paper’s presentation level different comparative
tables are structured by considering control architecture, local
control selected, V&f mode, power management, optimization,
steadiness, battery management, and installation complexity.
6. At last, the research gap and possible solutions are highlighted,
and this can be considered as an additional contribution to this
research field.
Due to the significant development of APF, various power engineers are analyzed and surveyed on this at different perspectives
and angles of microgrid applications. In [11], the working of active
conditioners is analyzed in the time and frequency domain compensation method and discussed the merits and demerits of each
method. In [12], as per the inverter type, construction, practical
functions, structure of the power system, associated controller,
and its application, the APFs are categorized into different numbers. To support the above, in [13], a total of 22 numbers of basic
power filters as series, shunt, hybrid, and universal power filters,
etc are discussed and concisely compared their outcomes according to their application and structure. In [14], a comparative power
filter study is done and concluded that out of all power filter
topologies, shunt-connected APFs are performing excellent results
during complex system applications. In [15], the operation of APFs
is characterized as per the rating, circuit design, harmonic contained, power factor and frequency imbalance, control technique
and reference switching signal generation, etc. However, the
improvement of APF also increases the requirement of semiconductor switching devices such as a thyristor, MOSFET, insulated
gate bipolar transistor (IGBTs), and emergencies the requirement
of power controllers as digital signal processors (DSPs) and fieldprogrammable gate arrays (FPGAs) [16]. Moreover, due to the
occurrence of non-linear grid voltage, the performance of APFs is
also decreased and needs significant structural and control modifications during real-time applications. From the literature review, it
is found that the APF performance depends on the appropriate control action. Therefore, the study motivates the researchers to not
only focus on the design of APFs but also on their control strategies.
2. Research methodology
In order to draw the attention of the power engineers, a comprehensive review on the existing shunt active filter control literature, and exploratory research on the development and types of
shunt active filter and control aspects are selected based on systematic, technical, and scientific resources as IEEE, Elsevier, Wiley,
Google Scholar, and Research Gate, etc. In the making of the paper,
the important factors such as benefits of series and parallel connection of voltage and current source inverters, control strategies
related to SHAF, microgrid applications, grid forming, and following conditions, challenges, and research gaps, and possible solutions are considered. To collect important, related, and to-thepoint control-oriented research papers, certain survey criteria such
as important terms, peer-reviewed journals and international conferences, and open-access scientific papers are fixed. Based on the
available data, data in brief, related conference/ journal titles,
abstract, and conclusion, the questionaries are developed to present the paper innovatively.
Questionaries:
Phase-1: Paper design:
1.4. Effective control solutions and motivation
In [17], various control solutions are surveyed based on the
most common problem i.e., nonlinearity issue and reference
switching pulse generation for APF operations. However, the
review paper only signifies the control methods without discussing
their strengths and weakness. In [18], different power quality (PQ)
control algorithm is discussed for appropriate APF operation. Similar to the above, in [19], different converter topologies and associated control solutions are suggested to solve the PQ problems
associated with the APF operation. However, in [18–19], the review
is not presented systematically and not considered V/f and droop
control methods. In [20], the associated APF control strategies are
compared and discussed by considering time and frequency
domain, impedance calculation, real and reactive power support,
balanced dc-link voltage, harmonic compensation, reference current, and appropriate switching pulse generation. It is found that
all the control strategies perform similar results having few merits
and demerits during balanced grid voltage conditions. However,
Related to the recent research area, does this literature review is
required, and is it results in a significant, real-world/conceptual
contribution?
140
Renewable Energy Focus 44 (2023) 139–173
B. Sahoo, M.M. Alhaider and P.K. Rout
Check the methods of data collection to guarantee the quality
and standard of the paper.
Find suitable methods of data identification by considering the
overall problem formulation and research questioning.
Check the analysis process is properly defined and transparent.
Check the objective, motivation, need, and research questions
are clearly stated or not.
Is the review paper’s interpretation similar to the earlier literature and other appropriate literature?
Check the methodology of the presented paper is indicated or
not.
Does this is the most significant method to address the research
problem?
Check the transparency level of methodology and search techniques during the data collection.
Phase-4: Structure of the review
Check the organization and presentation of the review paper
concerning the problem formulation and research questioning.
Do the methods used for the literature review sufficiently
described the problem? Can the study be simulated?
Check the results of the review report are clearly stated or not.
Is the manuscript representing the findings of the literature
review as a transparent and valuable input to the subject?
Check the questions and whether further enhancement of the
research is included or not.
Phase-2: Significance:
Check the search process for this type of technical review.
Do the field and experiment-oriented surveys properly define or
not?
Check the transparency process of insertion and elimination of
articles.
Maintain the research quality by properly selecting the methods and objectives.
Check the significance and effectiveness of the final sample concerning the problem formulation.
By considering the above questionaries, the review paper is
designed and the complete flowchart related to the manuscript
making is illustrated in Fig. 1. Looking to the questionaries, six
important steps such as data identification, survey & screening, eligibility, final scrutiny, and data collection are followed to construct
a standard review paper. In Step-1 (Data identification), different
search engines are used to collect the related peer-reviewed journal papers. Primarily, from the valid resources 583 papers
(n = 583), and from other sources 75 papers (n = 75) are considered. From a total of 613 papers, the irrelevant duplicate files of
Phase-3: Final scrutiny
Check the appropriateness and significance of data collection
for developing the review paper.
Does the procedure for data collection is correctly described?
Fig. 1. Flow chart of research methodology.
141
B. Sahoo, M.M. Alhaider and P.K. Rout
Renewable Energy Focus 44 (2023) 139–173
Fig. 2. Complete microgrid structure with active power filter (APF) capability.
around 163 papers are excluded in Step-2 (Survey and screening
process). In Step-3 (Eligibility), with complete full-text reading, a
total of 358 papers (n = 358) are selected for review by eliminating
92 papers (n = 92) for reasons such as unsuitability, variable data
contained, and unstructured representation. In Step-4 (Final Scrutiny), from 358 papers, selective papers around 295 papers
(n = 295) in the related areas as comparative review, active and
passive filters, shunt active filter controller and microgrid controllers are selected for the making of the review paper. By considering the above areas, the structure of the review manuscript is
decided and clearly stated in the presented flow chart. In addition
to that, the overall structure of the APF-based microgrid system is
illustrated in Fig. 2 by using different renewable energy and battery sources.
Table 1
Harmonic current and TDD evaluation.
Is/Il
H<11
11 6 Hh17
17 6 Hh23
23 6 Hh25
TDD %
<20
20-50
50-100
100-1000
>1000
4
7
10
12
15
2
3.5
4.5
5.5
7.0
1.5
2.5
4
5
6
0.6
1
1.5
2
2.5
5
8
12
15
20
Table 2
Voltage distortion limit.
3. Standards
In this section, the necessary standards related to PQ, grid connection, microgrid, grid connection, and power factor are presented. In Table 3, grid connection and microgrid standards are
presented. In Table 4, the above standards are presented according
to the installation and trip time. Similarly, in Table 5, the standardization related to the power factor is presented. In addition to that,
a comparative standardization table related to AC and DC microgrids is presented in Table 6.
Voltage range
Fundamental frequency
THD %
V<69kV
69kV 6 Vh160kV
V P 160kV
3%
1.5 % %
1%
5%
2.5 %
1.5 %
cess. Recently, most of the related work by IEEE in the harmonic
standard amendment has shifted to modify the standards 5191992.
3.1.1. IEEE 519-1992xxx
This standard recommends practices and necessities related to
harmonic problems in electric power systems. It establishes different limits on non-linear currents and voltages at the point of common coupling (PCC) [215].
3.1. PQ standards
This is a universal issue and regulation of standards is an
endless task. It takes more time to push changes through the pro142
YEAR
STANDARD
COUNTRY
HEADING
B. Sahoo, M.M. Alhaider and P.K. Rout
Table 3
Grid connection and Microgrid standards for integration [212–220].
APPLICATION
2000
IEEE_929
International
Suggested practices for solar integrated systems
2005
UL 1741
USA
Inverter, converter, controller, and integration standard for distributed system
2006
GB-T 20046
PRC
Solar-PV systems. Characteristics for grid integration
2008
BDEW
Germany
Generating plant coupled to MV and energy stations coupled to LV network
2011
VDE-AR-N 41052
Germany
Distribution system: Sets guidelines for grid integration and parallel operation for LV network
2011
IEC/IEEE/PAS 63547
International
DES integration with the utility grid
2012
G83
U. K
Parallel connection of 16A/phase-based embedded generators for LV DES
2012
GB-T 199644
PRC
Monitor the technical necessity for PV integration to the utility
2013
UNE 206007-1
Spain
Monitor grid integration standards, Part-1: Grid-integrated inverters
2013
UNE/EN/IEC 62109
International
Safety measure for converter in PV applications: Part-2: Particularly for inverter
2013
EN 50438
Europe
Sets guidelines for micro generation plants and parallelly connected to LV distribution system
2014
G59
U.K.
Sets guidelines for licensed distribution network operators for grid integration
2014
Gazette of India Part III-Sec.4
India
Recommends practices for integration of DESs
2015
AS 47772
AUS/NZ
Grid integration through inverters, Part-2 Inverter Necessity
2016
AS 4777-1
AUS/NZ
Grid integration through inverters, Part-1: the necessity of installation
2017
IEC 62898-1
International
Microgrid- Part-1: Sets guidelines for microgrid projects and specifications
2017
IEEE P2030.8
International
Verify and monitor the microgrid controller
2018
IEEE 1547
International
Recommends practices for DES-based grid integration
2018
ARCONEL 003
Ecuador
Solar-PV microgeneration for islanded conditions
2018
IEC 62898-2
International
Microgrid-Part-2: Operational guideline
2019
CLC/TS 50549-1
Europe
Parallel connection of distribution system- Part-1: LV connection
2019
CEI 0-21
Italy
Recommends technical guidelines for the connection of active and passive users
2020
IEC 62898-3-1
International
Microgrid-Part-3: control and protection technical requirement
Note: DES: Distributed energy sources, LV-Low voltage, HV-High voltage, MV-Medium voltage, PV-Photo voltaic system, AUS-Australia, NZ-News land
Solar 6 10kW
Grid integration through distributed energy sources
Solar 6 10kVA at LV distribution
Generating plants integrated for LV and MV
Generating station 6 10kVA for LV network
DES 6 10MVA
Small generations 6 16A/phase for 230/400V network
Solar integration for LV, MV, and HV
Inverter integration to the local distribution system
Solar 6 1000V
Small generations 6 16A/phase for 230/400V network
Generating station 6 17kW/phase or 6 50kW/3-phase
DESs integrated with the utility system
Inverters integrated for LV system
Inverters 6 200kVA at LV applications
AC grid with load and DES with LV or MV application
Testing for different functions of MG controller
DES operation at primary and secondary voltage
PV 6 100kW at LV/MV, 6 300kW for residential use
AC-grid with loads and DES connected at LV and MV
Generation plants including Type-B at LV network
Active and passive user 6 1kV (LV)
AC-grid with loads and DES connected at LV and MV
143
Renewable Energy Focus 44 (2023) 139–173
The prescribed limits are projected to
a. Guaranteed clean power transmission to the end users.
b. Ensure protection from overheating, increase harmonics,
and additional voltage stress.
c. The harmonic voltage limit lies between 0–3 % for each harmonic component and 0–5 % for THD.
d. Harmonic limits are set at the PCC and metering point of the
grid.
IEEE 519 for current nonlinearity:
In the power generation sector, the distortion limits can be
obtained by Is/Il<20. where Isc is the short circuit current and Il is
15 to 25 minutes of the load current at the maximum fundamental
frequency. TDD is defined as total demand-side distortion. The distortion limit is illustrated in Table 1.
IEEE 519 for voltage nonlinearity:
Depending on the network and functionality, voltage distortion
limits decide the quality of the power. Voltage distortion limits for
different applications are indicated in Table 2.
3.1.2. IEC 61000xxx
IEC 61000 is broadly divided into two sub-standards as IEC
61000-3-2 (1995-03) and IEC 61000-3-4 (1998-10) respectively.
The details are illustrated below.
IEC 61000-3-2:
This standard sets limits for distorted current signals and is
valid for electrical and electronic instruments having an input current up to 16A per phase. These instruments are needed to be integrated for low-voltage distribution system applications. The
assessments as per the standard are known as type tests [216–
218].
IEC 61000-3-4:
This standard sets a limit for electrical and electronic instruments having a greater 16A current per phase. These instruments
are applicable for low-voltage distribution networks such as.
Voltage rating up to 240 V, 1U, two or three wire application
Voltage rating up to 600 V, 3U, three or four-wire application
The rated frequency at 50 Hz–60 Hz.
3.1.3. IEEE 141-1993xxx
Standard is recommended for power distribution at industries
sectors. In this standard, a detailed explanation regarding the project, structure, working rules, implementation, maintenance, and
flexibility to disturbances are presented.
3.1.4. IEEE 142-1991xxx
This is recommended to set grounding conditions at industries
and commercial system applications. Detailed analyses regarding
grounding problems and policies are discussed. In addition to that,
a specific chapter is also provided for grounding modern
equipment.
