Multi-Channel Networked MIMO-MPC-based SiL/HiL/MiL for
CC/CV Sections’ Optimization in 6th Gen Hybrid/Islanded Inverters for
Mobile Green Nano-Grids in FEW Nexus
HASAN TARIQ1, SHAFAQ SULTAN2
1Department of Electrical Engineering, College of Engineering,
Qatar University, Doha, QATAR
2Faculty Of Education, Allama Iqbal Open University
Islamabad, PAKISTAN
Abstract: - The Food, Energy, and Water (FEW) Nexus is an ever-existing paradigm since the big bang. Resilient
and mobile green energy nano-grid fabric is the horizon at the pinnacle of 6th generation inverters where FEW
and major UNDP SDGs seem to meet. Three major challenges exist in the existing inverters: a) are based on uni-
variable PID controllers and do not provide abstract grid parameters that make the decision-making for the
consumers and OEMs, especially in islanded nano-grids; b) there is not a single MIMO-MPC-based solution that
can employ a mesh network of spatially deployed Nanogrids nodes to derive the abstract key performance
indicators (KPIs) in nano-grids, and c) the hardcoded smart inverters’ firmware is impossible to optimize like
SoC-based SiL/MiL/MiL looped embedded systems that hamper the adaptation of SISO-MPC and MIMO-MPCs.
In this work design, development, and optimization of multi-channel CC/CV section modules based on MIMO-
MPC using Hardware in Loop (HiL), Software in Loop (SiL), and Model in Loop (MiL) integrated 6th generation
inverters architecture was proposed to achieve the autonomous green mobility nano-girds. The system achieved
an efficiency of 7.8kWh/day at 20.8ᵒ tilt with charging states of [23% to 65%].
Key-Words: - Energy, Power, Inverters, Grids
Received: March 5, 2022. Revised: October 8, 2022. Accepted: November 10, 2022. Published: December 27, 2022.
1 Introduction
The key motivation is improved quality of life and
survival as a contribution to energy for FEW Nexus
for global resilience and sustainability. Autonomy is
an obligation for every industry and especially
human survival which is a pressing need across the
globe being UNDP SDPs 1-3, 6-9, and 11-15, mainly
SDG-7 and SDG-9. Nanogrid's revenue will increase
from $37.8 billion in 2014 to $59.5 billion in 2023
and Nanogrid business has the potential to radically
change the power sector [1] as presented in fig 2 (a).
According to Navigant, Europe now has the largest
market for Nanogrids and is predicted to grow that
market by 41.7% CAGR (compound annual growth
rate) by 2024, going from 184.4 MW this year to
4,272.1 MW followed by Asia-Pacific with the
expected installation of 5,619.9 MW installed in
2024, a 46.3% CAGR [2] as presented in fig 1.
a. Hybrid/Stand-Alone Inverter Market Shift
b. Green Nano-Grid Market CAGR
Fig 1. Expected Market Sizes of Nano-Grids and
Inverters
The global inverter market is anticipated to grow
at a CAGR of 15.7% from an estimated USD 16.3
billion in 2022 to USD 33.8 billion by 2027 [3]. The
significance of multi-channel spikes by the global
green energy share stats in 2021 (93 GW for wind and
133 GW for solar), renewable electricity generation
grew steadily (+16% for wind and +23% percent for
solar) [4]. The entire paradigm is expected to shift to
green mobile nano-grids in coming years and can be
a lifesaver for extremely poor countries that still
don’t have basic food, water, and energy, these drive
extended research and optimization in this direction
[5]. Even in space research, these gaps were
addressed by the CubeSAT resilience concern [6].
International Journal on Applied Physics and Engineering
DOI: 10.37394/232030.2022.1.1
Hasan Tariq, Shafaq Sultan
E-ISSN: 2945-0489
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2 Problem Formulation
The following gaps were found in existing nano-
grid practices and orientation [7-9] literature
regarding 6th generation inverters as shown in fig 2.
In fig 1, a clear picture of the contribution
expected from this research is presented and will
have a huge impact on the green mobility-based FEW
Nano-grids as a scalable factor in their future market.
The role of electro-chemistry in conductors and
energy elements and materials’ structural health used
is worth mentioning as per contributions [10, 11].