3.1.5. IEEE 446-1987xxx
Standard is recommended for alternative and emergency power
supply for industries and commercial system applications. It offers
the facility to manufacturers, operators, and installers with proper
guidelines and rules for guaranteeing better PQ conditions.
3.1.6. IEEE 493-1997xxx
This recommends practices for the development of reliable
power industries and commercial applications. The reliability analysis of the plant is achieved by probability techniques, cost evaluation, fundamental power extraction, power outage data, and
monitoring equipment robustness. [218–219]
STANDARD
Role
UV Threshold-1
Rated Voltage
OV Threshold-1
OV Threshold-2
UF Threshold-2
UF Threshold-1
Rated
OF Threshold-1
Frequency
OF Threshold-2
Installation
Trip time
UL 1741
Installation
Trip time
GB-T 20046
Installation
Trip time
BDEW
Installation
Trip time
VDE-AR-N 4105
Installation
Trip time
IEC/IEEE/PAS 63547 6 30kW Installation
Trip time
IEC/IEEE/PAS 63547 i 30kW
Installation
Trip time
G83
Installation
Trip time
GB-T 19964
Installation
Trip time
UNE/EN/IEC 62109
Installation
Trip time
EN 50438
Installation
Trip time
G 59
Installation
Trip time
Gazette of India Part III-Sec.4 Installation
Trip time
AS4777.2
Installation
50 %
0.1 s
NA
NA
50 %
0.1 s
55 %
0.3 s
20 %
0.1 s
50 %
0.16 s
NA
NA
20 %
0.5 s
NA
NA
NA
NA
NA
NA
22 %
0.48 s
NA
NA
NA
120V
NA
NA
NA
220V
NA
230V
NA
230V
NA
120600V
NA
NA
NA
230V
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
2 Hz
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
+0.5 Hz
0s
NA
NA
NA
NA
37 %
0.03 s
20 %
0.16 s
20 %
0.16 s
+30 %
NA
+15 %
0.2 s
NA
NA
NA
NA
NA
3.5 Hz
0.16 s
3.5 Hz
0.16 s
2.5 Hz
NA
2.5 Hz
0.1 s4 s
NA
NA
0.7 Hz
0.1 s
0.7 Hz
0.1 s
0.5 Hz
2s
2.5 Hz
0.1 s
2.5 Hz
0.1 s
0.7 Hz
0.16 s
0.2 to 3 Hz
0.16 to 300 s
NA
NA
NA
NA
3 Hz
NA
2.5 Hz
0.5 s
0.5 Hz
600 s
2.5 Hz
0.2 s
AU S (3 Hz)
NZ (3 Hz)
2s
0.7 Hz
0.1 s
1.5 Hz
300 s
1.5 Hz
300 s
1.5 Hz
NA
0.5 Hz
0.1
0.5 Hz
NA
60 Hz
NA
60 Hz
NA
50 Hz
NA
50 Hz
NA
50 Hz
NA
60 Hz
NA
NA
NA
NA
NA
NA
NA
50 Hz
NA
50 Hz
NA
50 Hz
NA
50 Hz
NA
50 Hz
NA
50 %
0.1 s
55 %
0.16 s
55 %
0.16 s
NA
NA
60 %
0.2 s
NA
NA
+10 %
2s
NA
NA
+10 %
2s
+20 %
0.1 s
+10 %
0.1 s
+10 %
1s
NA
NA
+14 %
1s
+10 %
2s
NA
NA
+10 %
0.2 s
+17 %
0.98 s
+10 %
2s
AU S(+13 %)
NZ (+9 %)
2s
+10 %
2s
+10 %
2s
+10 %
2s
+20 %
NA
+10 %
603 s
+10 %
1
+37 %
0.03 s
NA
NA
+37 %
2–60 s
NA
NA
+15 %
0.1 s
+20 %
0.16 s
NA
NA
+19 %
0.5 s
+20 %
0.5 s
NA
NA
+15 %
3s
+21 %
0.48 s
NA
NA
NA
Trip time
Installation
Trip time
Installation
Trip time
Installation
Trip time
Installation
Trip time
Installation
Trip time
Installation
Trip time
12 %
2s
NA
NA
12 %
2s
20 %
1.5 s–2.4 s
20 %
0.1 s
12 %
2s
NA
NA
13 %
2.5 s
10 %
NA
NA
NA
15 %
1.5 s
18 %
2.48 s
20 %
2s
AU S (20 %)
NZ (22 %)
2s
12 %
2s
30 %
2s
30 %
2s
15 %
NA
15 %
0.4 s
10 %
1s
IEEE929
144
IEEE 1547 Cat-1
IEEE 1547 Cat-2
IEEE 1547
Cat-3
CLC/TS 50549-1
CEI 0-21
ARCONEL 003
OV-Over voltage, OF-Over frequency, UV-Under voltage, UF-Under frequency.
220V
NA
NA
NA
230V
NA
230V
NA
230V
NA
AU S(230V)NZ (230V)
NA
NA
NA
120600V
NA
120600V
NA
61000V
NA
230V
NA
NA
NA
60 Hz
NA
60 Hz
NA
60 Hz
NA
50 Hz
NA
50 Hz
NA
60 Hz
NA
+0.5 Hz
0.1 s
+0.5 Hz
0.1 s
+0.5 Hz
2s
+2 HZ
0.1 s
+1.5 HZ
0.1 s
0.5 HZ
0.16 s
0.5 HZ
0.16 s
NA
NA
NA
NA
+2 Hz
NA
+2 Hz
0.5 s
+0.2 Hz
120 s
+0.5 Hz
0.2 s
AU S (+2 Hz)
NZ (+2 Hz)
2s
+0.5 Hz
0.1 s
+1.2 Hz
300 s
+1.2 Hz
300 s
+1.5 Hz
NA
0.2 Hz
0.1 s
+0.5 Hz
NA
NA
NA
NA
+2 Hz
0.16 s
+2 Hz
0.16 s
NA
NA
+1.5 Hz
0.1 s
NA
NA
Renewable Energy Focus 44 (2023) 139–173
UV Threshold-2
B. Sahoo, M.M. Alhaider and P.K. Rout
Table 4
Grid connection and Microgrid standards according to installation rate and trip time [214–218].
Renewable Energy Focus 44 (2023) 139–173
B. Sahoo, M.M. Alhaider and P.K. Rout
Table 5
Standardization for power factor (PF) regulation [213–214].
STANDARD
CONDITION AT RATED ‘P’ AND
‘S’
STANDARD OPERATING
CONDITION
Leading PF
Lagging PF
IEEE_929
GB-T 20046
BDEW
VDE-AR-N 41052
NA
NA
NA
613.85kVA
>13.85kVA
NA
NA
NA
NA
NA
Close to load
Output >10 % of Rated value
6 50 % of its nominal power
Any real power
NA
NA
Rated power
<Rated real power
P 20% of its nominal power
<20 % of its nominal power
Rated power
Rated power
0.85
NA
0.95
0.95
0.9
0.95
0.95
0.9
Q/nominal power 6 0.1
0.95
0.85
0.85
0.9
0.95
0.95
0.9
0.95
0.95
0.9
Q/nominal power 6 0.1
0.95
0.95
Faraway from load
Rated power
0.9
0.95
NA
NA
NA
25 %–100 % of O/P current
P 20% of its nominal power
<20 % of its nominal power
NA
NA
NA
NA
0.95
Q/nominal power 6
0.44
Q/nominal power 6
0.44
0.9
0.9
0.95
Q/nominal power 6
0.25
Q/nominal power 6
0.44
0.9
0.9
G83
GB-T 199644
EN 50438
G59
Gazette of India Part III-Sec.4 on/after
2004
Gazette of India Part III-Sec.4 on/after
2014
AS 47772
IEEE 1547
CLC/TS 50549-1
CEI 0-21
Table 6
Comparative standardization of power quality issues study in both AC and DC microgrid [212–215].
PQ Issues
AC
DC
IEC 61000-3-4 and IEC61000-3-2
IEEE 159
Frequency Fluctuation:
Transient:
1. Surge/Impulse
2. Oscillatory
Short Fluctuation:
1. Sag
2. Swell
3. Interruption
Long Fluctuation:
Under voltage
Over voltage
Interruption
Imbalance:
1. Voltage
2. Current
Distorted Waveform:
1. AC offset
2. DC offset
3. Harmonics
4. Inter-harmonics
5. Noise
6. Notching
Voltage fluctuations:
A
NA
Data
Ranges
Data
Ranges
A -AC, NA-DC
A-AC, NA-DC
A-AC, NA-DC
A-AC, NA-DC
A
A
A
A
A -AC, A -DC
*
A -AC, A -DC
*
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A
A
A
A
A
A
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A
A
A
A
A
A
NA-AC, NA-DC
NA-AC, NA-DC
A -AC, A -DC
NA -AC, NA-DC
NA -AC, NA-DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A
A
A
A
MR
MR
MR
MR
MR
MR
MR
MR
NA
A
A
A
A
A
A
A
NA
NA
A
A
A
A
NA-AC, NA-DC
A -AC, NA-DC
A -AC, NA-DC
A -AC, A -DC
NA-AC, NA-DC
NA-AC, NA-DC
A -AC, A -DC
NA-AC, NA-DC
A -AC, NA-DC
A -AC, NA-DC
A -AC, A -DC
NA-AC, NA-DC
NA-AC, NA-DC
MR
NA-AC, NA-DC
A -AC, NA-DC
A -AC, NA-DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
NA-AC, NA-DC
A -AC, NA-DC
A -AC, NA-DC
A -AC, A -DC
A -AC, A -DC
A -AC, A -DC
MR
Note A: Applicable, NA: Not Applicable, MR: Modification Required, AC: AC Microgrid, DC: Microgrid.
identifications of different PQ terminologies, sets PQ definitions,
the impact of PQ problems on utilities and equipment, and measuring electromagnetic phenomena [217–221].
3.1.7. IEEE 1100-1999xxx
This recommends practices such as strategy, implementation,
and maintenance for power supply and grounding of sensitive load
applications [219–221].
3.1.9. IEEE 1250-1995xxx
Sets guidelines for equipment sensitivity to momentary voltage
fluctuations. The standard is used to create awareness for the new
sensitive load user from surges, fluctuations, faults, and reclosing
times that occur in the distribution system. Momentary voltage
variations have occurred in ac power distribution and utilization
sectors. In this standard, the effects and compensation standards
towards compensations are described [219].
3.1.8. IEEE 1159-1995xxx
This standard recommends practices to measure the PQ issues.
In power industries, many different types of power quality (PQ)
monitoring devices are present. Therefore, to maintain uniqueness
and easier identification, there is a necessity to standardize the
monitoring unit for both industries and commercial applications.
Standard includes monitoring units for AC power systems,
145
B. Sahoo, M.M. Alhaider and P.K. Rout
Renewable Energy Focus 44 (2023) 139–173
3.1.10. IEEE 1346-1998xxx
This standard recommends practices to monitor the voltage sag
compatibility among the equipment and power system.
appropriate active current (I d ) component for charging the SHAF.
The computed current is the amount of dc-current required to be
haggard by the SHAF for facilitating the switching operation by
which the system can maintain its dc-link voltage of the capacitor
at its desired value.
c) CRT-based controller:
In this control technique, the output responses of the NET and
DC-VCT-based controller are considered to extract appropriate
switching pulses ‘P’ for the inverter operation, by which the inverter behaves like a SHAF. The CRT-based controller is designed by
considering a space vector pulse width modulation (SVPWM) technique for appropriate pulse generation and a current regulation
loop is required to guarantee that the generated injected current
(Iin ) is properly synchronized with the reference current (Ig ).
d) SCT-based controller:
The SCT-based control approach is designed based on the
phase-locked loop (PLL) approach. In this control technique, the
controller takes the grid voltage as an input parameter and extracts
a synchronization angle (hs ), so that the injected current generated
by the SHAF is easily synchronized with the grid voltage. It also
ensures that there is no necessity for explicit SCT for SHAF controller operation.
Other related important factors for the SHAF operation are discussed below.
e) Voltage source converter (VSC):
As illustrated in Fig. 3, this is a power electronic componentbased device, which is used to generate an appropriate injection
current for reducing the power system’s non-linearity. The dc
capacitor-based energy storage device is used to reduce the active
power fluctuations that occurred during the dynamic study of
SHAF operation. The VSC modeling also incorporates a filter inductor by which it mitigates the higher ripples present in the injection
current. Recently, multi-level voltage inverters are also gaining
interest due to their significant contribution such as improved
voltage levels, better power quality, reduced harmonic, lesser
switching components, and reduced size.
f) Non-linear load:
This type of load injects harmonic to the linear/stable power
system through PCC. The application of these types of loads is gradually increasing day by day and a few of them are illustrated as
switched power supply, industrial application, furnace, speed drivers, converters, battery chargers, etc. These types of practical
loads generate higher harmonics and an increase in reactive power
components. However, during the Simulink model design, an
uncontrolled RL, RC, and R-based bridge controller is used as it generates excess harmonics [15,23,24].