The nine potential gaps were observed in
conventional PV inverters and are mentioned as:
a) There is not a single MIMO-MPC-based
solution that can employ a mesh network of
spatially deployed Nanogrids nodes to derive
the abstract key performance indicators
(KPIs) in nano-grids.
b) The existing inverters are based on uni-
variable PID controllers and do not provide
abstract grid parameters that make the
decision-making for the consumers and
OEMs, especially in islanded nano-grids.
c) The hardcoded smart inverters’ firmware is
impossible to optimize like SoC-based
SiL/MiL/MiL looped embedded systems that
hamper the adaptation of SISO-MPC and
MIMO-MPCs as addressed energy harvesting
[11] and the associated role of oxidation on
the conductors [12].
d) Local nano-grids use a single channel
approach, i.e. a single source of energy i.e.,
wind turbines or PV modules, and single
storage type like battery types, and rarely have
bi-directional AC/DC buses that are not a
competitive candidate for 6th generation
hybrid and islanded inverter applications as
infrastructure concern [13, 14] and electrodes
chemistry with pH issues [15].
e) The existing inverters systems have
challenges in their parametric calibration
(I/V/Hz, L, C, R, pF, %, Wh, Azimuthal
Source Φ, Ψ, and θ tracking, geo (Latitude,
Longitude, Altitude, and Windspeed) based
generation, and forecasting) and operational
adaptation that is a challenge in FEW mobile
nano-grids and any islanded application.
f) The mentioned challenge (e) leads further to a
lack of real-time resilience due to the absence
of redundancy options in the mobility of smart
systems [15]; ultimately energy professionals
have to visit the sites that are challenging in
harsh areas with electrode catalysis concerns
[16] and remote locations due to the absence
of remote power controller analytics.
g) Power/Energy scientists have a gap of
awareness in instrumentation and control
technology used in smart systems that effects
the multi-variable systems integration in
inverters due to the absence of Digital Twin in
existing power converter-controllers as well
Fig 2. Overview of Research Gaps
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DOI: 10.37394/232030.2022.1.1
Hasan Tariq, Shafaq Sultan
E-ISSN: 2945-0489
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as their environmental impact and air quality
issues [17, 18] and associated human health
[19].
h) The programming, calibration, and remote
access costs of the existing power converters
systems are huge and complex methods like
bipolar plates adaptation [20] challenge.
i) The existing power converter controllers have
gaps in real-time analytics on-chip which is
another setback costing the local consumers
and problematic for subject matter experts
(SME) that requires extra measuring
instruments and secure interoperability [21-
23] during control.
3 Research Methodology
A detailed literature survey for autonomous
British energy systems, green mobility conditions,
and food security constraints has been performed to
streamline the critical energy-environmental
variables and abstract parameters. The following
research approach has been devised:
2.1 Survey of MIMO Bi-Direction Power
Converters
The survey of the bi-directional MIMO power
converters in section 1 devised the following
directions:
Magnitudes, frequency, location, and nature of
AC/DC sources and converter topologies need to
be studied and reviewed.
Wind, PV/prime-mover, and multi-MPPT
channel cascade with programmable DC bus
options and control segments study.
Utility, Genset, and prime-movers synching for
programmable AC bus designs investigation.
Multi-PIDs and MIMO control strategies for
CV/CC equalization [24-27].
Storage and buffering sources (batteries and
super-capacitors) bi-directional conversion
approach.
Programmable DC-DC, DC-AC, AC-DC, AC-
AC, and synching UPS configurations
investigation.
2.2 Smart Power Converters KPIs:
Formulation of major KPIs to gauge the effect of
MIMO bi-directional converters and their support for
FEW services as a collaborative FEW-Grid
Resilience Index (CFGRI) using the KPIs presented
in works [28, 29] from the perspective of resilience
in the energy efficiency of MIMO power drives
communication systems.
2.3 System design
The Selection of potential and stable sensors and
controllers (with better outdoor life) for real-time
measurement of variables and critical data
processing procedures and statistical evaluations
to compute real-time CFGRI [30, 31].
Design of flexible/programable transformer-less
smart converter with embedded IoT gateway
system to achieve the required degree of
autonomy by improved deep learning approaches
for embedded IoT systems [32].
Design and Model the multi-PIDs into MPC
equivalents and implement them on the Smart
Converters Topologies by validating on
programmable power supplies [33].
Design, Develop and Fabricate a Digital Twin
with HiL/SiL/MiL Loop using Proteus,
MATLAB, Physical System, and FEW Nano-
Grid Test Bench.
The fault codes and digital calibration certificates
(DCCs) using wireless consensus and temperature
concerts for the entire deployment will also be taken
into account based on the meteorological data as
shown in the results section.
2.3 Measurement and Validation:
The developed system will be deployed in selected
farms for measurement and data analysis.
2.4 Case Studies and Evaluation
The survey of the bi-directional MIMO power
converters in following case studies.
2.4.1 Case Study 1
Static long-haul free-run in the geometrically
classified field for stationery and mobile outdoor
system evaluation over Digital Twin Test Bench
(presented in fig 3).
Fig 3. Complete System Implementation Layout with
Case Study 1: Static Evaluation Test bench
International Journal on Applied Physics and Engineering
DOI: 10.37394/232030.2022.1.1
Hasan Tariq, Shafaq Sultan
E-ISSN: 2945-0489
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2.4.2 Case Study 2
Mobile deployment for outdoor sensing and
communication system evaluation for CFGI
Mapping for geo-spatial evaluation ((presented in fig
4).
Fig 4. Complete System Implementation Layout
with Case Study 2: Mobile Evaluation
In the second case study the 6th Generation Inverters
Testbench will be installed on a Mobile EV and given
a free run in outdoors to validate:
A/V/Wh Generation Optimization based on
Typography/Terrain.
A/V/Wh Generation vs Autonomous Green
Mobility.
A/V/Wh Generation vs FEW Services.
Based on the outcomes of this research and
developments in this research a startup company 1
will be initiated for 6th Generation Smart Inverters
based hybrid and the Autonomous Mobile FEW
Nano-Grid platform will be developed through a
research grant leading to a startup company 2.
4 Results and Discussion
The system design spiking statistics are presented in
a systematic manner from fig 5 to fig 10. Being a
FEW based application the first step was the
geographical site study using NMEA coordinates as
mentioned in the problem statement.
The site chosen for simulation was Turaynah and its
meteorological data was studied using online web
data (https://qweather.gov.qa/CAA/Index.aspx)
based on that data the irradiance study was performed
for sun trajectories over the course of a year as shown
in figure 6.
Fig 6. Site Meteorological Data
The next step in this FEW works was the clearness
index study and its convolution with the sun hours
and its path as presented in the figure 7.
Fig 7. FEW-based Clearness Index for different
positions of the sun.
As per the green block “cognitive tracking” in fig 3,
it was mandatory to calculate the inter-shading effect
of PV resources during the tracking process based on
the sun height. For this, we used the cascaded shading
mechanism inter-angular estimation presented in
figure 8.
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Hasan Tariq, Shafaq Sultan
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Fig 8. Inter-PV array shading estimation
The profile angle 20ᵒ can be observed in fig 8 for 0.8
deviation which is near optimal. After the static inter-
shading effect, the dynamic tilting effect with
transposition and irradiance was the major estimation
required to estimate the impacts of tracking in the
case of studies 1 and 2. In fig 9, it can be observed
that the maximum shading loss of 1.7% was observed
at 30ᵒ tilt which was a fraction of 45.5% of the annual
energy profile for the same meteorological influx. In
fig 9, pure transposition is expressed as a green curve,
irradiation at 20.8ᵒ with black, and the for cell 15.6cm
of 3 strings as orange curve.
Fig 9. Tilt Optimization Estimation at 20.8ᵒ being an
optimal fraction
The horizontal diffusion factor at 20.8ᵒ was estimated
as optimal from 85ᵒ to 90ᵒ for sun height and with -
90ᵒ to 90ᵒ and maximum on Jun 22 at 1:22 pm and
can be seen the fig 10.
Fig 10. Mutual Shading and Horizontal Diffusion
Estimation for 24 hours at 7 sun positions.
The PV efficiency was estimated using the 265W
panel model in PVSyst with 6M-30S consisting of 60
cells and compliance 1000W/m2 solar constant. The
irradiance estimation for this model is presented for
different irradiance conditions at 45ᵒ C temperature
that varies the watts per m2 from 200 to 1000. The
maximum power generated by this using model was
242W at 28V and the minimum was 46.8W at 27V
presented in figure 11. The values vary from location
to location based on the meteorological data and tilt
angles. In this study 20.8ᵒ tilt angle was used as the
optimal power point.