3.1.11. IEC 61000-2-8xxx
A new standard is formed to discard the conflicting methods to
characterize the system performance. The name of the standard is
Environment- voltage dips and short interruption.
4. Design and working principle of SHAF
The complete SHAF-based system modeling with its important
four control strategies are illustrated in Fig. 3. In the complete system modeling, the non-linear/sensitive load is directly connected
to the grid and the SHAF is connected to the point of common coupling (PCC) in between the grid and non-linear load. The complete
working principle of SHAF is majorly dependent upon two factors
such as voltage/current source inverter/converter and control
strategy [22]. Specifically, the important four control techniques
are known as the non-linear extraction technique (NET), dcvoltage control technique (DC-VCT), current regulation technique
(CRT), and synchronizer control technique respectively. Each of
the control operations is discussed below.
a) NET-based controller:
In this control technique, by considering the non-linear load
current signal (Il ) from the high-frequency load, the NET-based
control design is started. After gathering sufficient knowledge
about the harmonic percentage of current, it is passed through
the linear current controllers for isolating the high-frequency component and extracting the fundamental current component. Lastly,
by using the fundamental current component, the reference current (Ig ) for the SHAF operation is developed. Meanwhile, the main
aim of the NET-based controller is to develop the reference current
generation and otherwise known as the reference current extraction technique.
b) DC-VCT-based controller:
In this control technique, the actual dc voltage (V dc ) of the SHAF
is compared with the reference dc voltage (V dc ). The compared
result (Ide ) is passed through a linear controller, to compute the
4.1. SHAF design
As illustrated in Fig. 3, the mathematical SHAF modeling is presented. At first assume that the SHAF is not connected to the system model, the undertaken system current flow equation is
mathematically represented as.
Ig ¼ Il ¼ Ifu þ In
ð1Þ
where Ig is the grid current, Il is the load current, Ifu is the fundamental current, and In is the non-linear current component generated by the non-linear loads. Due to the absence of SHAF, the grid
current is equal to the load current, which indicates that the grid
current is distorted and changes its phase. However, by connecting
the SHAF to the PCC of the undertaken system as illustrated in
Fig. 3, two supplementary currents such as SHAF injection current
(Iin ) and dc-link current (Idc ) are flowing in the system. Iin is used to
mitigate the nonlinear current generated by the sensitive load and
Idc is used to compensate the switching losses of the SHAF and to
Fig. 3. Overall SHAF design with important controller applications.
146
Renewable Energy Focus 44 (2023) 139–173
B. Sahoo, M.M. Alhaider and P.K. Rout
The related instantaneous non-linear current (Il ðtÞ) equation is
presented in terms of fundamental and non-linear components as.
regulate the dc-link voltage of the inverter. Therefore, after using
the SHAF in the design system, the new current flow equation is
mathematically represented as.
Ig ¼ Ifu þ In Iin þ Idc
Il ðtÞ ¼
ð2Þ
ð5Þ
nonlinear
Fundamental
By using Eq. (4) and Eq. (5), the instantaneous non-linear load
power (Pl ðtÞ) can be computed as.
Pl ðtÞ ¼ V g ðtÞ þ Il ðtÞ
activ e powerPa ðtÞ
reactiv e power P r ðtÞ
zfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl}|fflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl{ zfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl}|fflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl{
2
¼ V a Il sin xt cos u þ V a I1 sin xt cos xt sin u1
ð3Þ
After computing an appropriate current flow equation, the
related power flow equations of the system are computed as follows. The instantaneous grid voltage (V g ðtÞ) of the undertaken system is presented as.
V g ðtÞ ¼ V a sin xt
Ik sin ðkxt þ uk Þ
zfflfflfflfflfflfflfflfflfflfflfflfflffl}|fflfflfflfflfflfflfflfflfflfflfflfflffl{ zfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl}|fflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl{
X1
I2 sin ðkxt þ uk Þ
¼ I1 sin ðxt þ u1 Þ þ
k¼2
From Eq. (2), it is visualized that the main role of SHAF is to
eliminate the nonlinear current by injecting the appropriate injection current and making the grid current sinusoidal current. In this
way, the SHAF can regain the sinusoidal characteristics of the grid
and in phase with the grid voltage. After eliminating the non-linear
current, Eq. (2) is simplified as.
Ig ¼ Ifu þ Idc
1
P
k¼1
ð6Þ
nonlinear powerPn ðtÞ
zfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl}|fflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl{
X1
þ V a sin xt k¼2 Ik sin ðkxt þ uk Þ
ð4Þ
Table 7
Filter characterization with respect to voltage and current source-based non-linear load [198–200,207–222].
(continued on next page)
147
B. Sahoo, M.M. Alhaider and P.K. Rout
Renewable Energy Focus 44 (2023) 139–173
Table 7 (continued)
148
Renewable Energy Focus 44 (2023) 139–173
B. Sahoo, M.M. Alhaider and P.K. Rout
Table 7 (continued)
(continued on next page)
149
B. Sahoo, M.M. Alhaider and P.K. Rout
Renewable Energy Focus 44 (2023) 139–173
Table 7 (continued)
where Ig : grid current, V gh : grid harmonic voltage, Ic : compensating current, In : non-linear load current, Lg : grid inductance, Ll : load inductance, C l : capacitive load, V C :
compensating voltage, Z f : filter impedance, If : filter current, V n : non-linear voltage, X p : parallel reactance, X s : series reactance, X c : capacitive reactance.
respectively. From the above-presented models, a few of them are
novel and show excellent characteristics of non-linear loads, while
others are well-known filters and successfully applied for real-time
applications. The overall comparative studies of APF are illustrated
in Table 8. However, looking at the size, complexity, and cost,
power engineers are preferably selecting SHAFs for non-linear load
applications [27]. As per the suggestion, if the system is operated
only by using SHAF, then there is a necessity to find optimal control solutions for the SHAF operation. The related different control
solutions and their applications are discussed in the following sections. For the Microgrid condition, the use of a passive filter creates
a power factor issue by providing a leading power factor if the generator is close to the load station. The generator can only be capable to handle a limited amount of leading kVAr before voltage
disturbance and/or it will damage [223]. From the literature, it is
found that if the total capacity of the passive filter does not exceed
20 % of the generator’s kVA rating, then the generator can handle it.
Otherwise, it will create voltage regulation and control problems.
As a solution, HPS centurion P passive harmonic is always less than
20 % of its kVA rating to compatible with generator fed system. Due
to small capacitance, it may not be needed for light load conditions.
To solve the problem, the developers offer a contactor to avoid the
switched capacitor in the filter for light load conditions to prevent
From the active power component as illustrated in Eq. (6), the
respective three-phase reference grid current components (Iga ðtÞ,
Igb ðtÞ, and Igc ðtÞ) are computed as.
Iga ðtÞ ¼
Pa ðtÞ
¼ I1 cos u1 sin xt ¼ Im sin xt
V g ðtÞ
Igb ðtÞ ¼ Im sinðxt 120 Þ
ð7Þ
ð8Þ
Igc ðtÞ ¼ Im sinðxt þ 120 Þ
ð9Þ
The maximum current component (Im ) is regulated by controlling the dc-link voltage of the SHAF through a PI or other linear
controllers.
4.2. Detailed working principles of parallel/series filters for current and
voltage source non-linear load applications
4.2.1. Findings
In Table 7, all-around 22 different power filter combinations are
presented, which are used for harmonic mitigation [25–26]. The
harmonics are generated from two different load models such as
current source and voltage source non-linear load (CSNL and VSNL)
Table 8
Overall comparative studies of active power filter (APF) topologies.
Major Factor
APF topology
SHAF (Shunt Active Filter) [85–95]
Power Range:
Small scale
Medium scale
Large scale
Inverter Efficiency:
Small scale
Medium scale
Large scale
Control loop:
APF operation:
Non-linear load:
Improved factors:
Switches:
Current distortion:
Reactive support:
Load management:
Neutral component:
Voltage distortion:
Improved regulation:
Balanced voltage:
Voltage flicker:
Sag and swell:
SEAF (Series Active Filter) [201–206]
HAF (Hybrid Active Filter) [18,43]
<400W (below 100kVA)
<400kW (3u systems between 100kVA to 10 MVA)
<400kW (above 10MVA)
Lowest (maximum to 90 %)
High (maximum to 90 %)
Highest (maximum to 90 %)
Simple control loop in SVPWM-VSI
Current operated converter (COI)
Rectifier with inductive load
Reactive power support
Current Compensation
IGBTs, MOSFETs, Thyristors
++
+++
+
++
NA
+
NA
+++
+
No control loop in SVPWM-VSI
Voltage operated converter (VOC)
Rectifier with capacitive load
Regulation of AC voltage
Provide voltage support
IGBTs, MOSFETs, Thyristors
NA
NA
NA
NA
+++
+++
+++
++
+++
+ indicated as per their capability, NA-Not Applicable.
150
Simple/No control loop in SVPWM-VSI
Both in COI and VOC
Rectifier with inductive load
Harmonic regulation
Isolation and damping support
IGBTs, MOSFETs, Thyristors
+++
++
NA
+
++
++
++
NA
++
Renewable Energy Focus 44 (2023) 139–173
B. Sahoo, M.M. Alhaider and P.K. Rout
Merits of SHAF over SEAF:
the system from leading power factor [224]. However, switching
out the capacitor means the system is no longer used as a harmonic
filter.
Similarly, in Utility power distribution, the leading power factor
will result in higher losses and a rise in voltage. In utility stations,
under light load conditions, the selection of a passive filter can
cause a leading or negative power factor as this integrates capacitance and impacts the power factor at the utility connection. In
addition to that, the utility also charges an additional kW hour
used plus the demand cost.
Demand cost depends upon peak power [225]. At lower power
factors and peak load conditions, the demand cost is more. However, at low power factor and light load conditions, the demand
cost is low.
Therefore, to resolve the above complexity related to the power
factor issue, recently, active power filters are preferred for realmicrogrid system applications. The merits and demerits of SHAF
application over SEAF are presented as follows.
a)
b)
c)
d)
e)
f)
g)
h)
i)
j)
k)
l)
Requires lesser component.
Operated at the lower switching frequency.
Light-weighted.
Improved power factor
Independent upon system impedance and load shading
condition.
During harmonic mitigation, the resonance problem does
not appear.
Capacitor aging is also avoided.
Necessitates active switching components.
Only a single filter is enough capable of harmonic
elimination.
Power factor correction is possible.
Facilitates harmonic mitigation with/without reactive power
support.
Used for flicker reduction in Arc furnace
Fig. 26. Detailed classifications of APFs.
151
B. Sahoo, M.M. Alhaider and P.K. Rout
Renewable Energy Focus 44 (2023) 139–173
Table 9
SHAF overall control technique.
m) Offers excellent voltage
applications.
n) Cheaper solutions.
regulation
during
d) Comparatively high-cost power electronic devices are
required.
real-time
5. SHAF control technique
Demerits of SHAF over SEAF:
In Fig. 26, the detailed classifications of APF are done as per the
power ratings and connection structure. The performance of the
SHAF is dependent upon the appropriate reference current generation technique. In this section, four important reference current
generation algorithms such as NET, DC-VCT, CRT, and SCT are presented during non-linear load application conditions. The detailed
overall SHAF control technique is illustrated in Table 9.
a) High-frequency switching operations are required specifically for the zero-crossing operation.
b) During voltage source inverter (VSI) operation, high-rating
capacitors are required.
c) Regulation of dc-link voltage at its rated value is difficult
during transient conditions.
152
Renewable Energy Focus 44 (2023) 139–173
B. Sahoo, M.M. Alhaider and P.K. Rout
nents (Ild;h , and Ilq;h ). Therefore, through a low pass filter (LPF),
the Ild;f , and Ilq;f components are cancelled and only the harmonic
DQ current component is extracted for SHAF operation [31–32].
However, the dc-link voltage regulation is required to reduce the
switching regulation. Therefore, in the SRFM method, by comparing the reference voltage and actual dc-link voltage, the appropriate real current component is computed. The sum of the direct
fundamental current and appropriate real current component gives
an actual idea about the direct component. After evaluating the
actual harmonic information regarding the DQ0 current component, it is passed through inverse park transformation for reference
current generation. The related mathematical representation of the
SRFM is presented below.
5.1. Nonlinearity extraction technique (NET)
The extraction of non-linear current from the sensitive loadbased power system to produce an appropriate current component
(Ig ) by using the NET-based control method is the first and most
prominent method for developing the SHAF control system [28–
29]. In the SHAF control design, the NET method is the first control
method by which the undertaken system can generate an appropriate reference current. For harmonic elimination, the accurate
reference current generation is important for the estimation of
injection current. Mostly, the above technique uses signal
processing-based functions and is specifically known as a nonlinear identifier. The non-linear identifier receives the harmonic
current signals and produces the reference current signal by properly isolating the harmonic signals from the fundamental signals.
So far, for the above purpose, different extraction techniques and
related performances have been discussed in the literature. Commonly, the NET algorithm is divided into four sub-sections as
time-domain approach (TDA), the frequency domain approach
(FDA), the learning technique approach (LTA), and other related
approaches (ORA).