Fig 10. PV Module Power Estimation Simulation.
The step of individual PV module power estimation
was the estimation of the complete PV system from
Jan 1, 2022, to Dec 31, 2022, and is presented in
figure 11.
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DOI: 10.37394/232030.2022.1.1
Hasan Tariq, Shafaq Sultan
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Fig 11. PV Array Power Distribution from Jan 1 to
Dec 31, 2022.
In fig 11, it can be observed that the peak as MIMO-
MPC based MPPT used in the system it touched the
1700.6MW using the per unit system kW/h energy
unit standard. The state of charge for this energy
magnitude was the next step as shown in the fig 12.
Fig 12. State of Charge for Battery Bank
In fig 12, it can be observed that the lowest state of
charge was observed as 0.24 in the last week of
January and the maximum was observed in the third
week of June as 0.60+. In July the charging and
discharging balance was observed, i.e. [0.63 to 0.41].
Fig 13. Daily Effective Energy output of FEW
Nano-Grid
Before feeding the FEW Nano-Grid to any food or
water service system the daily output efficiency
estimation is the last step to conclude its productivity
as a resilient energy alternative for food and water
systems energy need services as shown in figure 13.
This system can deliver an average of 7.3kWh per
day with some exceptions in the last week of April
and mid of November.
5 Conclusion
The presented research, system design, and
simulation produced promising results as energy
alternatives for FEW units. The electrical,
mechanical, and meteorological variables were fed to
the MIMO-MPC controller which helped in real-time
estimations and computation of the SiL/MiL/HiL
models. Such systems are expected to serve the
energy needs of the food and water sector in a
resilient manner as per the results presented. In the
future we are planning to develop a cyber-physical
MIMO-MPC 6th generation inverter that can deliver
the simulated results with certain variations.
Acknowledgement:
This research was based on personal effort and was
not funded by any funding agency.
References:
[1] https://eepower.com/news/nanogrid-market-to-
reach-nearly-60-billion-annually-by-2023/.
[2] https://solarlove.org/revenue-global-solar-pv-
energy-storage-nanogrid-expected-reach-23-1-
billion/
[3] https://microgridknowledge.com/microgrid-jr-
comes-of-age-the-rise-of-the-solar-plus-
storage-nanogrid/
[4] https://www.globenewswire.com/news-
release/2022/06/13/2460957/0/en/The-inverter-
market-is-anticipated-to-grow-from-an-
estimated-USD-16-3-billion-in-2022-to-USD-
33-8-billion-in-2027-at-a-CAGR-of-15-7.html
[5] Eko Adhi Setiawan and Novagia Adita. Hybrid
nanogrids development to improve residential
reliability and resiliency supply: Testing and
implementation, Energy Reports, Volume 8,
Supplement 3, June 2022, Pages 284-290 2022.
[6] Mohammad Yaqoob et al. Self-directed Energy
Management System for an Islanded Cube
Satellite Nanogrid, IEEE Aerospace
Conference, 2020.
[7] Hasan Tariq, Farid Touati, Mohammed A. E.
Al-Hitmi, Damiano Crescini, and Adel Ben
International Journal on Applied Physics and Engineering
DOI: 10.37394/232030.2022.1.1
Hasan Tariq, Shafaq Sultan
E-ISSN: 2945-0489
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Volume 1, 2022
Mnaouer, Design and Implementation of
Programmable Multi-parametric 4-degrees of
Freedom Seismic Waves Ground Motion
Simulation IoT Platform. 15th International
Wireless Communications & Mobile Computing
Conference, 2019.
[8] Syed Javaid Zaidi, Mukhtar Bello, Amir Al-
Ahmed, Ammar Bin Yousaf, and M. Imran.
Mesoporous carbon supported Pt/MO2 (M=Ce,
Pr, Nd, Sm) heteronanostructure: Promising
non-Ru methanol oxidation reaction catalysts
for direct methanol fuel cell application.
Journal of Electroanalytical Chemistry,
Volume 794, 2017, Pages 86-92, ISSN 1572-
6657.
[9] Hasan Tariq, Farid Touati, Mohammed Abdulla
E Al-Hitmi, Anas Tahir, Damiano Crescini, and
Adel Ben Mnaouer, Structural Health
Monitoring and Installation Scheme
Deployment using Utility Computing Model.
2nd European Conference on Electrical
Engineering and Computer Science, 2018.
[10] Yad Tahir, Shusen Yang, Usman Adeel, Julie
McCann. Symbiot: Congestion-driven multi-
resource fairness for multi-user sensor
networks. IEEE 17th International Conference
on High Performance Computing and
Communications, IEEE 7th International
Symposium on Cyberspace Safety and Security,
and IEEE 12th International Conference on
Embedded Software and Systems, 2015. DOI:
10.1109/HPCC-CSS-ICESS.2015.23.
[11] M. Chitra Devi, L. Rajendran, Ammar Bin
Yousaf, and C. Fernandez. Non-linear
Differential Equations and Rotating Disc
Electrodes: Padé approximation Technique.
Electrochimica Acta, Volume 243, 2017, Pages
1-6, ISSN 0013-4686.
[12] Hasan Tariq, Abderrazak Abdaoui, Farid
Touati, Mohammed Abdulla E Al-Hitmi,
Damiano Crescini, and Adel Ben Mnaouer, An
Autonomous Multi-variable Outdoor Air
Quality Mapping Wireless Sensors IoT Node
for Qatar. IEEE International Wireless
Communications & Mobile Computing
Conference, 2020.
[13] Ammar Bin Yousaf, M Imran, Peter Kasak,
Fathima Sifani Zavahir, Syed Javaid Zaidi, and
Carlos Fernandez. Enhanced and durable
electrocatalytic performance of thin layer PtRu
bimetallic alloys on Pd-nanocubes for methanol
oxidation reactions. Catalysis Science &
Technology, 2017.
[14] S. Yang et al. The Design of User-Centric
Mobile Crowdsensing with Cooperative D2D
Communications. IEEE Wireless
Communications, 2022. Vol. 29, no. 1, pp. 134-
142. DOI: 10.1109/MWC.2018.1600445.
[15] Farid Touati, Hasan Tariq, Mohammed A Al
Hitmi, Adel Ben Mnaouer, Anas Tahir, and
Damiano Crescini. IoT and IoE prototype for
scalable infrastructures, architectures and
platforms. International Robotics & Automation
Journal, 2018.
[16] Jaroslav Mosnáček, Anton Popelka, Josef
Osicka, Jaroslav Filip, Marketa Ilcikova, Jozef
Kollar, Ammar B Yousaf, Tomas Bertok, Jan
Tkac, and Peter Kasak. Modulation of
wettability, gradient and adhesion on self-
assembled monolayer by counterion exchange
and pH. Journal of colloid and interface
science, 2018.
[17] Muhammad Umar, Usman Adeel & Sajid
Qamar. Routing Protocols. In: Mahalik, N.P.
(eds) Sensor Networks and Configuration,
2007. Springer, Berlin, Heidelberg.
https://doi.org/10.1007/3-540-37366-7_7
[18] Abderrazak Abdaoui, Sabbir HM Ahmad,
Hasan Tariq, Farid Touati, Adel Ben Mnaouer,
and Mohammed Al-Hitmi. Energy efficient real
time outdoor air quality monitoring system.
2020 International Wireless Communications
and Mobile Computing (IWCMC), 2020.
[19] Mazen K Nazal, Olanrewaju Suleiman
Olakunle, Amir Al-Ahmed, Belabbes
Merzougui, Abdullah Abualkibash, Abdullah
Sultan, Ammar Bin Yousaf, and Syed Javaid
Zaidi. Precious metal free Ni/Cu/Mo trimetallic
nanocomposite supported on multi-walled
carbon nanotubes as highly efficient and durable
anode-catalyst for alkaline direct methanol fuel
cells. Journal of Electroanalytical Chemistry.
Volume 823, 15 August 2018, Pages 98-105.
[20] Abderrazak Abdaoui, Farid Touati, Hasan
Tariq, Adel Ben Mnouar. A smart rig for
calibration of gas sensor nodes: Test and
deployment. 2020 IEEE International
Conference on Design & Test of Integrated
Micro & Nano-Systems (DTS), 2020.
[21] Hasan Tariq and Shafaq Sultan. Real-time
Contactless Bio-Sensors and Systems for Smart
Healthcare using IoT and E-Health
Applications. WSEAS Transactions on Biology
and Biomedicine, 2022.