5.1.1 Time-domain method (TDM)
The working principle of this method is dependent upon the
change of the current amplitude signal with time. In TDM, the system responds with an input signal is represented as a function of
time. Due to the proposed approach, the time response analysis
of the proposed system can be computed if the nature of the input
signal and appropriate mathematical modeling of the system are
known. The TDM is further classified into two methods as synchronous reference frame-based method (SRFM) and the instantaneous power theory method (IPTM).
a) Synchronous reference frame method (SRFM):
Looking at the real-time SHAF control operation, the SRFMbased control method is applicable for both steady-state and
transient conditions. The complete control diagram of the SRFM
is illustrated in Fig. 27. The SRF method is well known as the DQcontrol method. In this method, the three-phase non-linear load
current signal (Il;abc ) is sensed and converted to a rotating DQ0
component (Il;dq0 ) through Park transformation [30].
However, during the control operation, only DQ components
are used for the reference current extraction process. Here, the
D-axis component (Il;d ) is used for active power and power factor
regulation of the system. Similarly, the Q-axis component (Il;q ) is
used to provide reactive power support. As illustrated in Fig. 24,
the phase-locked loop (PLL) is used to synchronize the obtained
signals at the point of PCC and extract the phase information accurately. After the DQ0 transformation, the DQ current component
contains both fundamental (Ild;f , and Ilq;f ) and harmonic compo-
V dc;e ðnÞ ¼ V dc;e ðn 1Þ þ K p fIdc;e ðnÞ Idce ðn 1Þg þ K i Idc;e ðnÞ
ð10Þ
where K p and K i are the proportional and integral gain, V dc;e is
the dc-link voltage error, Idc;e is the dc-link current error and ‘n’
is the number of intervals.
Merits of SRFM:
Because of the dc-nature of the fundamental current component, the variation in the phase sequence cannot affect the reference output signal
The mathematical modeling and control strategy is easier for
implementation, reduced cost, and lesser computational burden. The transformation model is quite easier for DSP and
FPGA-based control implementation.
SRFM also offers a faster response
Demerits of SRFM:
Only applicable for the balanced source voltage
b) Instantaneous power theory method (IPTM):
The IPTM-based non-linearity extraction technique is developed through a combination of mathematical computation of
instantaneous power. The complete control is designed on a ab reference frame through the Clarke transformation. The developed
controller is capable to mitigate the instantaneous reactive power
demand for a three-phase microgrid system without requiring an
additional energy storage device. The controller is valid for both
balanced/unbalanced systems, non-linear load application, with/
without neutral, and zero sequences current component. IPTM is
also valid for both steady-state and dynamic state conditions. During the mathematical computation technique, firstly, the grid voltage and load currents are transformed to abc ab frame through
Fig. 27. SRFM-based control diagram.
Fig. 28. IPTM-based control diagram.
153
B. Sahoo, M.M. Alhaider and P.K. Rout
Renewable Energy Focus 44 (2023) 139–173
Because of a definite bit span arithmetic process and fast application, the computational error is decreased significantly.
Offers excellent steady-state performance.
the Clarke transformation method. The complete control design is
illustrated in Fig. 28.
Ih;a
Ih;b
¼ V2
1
2
g;a þV g;b
þ V2
1
2
g;a þV g;b
V g;a
V g;b
Ph
V g;b V g;a
0
V g;a V g;b
0
V g;b V g;a Q h
Demerits of FFA:
ð11Þ
Require excess time for the computation due to the fixed window length.
Not applicable for harmonic signal
During multi-level inverter applications, capacitor voltage balancing is difficult.
As illustrated in Fig. 28, the ab current components are used for
instantaneous active, reactive, and zero sequence power computation. To minimize the circulating current, the zero-sequence power
component is used for the control design [33–34]. By using the ab
current and voltage component, the combination of fundamental
(P f and Q f ) and harmonic (Ph and Q h ) instantaneous active and
reactive power components is computed.
As illustrated in Fig. 28, the obtained fundamental and harmonic active component is passed through a low pass filter (LPF)
to eliminate the harmonic component from the total instantaneous
power. In this approach, the dc-link voltage regulation is also
required to avoid any switching losses. After getting the dc power
component (Pdc ), the total harmonic instantaneous power (Ph ) is
computed. By using Eq. (11), the harmonic ab current component
is computed. Through inverse Clark transformation, the harmonic
ab current component is converted to abc current component.
Merits of IPTM:
b) Recursive Fourier analysis (RFA):
The performance of the RFA is improved significantly because of
the sample-by-sample up-gradation with excellent time-frequency
coordination. As compared to other low-pass filter applications,
the RFA-based filter topologies are applied for improving the transient system performance. In RFA, a motionable and fixed frame
discreet filter is used to extract the active (Ia) and reactive (Ir) current components from the fundamental current, and the related
explanation is presented in Eq. (12) and Eq. (13). By considering
the
kth
sample,
a
window
having
M
values
fXðk M þ 1Þ; Xðk M þ 2Þ; ::::::XðkÞg, the complex root means
square of the fundamental nonlinearities is presented in [39].
pffiffiffi
2p
2
k
fðXðkÞ Xðk MÞÞg cos
M
M
ð12Þ
pffiffiffi
2
2p
Ir X 1 ðkÞ ¼ Ir X 1 ðk 1Þ þ
k
fðXðkÞ Xðk MÞÞg sin
M
M
ð13Þ
Ia X 1 ðkÞ ¼ Ia X 1 ðk 1Þ þ
Control operation is based upon the instantaneous value
Because of the dc-nature of the fundamental power component,
the variation in the phase error of LPF cannot affect the reference output signal
Merits of FFA:
Demerits of IPTM:
Facilitate better steady-state and transient response.
Require lesser time as compared to FFA.
Poor performance is illustrated during unbalanced non-linear
load application.
Excess number of voltage and current transducers are needed
for the delay.
Demerits of FFA:
Due to the dependency upon the sliding window, the convergence speed is affected.
5.1.2 Frequency domain method (FDM)
In the SHAF controller design, FDM based harmonic extraction
technique plays an important role. The sensed harmonic current
signals are isolated or separated from the fundamental signals
and transformed to time domain form for reference current generation. During the control operation, the switching frequency of the
SHAF is set two times higher than the non-linear frequency of the
reference signal [35–36]. In addition to that, this approach is applicable for both single and three-phase applications. In this method,
the transfer function of a complicated system can be experimentally computed by using frequency study and the disturbances/
fluctuations and parameter changes are easily distinguished. This
method is based upon Fourier analysis. FDM is further classified
into three various methods as fast Fourier analysis (FFA), recursive
Fourier analysis, and wavelet analysis. Each of the mentioned
methods is explained below.
a) Fast Fourier analysis (FFA):
In [37], FFA is used for machine computation of complex Fourier
series. It is a previous version of the discrete FFA (DFFA) based
method. The FFA-based control technique is implemented to
improve the steady-state performance of the SHAF operation
through the appropriate reference current generation [38]. In addition to that, this technique is also used for harmonic elimination by
using a neutral clamped-based multi-level inverter topology. Similarly, the short period FFA is also used for fast harmonic
elimination.
Merits of FFA:
c) Wavelet analysis (WA):
The WA-based control technique is based upon a highperformance signal processing method by which it provides the
Fig. 29. WA-based control approach.
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time-domain transient localized data. The WA method also provides multiple resolution capabilities. Wavelets are used to extract
the fundamental current component from the non-linear loads by
isolating the harmonic component. The WA method acquires an
unchanged frequency decomposition of input signals, which has
an excellent bandwidth with the frequency limits of different harmonic signals [40]. In [41], a combination of artificial networks and
WA-based controllers are used for different load applications to
improve the performance of SHAF significantly. The combined controller performance provides excellent outputs as compared to any
other traditional controller. The mother wavelet is selected as a
part of their feasibility of transients, lower overshoots, and oscillations in the frequency domain. The control block diagram of this
method is illustrated in Fig. 29. The WA of a continuous signal M
(t) at a scale b and the location d are calculated as.
1
W F ðb; dÞ ¼ jbj2
Z
MðtÞl
td
dt
b
ð14Þ
Fig. 30. ANN-BM-based control approach.
where l is the mother wavelet of the system. l is a function of
zero average and for a certain time that is enlarged with b and
interpreted by d.
Merits of WA:
Having non-linearity controlling capacity
More robust and faster speed
Demerits of FBM:
The method provides a fast response with below 1=4 transient
time and is used for both single/three-phase applications.
The computational burden is very less and does not require
expensive controllers.
It is applicable for both non-linear and unbalanced loads with
distorted voltage applications.
Rare uses in industrial application
b) ANN based method (ANN-BM):
ANN-BM is a learning-based system with an increased number
of processing components like a neuron. Recently, ANN-BM is
preferably selected for the SHAF control application. In [45],
ANN-BM is developed for regulating the current harmonics of the
SHAF and the neurons are trained offline by using the parameters
extracted from the PI regulator. The dc-link voltage dynamics are
used in a predictive regulator to compute the first guess tracked
by the convergence method by an adaptive ANN-BM. The learning
rate of the controller is regulated to compensate for the nonlinearity present in the current signal [46]. The detailed application of
ANN-BM is presented in [47]. ANN-BM is generally used to compute the phase information of the grid voltage. The computed
phase and frequency information are used to develop a phaselocking signal by which better synchronization with the grid volt-
Demerits of WA:
For PQ classification, it is not used
Not suitable for noised signal
During dynamic load conditions, the
performance.
WA
shows
poor
5.1.3 Learning-based method (LBM)
To solve natural and environmental-based complex problems,
LBM is used. LBM efficiently succeeds with fuzziness, randomness,
robustness, and uncertainty, and requires a lower cost. LBM is further divided into many advanced strategies like fuzzy-based
method (FBM), ANN-based method (ANN-FBM), adaptive neuro
fuzzy-based methods (ANFBM), genetic-based method (GBM), particle swarm-based method (PSBM), bacterial foraging-based
method (BFBM), ant colony-based method (ACBM) and cuckoo
based method (CBM) [41–42]. A detailed explanation regarding
the control strategy is presented as follows.
a) Fuzzy based method (FBM)
In FBM, the control operation is designed from the appropriate
computation of simple linguistic variable-based fuzzy rule tables.
During the design of fuzzy rules, a complete idea of the system
model is necessary. However, during the design of FBM, an accurate mathematical model of the undertaken system is not required
[43]. The harmonic mitigation process requires a PI/fuzzy regulator, to generate the reference current by properly regulating the
dc-link voltage of the system [44]. The detailed process of the dclink voltage regulation is presented in the next section.
Merits of FBM over traditional approaches:
An appropriate mathematical model is not required.
Controller performance depends upon the system developer’s
experience and knowledge
Operate with inaccurate input
Fig. 31. ANNFBM control approach.
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samples. On the other hand, the ANN can randomly generate and
selects the rules from the training data. FCS is advantageous during
logical and higher-order applications. The ANFBM-based SHAF
decreases the computational load and facilitates better transient
and dynamic operation than individual FBM and ANN-BM operations. The ANNFBM with two inputs and one output systembased equivalent structure is illustrated in Fig. 31 [48–49]. The
ANFBM-based controller is used as a fast reference current tracking
system with decreased settling time and reduced peak overshoot.
The complete control diagram of ANNFBM is illustrated in Fig. 32.
d) Genetic based method (GBM):
GBM is developed from human venereal decoding and designed
by using an ordinary evolution code and hereditary approach [50].
By selecting the population of the individual sample of the total
problem, the operation of GBM is developed. At starting period,
the GBM is based on strings of characters [51]. In [51], the GBMbased approach decreases the computational load and increases
the dynamic performance of the SHAF. By easily hybridizing the
GA with fuzzy and ANN techniques, the SHAF performance is significantly improved [52–53]. The complete control diagram of
GBM is illustrated in Fig. 33.
Merits of GBM:
age is achieved. The complete block diagram of the ANN-BM is
illustrated in Fig. 30.
Merits of ANN-BM:
Facilitate faster reference current extraction
It is used to solve both simple and complex problems.
Performs excellent operation during pattern recognition,
arrangement, and interpretation during noisy inputs
More robust and provide faster action
Demerits of ANN-BM:
Requires excess online or offline training data.
For larger system, needs excess time.
Appropriate precision is needed for layers and neuron
computation.
c) Adaptive neuro-fuzzy based method (ANFBM):
ANNFBM-based control approach is designed by hybridizing
both ANN and FC. It is an active and parallel processing method
that computes the input and output parameters without requiring
the appropriate mathematical modeling and acquires knowledge
from the previous sample information. As studied before, the FC
adaptively concludes and enhanced the data from the numerical
Increases steady-state performance of SHAF.
Reduces the harmonic contained of the system.
It requires a mathematical model.