[22] Majid Niaz Akhtar, Abu Bakar Sulong, A Umer,
Ammar Bin Yousaf, and Muhammad Azhar
International Journal on Applied Physics and Engineering
DOI: 10.37394/232030.2022.1.1
Hasan Tariq, Shafaq Sultan
E-ISSN: 2945-0489
7
Volume 1, 2022
Khan. Multi-component MWCNT/NG/EP-
based bipolar plates with enhanced mechanical
and electrical characteristics fabricated by
compression moulding. Ceramics International,
2018.
[23] Hasan Tariq and Shafaq Sultan. A Secure
Interoperable API Wrapper Tunnel for
Integration of GIS-Based ICS-IIoT and Digital
Twins in Industry 4.0 Clouds. WSEAS
Transactions on Computers, 2022.
[24] Verónica Gutiérrez, Evangelos Theodoridis 2 ,
Georgios Mylonas, Fengrui Shi, Usman Adeel,
Luis Diez, Dimitrios Amaxilatis, Johnny
Choque, Guillem Camprodom, Julie McCann
and Luis Muñoz. Co-Creating the Cities of the
Future. Sensors, 2016. DOI:10.3390/s16111971
[25] Amith Khandakar, Abir Touati, Farid Touati,
Abderrazak Abdaoui, Ammar Bouallegue.
Experimental setup to validate the effects of
major environmental parameters on the
performance of FSO communication link in
Qatar. Applied Sciences, 2018.
[26] Abir Touati, Farid Touati, Abderrazak Abdaoui,
Amith Khandakar, Syed Jawad Hussain,
Ammar Bouallegue. An experimental
performance evaluation of the hybrid FSO/RF.
Free-Space Laser Communication and
Atmospheric Propagation XXIX, 2017.
[27] Abderrazak Abdaoui, Tarek M El-Fouly.
TOSSIM and distributed binary consensus
algorithm in wireless sensor networks. Journal
of Network and Computer Applications, 2014.
[28] Farid Lahrach, Abderrahim Doumar, Eric
Châtelet, Abderrazek Abdaoui. Master-slave
TMR inspired technique for fault tolerance of
SRAM-based FPGA. 2010 IEEE Computer
Society Annual Symposium on VLSI, 2010.
[29] Abderrazek Abdaoui, Marion Berbineau,
Hichem Snoussi. GMRES Interference
Canceler for doubly iterative MIMO system
with a Large Number of Antennas. 2007 IEEE
International Symposium on Signal Processing
and Information Technology, 2007.
[30] Abderrazak Abdaoui, Abdulla Al-Ali, Ali Riahi,
Amr Mohamed, Xiaojiang Du, Mohsen
Guizani. Secure medical treatment with deep
learning on embedded board. Energy Efficiency
of Medical Devices and Healthcare
Applications, 2020.
[31] Hasan Tariq, Abderrazak Abdaoui, Farid
Touati, Mohammad Abdullah Al Hitmi,
Damiano Crescini, Adel Ben Mnaouer. Real-
time gradient-aware indigenous AQI estimation
IoT platform. Advances in Science, Technology
and Engineering Systems Journal. Vol. 5, No. 6,
1666-1673, 2020.
[32] Abderrazek Abdaoui, Tarek M Elfouly.
Distributed binary consensus algorithm in
wireless sensor networks with faulty nodes.
2013 7th IEEE GCC Conference and Exhibition
(GCC), 2013.
[33] Abir Touati, Abderrazak Abdaoui, Farid Touati,
Murat Uysal, Ammar Bouallegue. On the
Effects of Temperature on the Performances of
FSO Transmission under Qatar's Climate. 2017
IEEE 85th Vehicular Technology Conference
(VTC Spring), 2017.
Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
Hasan Tariq proposed and designed the 6th generation
PV-Wind hybrid inverters research.
Shafaq Sultan performed the simulation and results.
Sources of funding for research presented in a
scientific article or scientific article itself
Self-Funded.
Creative Commons Attribution License 4.0
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International Journal on Applied Physics and Engineering
DOI: 10.37394/232030.2022.1.1
Hasan Tariq, Shafaq Sultan
E-ISSN: 2945-0489
8
Volume 1, 2022