Demerits of GBM:
Specific evolutionary problems can be solved because of the
inappropriate knowledge of fitness function
GBM may not compute the global optimum.
e) Particle swarm based method (PSBM):
PSBM is a population-based stochastic evolutionary technique
stimulated by the normal behavior of swarm flocking and fish
schooling. During the initial period, the population size is randomly selected, and the search of the optimum point is achieved
by continuously updating the number of generations. Multiobjective PSBM is used by SHAFs to reduce the harmonics contained in the system and improve the grid current and voltage
quality. It is used to solve conflicting goals. In [54], ANFIS-based
PSBM is used to supply the minimum amount of real power
through UPQC for compensating the different voltage sag conditions. This method is also used to provide reactive power support
and facilitate voltage control through the grid [55]. In a non-
Fig. 32. ANNFBM-based complete control approach.
Fig. 33. Complete control diagram of GBM.
Fig. 34. Complete control model of PSBM.
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linear load application, PSBM is used to optimize the PI controller
gains by which the error can be easily minimized [56]. The complete control diagram of PSBM based strategy is illustrated in
Fig. 34. The output of the PI regulator is represented as.
Z
UðtÞ ¼ K P ½RðtÞ CðtÞ þ K I
Demerits of CBM:
Control action depends on the processor speed
Regular maintenance required
t
½RðtÞ CðtÞdt
ð15Þ
h) Cuckoo-based method (CBM)
This method is developed by considering the bird species’
behavior and is known as cuckoo. In CSBM, many nests are present.
In this method, every egg is used as a solution and new eggs of the
cuckoo are denoted as a new solution. The new and excellent
arrangement substitutes the worst solution in the nest. CBMbased SHAF is used to solve power quality problems by eliminating
the harmonics and properly regulating the reactive power [66]. In
[67], CBM improves the convergence speed and UPQC is used to
eliminate the harmonics present in the non-linear load significantly. In [68], the ANFIS-based CBM is used to improve the UPQC
performance and compensate for the voltage sag problems.
Merits of CBM:
0
where RðtÞ is the desired input signal, CðtÞ is the control input
signal, t is the instantaneous time, and UðtÞ is the control input
for the harmonic signal. The dc-link voltage error of SHAF is computed as.
V dc;e ¼ V dc V dc
ð16Þ
Merits of PSBM:
PSBM can handle non-linearity, uncertainty, and nondifferentiability
Regulates the dc-link voltage at dynamic load conditions.
Offers excellent steady-state performance and high accuracy
Demerits of PSBM:
Demerits of CBM:
During a very complex problem, the selection of optima is
difficult
Takes excess time during a longer time run.
Slower convergence speed
i) Adaptive filtering technique (AFT):
This is an excellent current control technique for SHAF reference signal generation [69–70]. The reference current is obtained
by regulating the load current through the sine and cosine values.
During distorted voltage conditions, the adaptive filtering technique provides an excellent result but lags the performance during
frequency variation conditions. The presence of local minima is
illustrated during the convergence condition. The complete control
structure of the adaptive filtering technique is illustrated in Fig. 35.
As illustrated in Fig. 35, Ik is the current input vector, Ok is the filter
actual output vector, Wk+1 is the next weighing vector, and l is the
adaptive constant.
Merits of AFT:
f) Bacterial foraging based method (BFBM)
Similar to the above, BFBM is another nature-stimulated evolutionary technique [57–58]. By eliminating animals having poor foraging techniques and supporting the proliferation of genes with
fruitful foraging techniques, the BFBM is developed. The above
activity is used as an evolutionary control method in power system
problems to eliminate the harmonic component and reference the
current generation. The control action of BFBM is divided into four
specific methods such as chemotaxis, swamped, imitation, and
elimination [59–60]. To reduce the fluctuations of actual dc voltage
as compared to desired dc voltage, by using PSO and BFO method,
the maximum error (Vdc,e), rise time, peak time, and steady-state
error are used as parameter constraints for the PI regulator.
Merits of BFBM:
ATF control theory is operated by a self-adaptation technique
and can change the weights according to the system input
conditions.
The proposed algorithm is suitable for eliminating nonlinearity, inter harmonics, and noise in the nonlinear load current application.
Improves the SHAF stability criterion
Offers excellent harmonic performance
Facilitate better transient response
Produces lesser ripples
Convergence speed is increased as compared to PSBM and GBM
Demerits of BFBM:
The fixed step size decreases the average rate.
g) Ant colony based method (ACBM)
By using the foraging behavior of actual ant colonies, the ACBM
is designed to resolve evolutionary problems [61]. More exactly,
the design of the ACBM is based on the findings for the shortest
path to the food in an ant colony. In [62], ACBM is used to reduce
the constraints of PI regulators and increase the performance of
SHAF. In [63], by using ACBM, a hybrid SHAF is implemented for
improving the power quality under different loading conditions.
In [64–65], an ACBM-based optimized PI controller is used to
reduce the peak overshoot, rise time, and settling time as compared to the conventional PI regulator.
Merits of ACBM:
Offers faster convergence and tracking speed as compared to
PSBM, GBM, and BFBM.
Improved the dynamic SHAF performance.
Fig. 35. Control structure of the adaptive filtering technique.
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Fig. 37. Fixed Frequency Control Diagram.
Merits of SFX:
Fig. 36. Control block diagram of SFX Algorithm.
Mathematical computation is reduced.
Operates for both periodic and harmonic signal
The proportional constant Kp is used to improve the dynamic
performance
Automatically regulates the transfer function to reduce the
Demerits of AFT:
Provide additional computational burden.
Requires a few times and depends on processor speed.
n2 ðnÞ
5.1.4 Other related approaches (ORA)
a) SFX algorithm:
SFX algorithm-based adaptive method is used as a novel control
technique for SHAF control operation. The main of the controller is
to identify the grid current. In this technique, the appropriate
tracking of output SHAF current and elimination of harmonic current from the grid current is not required. In this regard, the control
operation is simpler than another traditional approach. In [71], a
combination of adaptive filter and synchronized filter X technique
is used for SHAF control action. The SFX-based adaptive filter provides an additional gain at fundamental and harmonic load current
components. To improve the dynamic performance of the control
system, a PI controller is used. The undertaken method is used to
filter the harmonics from one or more sensitive load applications.
However, a few important factors are required for the control
action.
b) Fixed frequency:
The complete control structure of the fixed frequency method is
illustrated in Fig. 37 [72]. As illustrated in Fig. 37, the error
between the feedback and desired current is passed through a PI
regulator to produce a changeable linear voltage value. After generating the appropriate voltage, it is compared with the triangular
pulse width modulation value to generate the switching signals for
SHAF operation. The output voltage control of the amplifier is
related to a fixed frequency triangular waveform to generate the
required reference signal for pulse generation. The generated positive current error produces the larger SHAF voltage levels. Similar
to phase ‘A’, other two-phase currents are regulated.
The sensitive load must be a current source
The SHAF is used to compensate for the harmonics and provide
reactive power support.
The harmonic free grid current is extracted by computing the
total load current and compensating current from SHAF. By considering a fixed impulse digital filter with required impulse and error
signals, the complete control block diagram is illustrated in Fig. 36.
The relation between input (X) and output (Y) is represented as.
YðnÞ ¼
b1
X
W a ðnÞXðn aÞ
ð17Þ
a¼0
nðnÞ ¼ DðnÞ YðnÞ
ð18Þ
Fig. 38. Delta modulation Technique.
By properly updating the filter weights at every sampling
instant, the adaptive filters are used to minimize the mean square
error n2 ðnÞ. By using the least mean square (LMS) technique, the
adaptive filter outputs are regulated as.
W a ðn þ 1Þ ¼ W a ðnÞ þ 2lnðnÞXðn aÞ
ð19Þ
where a=0,1,2,3. . .. . .., b1. During the control operation, the
adaptive filters are facing a lot of mathematical computations
within a small period. Therefore, there is a necessity to limit the
order of the filter ‘b’, by which the output frequency of the filter
is also limited.
Fig. 39. DBCR control mode.
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c) Delta modulation technique:
This method is an advanced technique [73,74] of conventional
hysteresis current control. In this method, a constant voltage is
applied at all the switching conditions. The main aim of the controller is to produce an appropriate signal from the compared
results between the fixed tolerance limit (the limit is enough
nearer to zero) and grid current error. If the error between the current is positive, then the system obtains a positive voltage and if
the error between the current is negative then the system obtains
a negative voltage. At constant voltage, this controller synchronized the regular switching interval time with the switching frequency result for optimum result.
In Fig. 38, for phase ‘a’, if the reference current (IC;a ) is greater
than the actual current component then the comparator output
is zero. Similarly, in the opposite case, the comparator output is
one. The above findings are passed to a ‘D’ type flipflop to generate
the switching pulses.
d) Dead-beat current regulator (DBCR):
In the traditional dead-beat current regulator, the controller
computes the necessary voltage to equalize the actual current with
its reference value at the end of the total modulation period. In this
regard, an advanced dead-beat current regulator is proposed for
better SHAF operation [75–76]. The main purpose of the advanced
controller is to compute the actual period at the start of the switching inverter operation. The complete control structure of the
advanced dead-beat controller for single-phase operation is illustrated in Fig. 39.
Fig. 39 shows the basic control block diagram of DBCR, where
the feedback signal is slightly delayed by a definite sampling time,
and obtained few forward blocks are also necessary for switching
signal.
Fig. 41. (a) DDVECT through PI controller. (b) DDVECT through Fuzzy controller.
ing operation. The dc-link voltage regulation is achieved when the
real power injection amount is equal to the switching power loss.
Therefore, for excellent SHAF control operation, the magnitude of
reference current generation must be adjusted by controlling the
generated dc-link current signal (Ie) as illustrated in Fig. 40. Due
to that, an appropriate real power can be injected into the SHAF
for compensating for the switching losses. In recent days, various
types of DC-VCTs such as direct DC voltage control technique
(DDVCT) [77–78] and self-DC-Voltage charging method (SDVCM)
[79–80] are used for appropriate reference current generation. A
detailed explanation regarding the above-mentioned technique is
discussed below. In addition to those other related approaches
are discussed in [81–82].
5.2.1 Direct DC-voltage error control technique (DDVECT)
Traditionally, the dc-link voltage of SHAF is regulated through
the DDVECT where the error (V dc;e ðnÞ) between the actual dc-link
voltage (V dclink ) and reference dc-link voltage (V dc ) of SHAF is controlled by a proportional-integral control (PI) [83,84] and fuzzy
logic controller (FLC) [85,86] as illustrated in Fig. 41 (a–b), to produce an appropriate current signal for controlling the dc-link voltage. ‘n’ is used for the sampling time of the system.
As illustrated in Fig. 41 (a), due to the simple control structure,
the PI-controlled based DDVECT is selected for SHAF control action.
In this technique, the fixed values of proportional and integral
gains are used. However, due to the fixed values, the DDVECT is
unable to perform excellent results during dynamic and transient
state conditions. Therefore, the system exhibits an increased peak
overshoot [83,85], additional time delay [84,87], and increased
steady-state error during the dynamic conditions. The above factors badly affect the controller performance by which the system
is unable to show optimum results. Moreover, the PI controller
necessitates a detailed mathematical model which is quite difficult
during non-linear system design [85,88] and takes a lot of time to
evaluate the appropriate gains for the SHAF operation [88]. Therefore, it is not suitable for all types of system operations by using
fixed gain values.
Looking at the demerits of the PI controller, a substitute fuzzy
controller (FC) is used for a similar operation. The FC technique is
based upon four factors such as fuzzification, rule base, interpretation, and defuzzification. In Fuzzification, the crisp values of the
voltage error and change in voltage error are changed to the fuzzy
values by using the fuzzy membership functions. The shape of the
membership values can be trapezoidal, triangular, Gaussian,
gaussian-2, bell-shaped, etc. Due to the simple structure, implementation, and lesser computational burden, trapezoidal and tri-
5.2. DC voltage control technique (DC-VCT)
Similar to the above control technique, DC-VCT is also another
important control stage used for SHAF controller design. This control technique is used to regulate the dc-link voltage of SHAF where
the dc-link capacitor is used as an energy storage device. In ideal
conditions, a constant dc-link voltage of the SHAF is achieved with
no real power transfer between SHAF and the grid. However, during the real-time application, it is difficult to regulate the dc-link
voltage at its rated value because of the SHAF switching operation
and power loss condition. Therefore, there is a necessity to develop
an appropriate dc-link voltage control for excellent SHAF operation
by injecting the appropriate injection current into the system.
Mostly, the regulation of the dc-link voltage is achieved through
appropriate control of the real power injection during the switch-
Fig. 40. DC-VCT-based control approach.
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Findings:
The SDCCT offers better accuracy and faster speed as compared
to DDVECT during the DC generation [79]. However, the SDCCTbased control approaches are used in SHAFs during the
ANN-based non-linearity extraction techniques [92,79]. Therefore,
further study is required to test the suitability of the method during other nonlinearity extraction control algorithms.
5.2.3 Other related approach
To regulate the dc-link voltage of the SHAF efficiently, the
power engineers suggested different control features in the
above-mentioned approaches. The newly added features such as
step size error minimization method [79] to the SDCCT and
inverted voltage error variation to the DDVECT, are to facilitate
better control action by cancelling the variations in voltage error
in terms of over voltage and under voltage during the dynamic
or transient conditions. The previous methods are directly, and
the modified methods indirectly control the voltage error to provide optimal results through FC. The advanced approaches are
operated only during the presence of over-shoot and undershoot
voltage conditions. In this regard, the advanced controller does
not affect the normal operation of the controller during the
steady-state condition. A detailed explanation regarding the modified approaches is presented in [79]. The advanced techniques
show their effectiveness by offering faster dynamic/transient operation and improving the SHAF operation by properly mitigating the
harmonics.
Findings:
The above-advanced techniques provide better results as compared to other approaches. However, the above-advanced
approaches are used only for specific control applications like step
size voltage error minimization technique only applicable for
ANN-based single-phase harmonic mitigation technique and
inverted voltage variation method is only applicable for NETbased control technique. Therefore, novel advanced control techniques are necessitated further studies to guarantee the appropriateness and compatibility with other control applications.
Fig. 42. (a) SDCCT through PI controller. (b) SDCCT through Fuzzy controller.
angular shapes are widely selected [89,90]. After the selection of
the membership function, the input voltage errors are passed
through the fuzzy inference system to obtain the necessary DC
component (Ie) according to the designed fuzzy rule base table.
Due to the less computational time, the Mamdani-based inference
system is selected widely [88]. After all of the necessary processes,
the fuzzified DC outputs are converted to crisp outputs through the
defuzzification method. Mostly, centroid-based defuzzification
methods are chosen due to the accurate average computation.
Findings:
By using the merits of FLC, the performance of SHAF is significantly improved. FLC is shown its superiority by providing better
adaptability, robustness, faster-tracking speed, and better precision. Due to the superiority, the fuzzy control based DDVECT performs better results during both steady and dynamic state
conditions. During the control operation, there is no necessity to
know the appropriate mathematical model of the non-linear system. In this regard, by developing an increased number of 7*7
membership functions and 49 fuzzy rules for larger test systems
[91]. In this way, the Fuzzy based controller overcomes the demerits of the PI controller efficiently.
5.2.2 Self DC-capacitor charging technique (SDCCT)
Similar to the above, an alternative technique is used to regulate the dc-link voltage by using the SDCCT [92,79]. The previous
DDVECT-based method is depended on the appropriate estimation
of the control signal. However, this control strategy is based on the
self-capacitor charging method by applying the law of conservation of energy to facilitate both the charging and discharging operation of the capacitor. Like the DDVECT approach, the SDCCT is also
dependent upon two control operations such as PI [92,94] and FCbased self-charging [79,94] controller as illustrated in Fig. 42 (a–b).
The PI and FC-based methods are used to regulate the voltage error
and then used to generate the DC signal (Ie ) by using the following
mathematical equation [93].
Ie ¼ 2C=3V g T
V dc
2
ðV dc Þ2
5.3. Current regulation approach (CRA)
The main reason for the controller is to generate an appropriate
pulse through different CRA methods, by which the inverter is capable to produce an appropriate injection current to compensate for
the nonlinearity present in the load. Generally, the CRA is achieved
by perfectly sensing and comparing the grid/feedback current with
a fixed reference current obtained by the NET. In addition to that,
Fig. 43. Control model of the DCRA.
ð20Þ
where C is the capacitance value, V g is the grid voltage, and T is
the total period of the system.
Fig. 44. Control model of the ICAR.
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the obtained dc-link current through the dc-link voltage regulation
technique is used for generating the reference current for appropriate inverter pulse generation. Looking at the different current regulation techniques, the direct and indirect CRA-based approach is
widely used for reference current generation. In addition to that,
PWM, hysteresis band regulation method, and predictive regulation method is incorporated with the CRA to achieve an optimum
result [95–97].
5.3.1 Direct and indirect CRA (DCRA and ICAR)
During DCRA, the required harmonic injection current is
directly obtained by using a current control algorithm. The control
model of the DCRA is illustrated in Fig. 43. In this control operation,
by comparing the reference injection current (Iinj ) and the desired
non-sinusoidal injection current (Iinj ), an error signal (E) is computed. The generated error is passed through the current regulator
to obtain an appropriate reference signal by which the SHAF can
produce the required injection current according to the set nonlinear reference current condition. In this control operation, the
non-linear reference current is nothing but the actual load current.
Due to this the actual harmonic contained in the system is
computed.
Similarly, during ICAR operation, by considering the grid current system data, the non-linear injection current is computed to
compensate for the harmonics contained in the system. The complete control model of the undertaken ICAR scheme is illustrated
in Fig. 44. In this control operation, the sensed grid current result
(Ig ) is compared with the sinusoidal reference grid current results
(Ig ) to obtain a current error signal (E). After obtaining the current
error signal, it is passed through the current regulator to generate
the actual grid current by considering the sinusoidal reference grid
current. In this situation, the used reference current signal is nothing but the fundamental grid current component. As the system is
controlling the grid current, the actual nonlinear current injection
is generated by the SHAF according to the harmonic load current
demand directly. Therefore, this technique is known as ICAR.
Findings:
By comparing the outcomes generated from the above respective controllers, it is found that by using the ICAR scheme the performance of the SHAF is significantly improved. As compared to the
DCAR scheme, the control operation of ICAR is much simpler,
reduces the computational burden, and requires lesser sensor components [98–99]. ICAR is also capable to solve the switching ripple
problems of SHAF [100]. Due to the inappropriate knowledge of the
grid current, the DCAR cannot compensate for all the harmonics of
load during the distorted grid conditions. Therefore, the THD percentage of the overall system is increased. However, to solve the
above problem ICAR scheme is more efficient due to the presence
of appropriate grid data.
5.3.2 Pulse width modulation method (PWMM)
By sensing an appropriate current signal generated from the
regulator, it is used through a standard PWMM to generate
required switching pulses for SHAF operation by varying the duty
Fig. 46. SVPWM-based current regulation approach.
ratio of the inverter. A typical PWM-based current regulation
approach is illustrated in Fig. 45. As the illustrated method necessitates a sinusoidal modulating signal, hence the control technique
is known as the sinusoidal PWM technique. The above method is
widely accepted for voltage source based SHAF applications
[101,102]. The duty ratio of each pulse is decided according to
the amplitude of the used modulating signal. In this way, the SHAF
can produce the desired injection current for eliminating the harmonics and non-linearity of the sensitive load. In addition to that,
an advanced PWM technique [103] is proposed to improve the
SHAF performance. The advanced technique is developed by using
a 5 kHZ switching frequency and a minimum size LC filter. As compared to the sinusoidal PWM technique, this advanced technology
provides an excellent result by minimizing the odd harmonics,
which are nearer to the rated switching frequency.
Similar to the above methods, another popular technique
known as the space vector PWM technique is used for appropriate
switching pulse generation at a specific conduction period [104].
Not only this technique is used for two-level voltage source inverters, but also it is used for larger switching operations like neutral
point inverter applications [105,96]. Due to the better control operation and appropriate switching pulse generation, it is applicable
for different single and multi-level inverter applications.
Findings
As compared to the above-mentioned SPWM, the SVPWM strategy facilitates excellent harmonic elimination capability, smoother
modulation, and 15 % higher dc voltage utilization as compared to
SPWM. However, the modeling and working principle of the
SVPWM is difficult as compared to the SPWM approach. The complete control structure of the SVPWM strategy is illustrated in
Fig. 46.
5.3.3 Hysteresis band regulation method (HBRM)
HBRM-based control technique is selected for its simple implementation advantages. By comparing the voltage/current error
with the hysteresis band, the control operation of HBRM is
achieved. In HBRM, the error component is passed through two
hysteresis bands (top and bottom). When the error component
exceeds the top and bottom hysteresis limit, an appropriate
switching signal is passed to the power switches for limiting the
error component within the set limit and estimating the required
reference current component. Due to this, the system achieves faster current regulation with improved accuracy and does not need
any system information [106,107]. However, the fixed band techniques lag the system performance during high-frequency variation by providing additional noise and switching losses
[108,109]. To overcome the above problem, an adaptive HBRMbased control technique is suggested in [106,108,110]. HBRMbased current control technique is applied for SHAF operation with
a set switching frequency [108,111,197–200]. However, the control
approach is very sensitive to the system parameter [109], and the
application of an adaptive band also rises the system complexity.
5.3.4 Predictive regulation method (PRM)
PRM [112–113] based control approach is applicable to forecast
the future comportment of the regulated current component-
Fig. 45. PWM-based current regulation approach.
161
B. Sahoo, M.M. Alhaider and P.K. Rout
Renewable Energy Focus 44 (2023) 139–173
based test system model, previous input/outputs, and actual input/
output. Notionally, the PRM-based controller operates by forecasting a voltage control signal for SHAF operation based on the comportment of reference and measured current and supply voltage
components. This helps the output current to reach the actual reference target within the sample time [114,115,200–211]. However,
to forecast an accurate desired current, actual knowledge of the
system must be required. In [114], to improve the forecasting process, an additional delay time is required. However, this reduces
the accuracy of harmonic elimination during complex system
applications. Moreover, this approach is suggested to apply with
a PWM generator for SHAF operation.
5.4. Synchroniser control technique (SCT)
In this section, different phase synchronizer methods are discussed for SHAF operation. The above control approach is based
upon two common methods as phase lock loop (PLL) [116–1117]
and zero-cross detection (ZCD) technique [118,119,120]. Similar
to the above, other techniques such as ANN/Adaline [121–
122,222] and fundamental current extraction (FCE) [123–124]
methods are also included for three/ single phase SHAF operation.
5.4.1 ZCD method
This is the simplest control method used for phase synchronization reasons. As per the ZCD, a control unit is developed to identify
the zero-crossing point of grid voltage and generate appropriate
pulses for SHAF operation [119]. Due to the simplicity of design,
the integration is easier as compared to other methods, but loses
its stability during oscillating grid current situations [125]. In that
case, the possibility of inaccuracy is more due to the greater number of ZCD points. To resolve the problems, filters are used before
the integration of designed controllers [126]. However, the prefiltering operation again leads/lags the phase sequence, which is
difficult to regulate as ZCD is an analog-based method. In addition
to that, the ZCD point only detects at every half cycle interval of
fundamental grid frequency [127]. To circumvent the above problem, the control circuit regulates additional hardware circuits per
phase, which again increases the cost, size, and reliability. In
[119], a ZCD method-based experimental setup is proposed to provide the initial pulses for a digital signal processor-based SHAF
controller during zero-crossing voltage at PCC. This technique is
applicable for both single and three-phase system applications.
However, looking at the above demerits, this technique-based control method is least preferred for SHAF operation.
5.4.2 PLL method
This is the most preferred control technique because of its simplicity and capability to operate at oscillating grid conditions. PLL is
an old technique [128,129] and is applicable for different applications such as communication, a control application, and instrumentation. The control application is divided into three sub-parts
as phase comparator (PC), low pass filters (LPF), and voltage control (VC) as shown in Fig. 47. In PC, a reference phase angle (h )
is compared with a feedback phase angle (h) and generates an error
signal (Dh). After that Dh is passed through the LPF to eliminate the
noise and high-frequency component generated from the PC. The
obtained signal is passed through the VC to generate the feedback
Fig. 48. SRF-PLL control method for SHAF operation.
phase angle (h) and again goes to the PC block. LPF is used to continuously eliminate the undesired signal for a few iterations and
when it reaches zero, the phase angle is locked and matches the
h . By using the above method, the phase angle of the system is
easily regulated.
a) Synchronous reference frame PLL (SRF-PLL):
The performance of PLL is enhanced through SRF based
approach known as SRF-PLL. SRF-PLL approach improved the performance of both single/three-phase applications [117–121,116–
130]. The detailed structure of SRF-PLL is illustrated in Fig. 48 (ab). By comparing Fig. 47 and Fig. 48, it is found that the implementation of PD blocks is different from one another. As the SRF-PLL
name indicates, this controller operation is based on SRF theory.
In SRF-PLL, the three-phase voltage parameters are converted to
the two-phase stationary ab frame (Clark transformation) and
rotating dq frame (Park transformation) as illustrated in Eq. (21)
and Eq. (22) respectively.
Note that ‘n’ indicates the sampling rate. To eliminate the nonlinearity, a PI regulator is used to regulate the ‘q-axis’ component
and angular frequency ‘x’ of the undertaken voltage parameter.
Integrating ‘x’, the h can be computed and this process is continued by feeding back the h in to ab dq block until the h is equal
to h value.
2
3
"
# V ðnÞ
pffiffiffiffiffiffiffiffi 1 1=2 1=2 6 ga
7
pffiffiffi
pffiffiffi
¼ 2=3
4 V gb ðnÞ 5
V b ðnÞ
0
3=2 3=2
V gc ðnÞ
V a ðnÞ
V d ðnÞ
V q ðnÞ
¼
Cosh
Sinh
Sinh Cosh
V a ðnÞ
V b ðnÞ
ð21Þ
ð22Þ
Initially, SRF-PLL is applicable for three-phase applications as
illustrated in Fig. 48 (a). However, looking at the single-phase need,
it is used for single-phase controller design as illustrated in Fig. 48
(b). In single-phase, the Clark transformation is avoided and a p=2
factor is multiplied with the actual voltage component to generate
the ‘b’ axis component. After generating the ab component, the further control technique is similar to the three-phase controller.
Merits:
Avails accurate and fast-tracking of grid frequency and phase
angle during linear grid voltage conditions.
Demerits:
Unsuitable for harmonic grid voltage conditions.
Requires additional filters like low pass and high pass filters for
harmonic elimination.
Fig. 47. PLL control method.
162
Renewable Energy Focus 44 (2023) 139–173
B. Sahoo, M.M. Alhaider and P.K. Rout
Demerits:
Computation of constant gain is very difficult during unbalanced grid voltage conditions.
c) Double decoupled SRF-PLL (DD-SRF-PLL):
DD-SRF-PLL is used to separate the positive and negative
sequence components and transformed them into two SRF loops.
After that, an additional decoupling network is implemented to
separate the positive current component with the fundamental frequency before entering to the PLL. A control diagram related to DDSRF-PLL is illustrated in Fig. 50 [116]. As illustrated in Fig. 50, the
starting procedure is similar to the traditional SRF-PLL technique
as shown in Fig. 48, where the three-phase voltage input signals
in the natural frame is converted to a two-phase ab rotating frame
and again ab to dq stationary frame. In dq frame, the positive
(V þ
g;dq ) and negative (V g;dq ) components are separated. To obtain a
Fig. 49. SR-PLL control method for SHAF operation.
b) Self-regulating PLL (SR-PLL):
SR-PLL operating principle is similar to SRF-PLL. However, as
compared to traditional SRF-PLL, SR-PLL provides additional filtering operations. In this condition, the input in ab the frame will be
further filtered by a self-regulating controller to diminish the
unwanted noise and high-frequency elements before transforming
to a dq rotating frame. Due to this, the PLL can estimate the actual
phase angle and frequency respectively.
The basic block diagram of SR-PLL is illustrated in Fig. 49 and
the working principle is detailed below.
"
Y fa ðsÞ
Y fb ðsÞ
#
¼
"
#
"
#
f
f
n Y a ðsÞ Y a ðsÞ
2pf c Y b ðsÞ
þ
s Y b ðsÞ Y fb ðsÞ
s
Y fa ðsÞ
þ
linear component V g;dq and V g;dq , the computed components are
passed through a decoupling network. The computed positive
sequence components with the fundamental frequency will be
applied until the desired phase angle is not achieved.
Merits:
Applicable for balanced and unbalanced load applications.
Not dependent upon the constant gain parameter.
Demerits:
ð23Þ
Complex structure due to additional SRF loop
where Y fab ðsÞ is the harmonic free (fundamental) input component in ab frame, Y ab ðsÞ is the instantaneous input signal in ab
frame, ‘n’ is the constant gain parameter, f c is the cut of frequency
of the system. Despite of all advantages, the requirement of proper
gain computation lags the controller performance during real-time
applications. A detailed analysis regarding the gain value estimation is discussed in [123,131].
From [123,131], a selection of reduced gain values improves the
accuracy of the controller but decreases the dynamic responses.
Similar to the above, for increased gain value opposite effects have
occurred. To obtain a better synchronization between accuracy and
dynamic response, a careful selection of gain value is needed.
Merits:
Suppress high-frequency components through constant gain
parameters
Fig. 51. DD-SRF-PLL control method for SHAF operation.
Fig. 50. DD-SRF-PLL control method for SHAF operation.
Fig. 52. FCCM control method for SHAF operation.
163
B. Sahoo, M.M. Alhaider and P.K. Rout
Renewable Energy Focus 44 (2023) 139–173
Cost is more.
nate the distorted component from the non-linear load current/voltage signals. Fig. 49 illustrates a control example model of
FCCM with an integrated self-regulating filter component.
To extract the required synchronized signal (sinðnxDt þ hÞ), the
following processes are necessary to follow up.
(i) The main objective of this control is to extract the sinusoidal
voltage reference component (V g;f ðnÞ) from the tracked grid voltage components (V g ðnÞ). Initially, abc=ab transformation is
required to separate the fundamental voltage (V ab;f ðnÞ) and distorted component (V ab;ac ðnÞ) respectively. The related mathematical equation becomes
5.4.3 ADALINE method
This is the most recent control method that is applicable for
SHAF based on the ADALINE method. Generally, the ADALINE
method is used for non-linear component extraction and fundamental current computation. However, in addition to the extraction, the proper regulation of the ADALINE method is also
suitable for the synchronization proposed. To achieve this objective, a unified ADALINE control technique is suggested for SHAF
operation [132]. The complete control structure of the proposed
system is illustrated in Fig. 51 and Fig. 52.
In controller design, the grid voltage V g ðnÞ is compared with a
computed voltage (V f ;c ðnÞ). Here ‘n’ is denoted as the sampling rate
for digital controller design. The error component (EðnÞ) is passed
through a weight update method as illustrated in Eq. (24). This
V a ðnÞ
V b ðnÞ
method is used to update the weight (w) or the coefficient (w11
and w21 ) of sinðnwDtÞ and cosðnwDtÞ vectors.
dEðnÞMðnÞ
MðnÞT MðnÞ
ð24Þ
w11
where w ¼
is denoted as the weight coefficient,
w21
sinðnxDtÞ
is denoted as fundamental sin e and cos ine vecM¼
cosðnxDtÞ
tors. EðnÞ ¼ V g ðnÞ V f ;c ðnÞ is denoted as the error among the measured and computed components. d is denoted as the learning
factor of the control signal.
At the equal time, w11 and w21 is used to estimate the instant
fundamental voltage magnitude ( V f ðnÞ ) of V g ðnÞ as illustrated in
Eq. (25).
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
V f ðnÞ ¼ w211 þ w221
V a;f ðnÞ þ V a;di ðnÞ
ð26Þ
V b;f ðnÞ þ V b;di ðnÞ
where V a;f ðnÞ is the fundamental voltage component and
V a;di ðnÞ is the nonlinear voltage component respectively. Similarly,
the b components can be identified and represented. By using the
inverse transform as indicated in Eq. (27), the computed V a;f ðnÞ and
V b;f ðnÞ components can be converted into pure sinusoidal components V g;f ðnÞ. This self-regulation method is only applicable for
non-linear grid situations and for balanced grid conditions, this
method can be omitted to reduce the complexity.
wnþ1 ¼ wn þ
¼
rffiffiffi 1
2
12
V g;fb ðnÞ ¼
3
12
V g;fc ðnÞ
V g;fa ðnÞ
0
pffiffi
3
2
pffiffi
23
V a;f ðnÞ
V b;f ðnÞ
ð27Þ
(ii) Magnitude of voltage V f ðnÞ can be determined by using the
estimated fundamental components as V a;f ðnÞ and V b;f ðnÞ. V f ðnÞ
can be computed as
V f ðnÞ ¼
ð25Þ
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
V a;f ðnÞ þ V b;f ðnÞ
ð28Þ
(iii) The unit form of the signal is generated by dividing V g;f ðnÞ
from the V f ðnÞ . At the end, the synchronization signal
sinðnxDt þ hÞ is computed as follows
This process continued until V f ;c ðnÞ ¼ V g ðnÞ. During that period,
the effective magnitude of V g ðnÞ is generated and divided from the
V f ;c ðnÞ, to generate the required synchronization component of
sinðnxDt þ hÞ.
This synchronization method is applicable for both 1u and 3u
applications [117–121,133]. During this condition, the grid voltage
must be balanced and sinusoidal. It is noted that by looking at
Fig. 48, the ADALINE-based controller is applicable for singlephased applications. For three-phase applications three similar
control models are required for the inverter operation.
Merits:
sinðnxDt þ hÞ ¼
V g;f ðnÞ
V f ðnÞ
ð29Þ
Merits:
This is applicable for three-phase applications.
Separate the balanced and unbalanced components.
Provides better frequency regulation.
Demerits:
Applicable for both 1u and 3u applications.
Simple structure and easier implementation.
The system performance depends upon the constant gain
parameter.
Demerits:
6. Comparative control analysis section
Not applicable during harmonic grid voltage application.
The advancement of the voltage controller is dependent upon
the learning rate.
To support the above literature survey and give a conclusive
idea about the SHAF control strategy, in this study, three comparative control tables such as Table 10, Table 11, and Table 12 are
presented. Table 10 is dedicated to summarising the abovementioned SHAF-based controller based on implementation complexity, response time, settling time and non-ideal grid condition,
and type of integration. Similar to Table 10, according to the controller types as centralized, decentralized, and distributed controllers, a constructive Table 11 is formulated, and the detailed
findings are presented. The complete control structure according
to their types is illustrated in Fig. 53(a–c) respectively. In addition
to that, the novel SHAF controller benefits and the shortfall is further discussed in the tabular form and presented in Table 5 accord-
5.4.4 Fundamental current computation method (FCCM)
This is the most recent current control technique for SHAF operation. This is specially used to compute the fundamental (pure
sinusoidal) of voltage by which the grid synchronization is possible. The output of the controller is almost similar to the
ADALINE-based SHAF control algorithm. However, FCCM has one
more merit over the ADALINE concept in that it can be operated
significantly during the presence of unbalanced/distorted load conditions [123–124]. This method is used an additional selfregulating filter component [131–134,135]. This filter can elimi164
Renewable Energy Focus 44 (2023) 139–173
B. Sahoo, M.M. Alhaider and P.K. Rout
Table 10
Comparative summary of SHAF-based controller.
SI No.
Control Approach
ImplementationComplexity
Dynamic Response Time
Settling Time
Non-ideal grid conditions
Applications
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
SRFM [30]
IPTM [34–39]
DC-VCT [35–36]
FFA [37]
RFA [39]
WA [40–41]
FBM [43]
ANN-BM [45]
ANFBM [48–49]
GBM [50–51]
PSBM [55–56]
BFBM [57–58]
ACBM [61–62]
CBM [66–68]
ZCDM [128–129]
SRF-PLLM [117–130]
SR-PLLM [123,131]
DD-SRF-PLLM [116]
ADALINE [132]
FCCM [123–124]
Less
Less
More
More
More
More
Less
Less
Less
Less
Less
Less
Less
Less
Less
Less
More
More
Less
Less
Faster
Slower
Slower
Slower
Slower
Slower
Faster
Faster
Faster
Faster
Faster
Faster
Faster
Faster
Faster
Slower
Slower
Slower
Faster
Slower
Faster
Faster
Faster
Faster
Faster
Faster
Slower
Slower
Slower
Slower
Slower
Slower
Slower
Slower
Slower
Faster
Faster
Faster
Slower
Faster
Satisfactory
Bad
Satisfactory
Satisfactory
Satisfactory
Superior
Superior
Superior
Superior
Superior
Superior
Superior
Superior
Superior
Bad
Bad
Satisfactory
Satisfactory
Bad
Superior
1u
3u
3u
1u
1u
1u
1u
1u
1u
1u
1u
1u
1u
1u
1u
1u
1u
3u
1u
3u
and 3u
and
and
and
and
and
and
and
and
and
and
and
and
and
and
3u
3u
3u
3u
3u
3u
3u
3u
3u
3u
3u
3u
3u
3u
and 3u
Table 11
Comparative summary of SHAF controller with a most suitable control architecture.
SHAF
based
control
Control architecture
Local control selected
V&f
mode
Power
management
Optimization
Steadiness
Battery
management
Installation
complexity
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
[136]
[137]
[138]
[139]
[140]
[141]
[142]
[143]
[144]
[145]
[146]
[147]
Distributed
Centralized
Centralized
Centralized
Centralized
Centralized
Decentralized
Distributed
Distributed
Distributed
Distributed
Decentralized
U
U
*
U
U
U
U
U
*
U
U
U
U
U
U
U
U
*
U
U
*
U
*
U
U
*
U
U
*
*
*
*
*
*
*
*
*
U
U
U
*
U
*
*
*
U
*
*
*
*
*
U
*
U
*
*
*
U
High
Medium
High
Medium
Medium
High
Medium
Simple
High
High
Medium
High
13.
14.
[148]
[149]
U
U
U
U
*
*
*
U
*
U
High
Medium
15.
16.
17.
18.
19.
20.
21.
22.
[150]
[151]
[152]
[153]
[154]
[155]
[156]
[157]
Droop method
Droop method
Droop method
Adaptive droop
*
*
*
*
U
U
U
U
*
U
U
U
U
U
U
*
*
U
*
U
*
*
U
*
*
U
U
U
U
U
U
U
*
*
U
*
U
U
U
U
*
*
U
*
Medium
Medium
Medium
High
High
High
High
Medium
23.
24.
25.
26.
27.
28.
[158]
[159]
[160]
[161]
[162]
[163]
Centralized
Centralized/
Decentralized
Distributed
Centralized
Centralized
Centralized
Distributed
Decentralized
Decentralized
Centralized/
Decentralized
*
*
*
*
Decentralized
*
PQ& Droop method
Droop method
Droop method
PQ& V/f mode
PQ & V/f method
Outer Voltage & Inner current
Droop method
Droop method
Angle control
Droop method
V/f mode
Sliding control with droop
strategy
Droop method
Droop method
Frequency scheduling control
*
Droop method
Droop method
Droop method
Droop method
U
*
U
U
U
*
*
*
U
U
U
U
*
*
U
*
*
U
U
U
*
U
U
*
*
*
*
*
*
*
High
Medium
Medium
Medium
High
Medium
hybrid grid applications. The research on shunt active filter controller design till now has mostly emphasized energy management
and power quality regulation by using dispersed and synchronized
control strategies. However, shunt active filter concept to be ready
for real-time implementation, other equally important factors such
as stability, power quality improvement, power reliability, fault
ride-through capability, optimal dispatch need to be enthusiastically explored for complex system applications. Research gaps
identified during the literature survey and conceivable research
points for future work are indicated further in this section.
ing to the AC and DC grid structure. In Table 10, Table 11, and
Table 12, the overall SHAF control structure is discussed with different future possibilities and challenges. In the respective tables,
a complete idea regarding the SHAF controller can be illustrated.
7. Research gap and possible solutions
In this study, a brief review on active power filter design and
associated control strategies are performed for microgrid and
165
B. Sahoo, M.M. Alhaider and P.K. Rout
Renewable Energy Focus 44 (2023) 139–173
Table 12
Summary of effective results and possible problems related to SHAF-based MG Applications.
SHAF based control
applications
[164]
[165]
[166]
[167]
[168]
[169]
[170]
[171]
[172]
[173]
[174]
[175]
[176]
[177]
[178]
[179]
[180]
[181]
[182]
[183]
[184]
[185]
Effective Solutions
Possible Problems
Lessen the effect of constant power load
Balance constant voltage and improve the stability at the DC grid without
affecting the charging/discharging condition
Provide a robust solution to improve the power quality
Tackle the effects of variable load
Balance the voltage and provide reasonable solutions.
Improved robustness and stability
Shows robustness across uncertain power loads
Provide parallel operation
Faster system response and provide multi-level output
Maintain constant power generation from the green energy system.
Provide faster dynamic response
Improves the power reliability
Generate constant current during voltage unbalance conditions
Having fault ride-through capability
Faster power balancing operation and improved stability
Improved voltage control with droop regulators
Having plug-and-play capability
Guarantee improved stability and reliability
Optimize the storage device performance
Avails better power flow
Balancing the load current between battery and DC grid
Balances the unbalanced terminal voltages
Excellent voltage and power-sharing operation
Improves the power regulation between sources
Eliminate the requirement of a communication network
Mitigates the line parameter variations
Compensate the circulating current
Improves the System accuracy
Improves the voltage and current accuracy
Resolves the power fluctuation issues
Resolve the power quality and reliability issues
Control performance is enhanced by using optimization techniques.
Improves the charging/ discharging capability
Reduces the power dependency from the grid
Improves the overall performance
Reduces the total harmonic distortion
Compensate the non-linearity
Considers variable green energy systems
Provides excellent reactive power support
Balances the frequency and voltages
Reduces the effect of high gain constants
Guarantee the dynamic stability
Improves the robustness by reducing the sensor requirement
Optimize the power generation and regulation
Provides reactive power support
Reduces the component requirement
Control the voltage magnitude variations
Improves the better power quality
Provides additional reactive power support to the synchronous generatorbased system
Support communication failure
Improves the grid synchronization
Facilitate parallel inverter operation
No synchronization is required
Sensorless operation
Better power-sharing operation between load and storage
Provide excellent SOC regulation
Provide excellent DC-link Voltage regulation
Provide better energy management
SOC control
Harmonic and frequency regulation
Excellent transient operation
Having Fault ride-through capability
Improves robustness of the system
Better economic operation
Facilitate better energy management
Optimize the power production rate
Loss reduction and avail better power reliability
Regulates the DC grid voltage
Better active and reactive power regulation of the DGs
Reduce the effect of line impedance
Decrease the circulating current between the DGs.
166
The chattering problem instigated by sliding mode control is not estimated
SOC is not considered during power management
The chattering problem is not considered
Response time is decreased due to the increase in load
Complex controller design
More sensors are used
Only focuses on PV-based DC microgrids.
Absence of proper energy management
Only focuses on PV-based DC microgrids.
Absence of proper mathematical computation
Controller implementation is difficult due to the presence of a communication network
Lots of sensors are required
Losses the control over sudden variation
non-linear load effects are not considered
Not considered the SOC limits
Decreases the storage capacity of the battery
THD is a major problem
Reduces the dynamic responses with load variations
THD is not considered
Complex controller design due to the use of virtual frequency concept
Implementation is also difficult
Not guaranteed the voltage and frequency stability
Slower controller responses
In AC-grid, the RES-based DGs are not integrated, and
the performance is not studied.
Implementation is not economical
Avoid sensitive load applications
Voltage magnitude may vary
Difficulty in implementation.
Implementation is difficult
Slower response
Not included reactive power comp.
Performance is limited to a radial network
Absence of mathematical computation
Not Economic
Difficult to implement
Communication networks make the system complex
No. of DGs is high
Not economic
Complex structure
Avoid signal decomposition
RES based DGs are not considered
Variability is not studied
Time-consuming
Variability is not studied
Complex system design
Slow tracking operation
Not considered frequency stabilization
Uses constant gains for controller design
Lesser synchronisation
Avoidance of Nonlinear/unbalanced load
Higher error values
There is lesser synchronization between controller
objectives and strategy
Not Economic
Renewable Energy Focus 44 (2023) 139–173
B. Sahoo, M.M. Alhaider and P.K. Rout
Table 12 (continued)
SHAF based control
applications
[186]
[187]
[188]
[189]
[190]
[191]
[192]
[193]
[194]
[195]
[196]
Effective Solutions
Possible Problems
Faster tracking operation concerning variable load
Improves the power quality
Regulate the voltage and frequency variation.
Faster power-sharing operation
Showing dynamic performances during both steady-state and transient
conditions
Reduces the communication channel requirement
Enhances the system efficiency
Provides excellent power flow
Harmonic reduction
Avoidance of communication system
Enhances the power flow between the sub-grid
Maintain the stability between the AC/DC MG
Enhances the power quality and reliability
Enhances the power flow control and guarantees the stability
Faster transient response
Robust controller performance
Enhances power quality and stability
Avails better power-sharing operation between AC and DC grid
Enhances the transient stability
Provide excellent voltage and frequency regulation
Improves the power-sharing operation
Provide excellent reactive power support
Guarantee the small-signal stability
Avails better power flow between AC and DC MG
Sudden integration and removal are also possible
Avoids communication network
Provide better economic operation
Facilitate hybrid AC-DC grid operation
Stable AC/DC MG operation
Excellent reactive power support
Harmonic regulation
Improves the power quality
Provides economic power-sharing operation
Difficult to apply in a complex system
Not guaranteed the reliability
No information regarding losses
Implementation is difficult
Not applicable to load variation
Not providing reactive power support
Enhances the system efficiency
Provides excellent power flow
Harmonic reduction
Complex circuit design
Slower response
Difficult to implement
Effect of high-frequency oscillation is avoided
Creates harmonic problem
Creates voltage and frequency problem
Complex integration
Higher error values
Performance is limited to the radial system
Lags the suitability in case of real-time application
Difficulties in operation
Communication delay leads to slower response
Higher deviations are found in power-sharing operation
Not economic
Lags during load variation
Presence of a higher unbalanced component
Production cost is not included
Variability in RES is not considered,
SHAF based interlinking inverter sizes can be regulated by considering the actual information related to variable load, renewable generation, and storage devices available at the dc-grid
stations.
On the line of synchronous converter concept, Novel interlinking inverter concepts are also required to evaluate.
7.1. Power-grid design topologies
If a standard shunt active filter (SHAF) based microgrid topologies are represented on the lines of IEEE 13/39 bus networks or
on the CIGRE network, then only a clear idea about the comparative control strategies is obtained.
SHAF based dc-sub grid designs such as AC-DC grid, ring grid,
zonal dc grid, and multi dc-grid into hybrid grid should be
discovered.
SHAF based topologies can be explored to enable different
power pricing bonds between the utility grid and ac-dc subgrid.
The analysis of short circuit capability or the ratio of power
demand and different parameter computation/ switches/capacitor requirements decides whether SHAF based different sub
grids can make a hybrid grid or not.
Voltage, frequency, power factor, and power quality conditions
for SHAF based hybrid microgrid systems can be studied.
There is a lot of scope for further research in the SHAF design as
only MLIs have been investigated to date.
Research effort on single-phase SHAF applications is
gaining interest as low-power smart homes are increasing
gradually.
7.3. Hybrid grid energy management
If the sub-grids are controlled by non-droop methods, then the
decentralized methods of regulating frequency and voltage for
active power regulations are limited to work. Therefore, to
reduce the complexity, other improved methods for SAHF operations are required to study.
Propper proportionate power exchange between the interlinking SHAFs using a decentralized method is necessary to
investigate.
To improve the system stability and not vary the droop values, a
novel reactive power-sharing approach is needed to be considered. This also helps to improve the dc-grid performances by
providing appropriate reactive power compensation.
There is a requirement for analytic evaluation to set the threshold values for power exchange by focusing on stability criteria,
power losses, system conditions, and efficiency, etc.
To avail accurate power at the respective busses, energy storage
controller improvement is very much required by considering
the higher and lower SOC limit.
Different signal processing and robust controller-based power
management structures are necessary to study during both
steady-state and transient state conditions.
7.2. Interlinking inverter
Exploring three-port interlinking SHAF based inverter topologies is much more worthwhile for facilitating multi-grid operations. Solid-state transformer-based approaches can be further
studied for interlinking operations.
167
B. Sahoo, M.M. Alhaider and P.K. Rout
Renewable Energy Focus 44 (2023) 139–173
Fig. 53. As per the types (a) Centralized controller. (b) Decentralized controller. (c) Distributed Controller.
Researchers are mostly emphasized only small-signal and
steady-state stability conditions during microgrid and AC-DC
grid application. Most important conditions such as larger signal and transient stability are needed to be considered.
Communication-based control stability estimation during loss,
error in data collection, and transient conditions are needed to
be developed.
7.4. Synchronized control
To improve the power quality and reliability, offer excellent
power management, and balance the voltage fluctuations,
advanced control strategies are needed to be examined. For
solving this problem, a hierarchical approach is more suited
for smart microgrid applications.
A preferably coordinated approach is necessary to investigate
for offering seamless transition among grid-connected and
islanded modes of operation. In addition to that, novel islanding
detection and better synchronization is also very much important factor during the controller design.
Better power management through distributed control is also
an important factor for real-microgrid applications.
Modified scalable and optimized communication methods are
required to investigate by reducing the component requirement,
conversion delay, and enhancing the power flow condition.
7.6. Power quality
There is a need to emphasize on the combination of power quality features along with power flow and management studies.
SHAF control strategy is needed to study during renewable
energy-based unbalanced grid and non-linear load applications.
The development of a suitable control strategy for reducing the
sub-grid effects on another microgrid due to voltage/current
fluctuation, droop variation, and load variations can be
emphasized.
7.5. Stability analysis
As the SHAFs are preferably used for developing the smart
microgrid system, the identification of possible unstable conditions and investigation of control stagey during that condition is
a tough task and necessary to focus on the hybrid microgrid system application.
Power researchers are giving less importance to considering the
stability analysis of microgrids during the verification of their
control application.
7.7. Protection
The protection aspect of the study having smart load and source
restoration and self-healing capability can be explored during
robust controller design.
Fault and transient limiting factors can be considered during
coordinated control design.
168
Renewable Energy Focus 44 (2023) 139–173
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8. Conclusion
The presented paper thoroughly reviewed and discoursed the
state-of-the-art of SHAF design and the related control strategies
for providing appropriate solutions to the AC/DC/Hybrid microgrid.
The significance of SHAF not only depends upon the harmonic
reduction and litheness in managing the dynamics of the system,
but also its progress depends on suitable power semiconductor
selection and suitable controller development at affordable cost.
The review has systematically been accomplished by comparing
and discussing various novel SHAF control algorithms for different
microgrid applications. The main objective of the review is to provide a complete overview of filter design and related control algorithms, by which the researchers can get the basic knowledge
about SHAF, and the related control techniques in a subjective
manner and ultimately increase their interest in future research
in this area. The review can be categorized into four specific categories as non-linearity extraction technique, DC-voltage control
technique, current regulation approach, and synchronization control technique. From the review, it is found that in real-time conditions, the presence of non-linearity in the source and load can be
eliminated by using the SHAF control technique. Table 4, Table 5,
and Table 6 summarize the controller applications like voltage
and frequency regulation, load management, battery and energy
management, power quality, stability, power generation, coordination, optimization, and SOC adjustment respectively. Therefore, it
is recommended to select an appropriate SHAF design and synchronized controller for handling adverse and dynamic grid conditions and the improvement of the controller can be emphasized as
a future aspect of microgrid development.
Data availability
No data was used for the research described in the article.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared
to influence the work reported in this paper.
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