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This paper is presented in 32nd Annual Newfoundland Electrical and Computer Engineering Conference (NECEC-2023) IEEE
Dynamic Modelling and Analysis of a Hybrid
Power System of Floating Solar PV System for
an Offshore Aquaculture Site in Newfoundland
Abstract—In this article a hybrid power system, a combination of
solar and diesel generator (DG) is modeled in
MATLAB and the dynamic performance of the system are analyzed
considering the design parameters. The
said system is designed for an offshore aquaculture site located in
Newfoundland, Canada. The paper presents a novel concept of
evaluating the dynamic performance of floating solar PV panels over
the water surface of the fish farm. The sizing and economic feasibility
of the system were carried out on HomerPro. Design is modeled in
MATLAB to analyze the impact of dynamic changes on system
performance. The system is exposed to variable irradiance,
temperature, and load side variations and simulated under each
condition. The results presented here confirm the satisfactory and
reliable response of the system in all scenarios. The designed system
shall replace the existing power source (diesel gen) with green and
economical energy resources and will be a great help to bring
sustainability in the Canadian aquaculture industry.
Keywords—Hybrid power system, Aquaculture, Floating solar PV
power system, HomerPro, dynamic modeling
I. INTRODUCTION
By developing the first civilized cities nearby the fresh
waters, we can see the history of fishery and the contribution of
marine foods in the human diet. The economy and policy of many
developed countries tie to this industry since the fisheries and
aquaculture sectors contribute to combat with challenges of
universal food security and bring economic benefits.
As of now, wild fisheries have a greater contribution to the
total production. Therefore, aquaculture business should be
encouraged so that the devastating effect of overfishing on the
marine environment and ecosystem can be minimized.
Aquaculture is embracing the latest technologies and many new
advancements are being made to improve the yield and lower the
operational cost and the environmental footprints. The availability
of appropriate energy sources is inevitable to bring enhancement
in the production capacity, and sustainability to achieve future
goals.
We must consider that energy plays a major role in fish farms.
For instance, components like feeders, aerators, air compressors,
lighting, and refrigerators are energy-intensive and need electricity
to operate. Renewable and Non-renewable energy sources are the
two different categories of energy sources in the world. The
carbon emissions from renewable energy sources are very low or
nonexistent, making them environmentally benign. Non-
renewable resources are harmful to the environment and cause
global warming.
II. LITERATURE REVIEW
Land-based (freshwater) and offshore (seawater) fish farms
are the two main categories of aquaculture activities. The offshore
fish farm cages are located inside the sea from 2km to 25km from
the coast. The cluster of cages is formed and a feeding barge
containing all the necessary operational equipment is anchored
near the cages. The automated monitoring and feed system form
an integral part of offshore aquaculture that provides regulated
feed and helps to monitor the health, and growth of fish inside the
cages. The system is primarily comprised of feed blowers, sensors
(dissolved oxygen (DO), salinity, pH, etc.), cameras, and a
centralized monitoring/control system. At the bottom of the fish
enclosure, an aeration system is deployed which diffuses air and
causes oxygen-rich water to travel upward in the pen.
The energy demand of offshore fish farms is usually fulfilled
by feed barges [1]. The feed barge is an integrated mobile setup
that houses all the necessary equipment/setup to run the operations
of the fish farm including the feeding system, air compressors for
aeration, silos to store the feed and staff accommodation, and DGs.
Further, the energy needs of an offshore fish farm site located in
the Mediterranean Sea having underwater lighting, sensors,
cameras, and remote video is recorded as 4783.88 Whr/day [1].
The usage of solar power for the aquaculture industry has
been increasing significantly each day due to minimized
operational costs, environmentally friendly nature, and low soil
contamination [2]. The presence of solar energy systems in land-
based fish farms is quite convincing and discussed here. An off-
grid solar system was developed to completely power up the fish
farm along with its monitoring system (PLC & HMI) [3], the yield
of the fish farm is increased by maintaining the temperature of the
fish cage. An automated and solar-powered fish farm management
system with of aim of fish conservation is designed by Fourie [4].
Muhammad Nadeem Asgher
Department of Electrical Engineering
Memorial University of Newfoundland
St. John’s, NL, Canada
mnasgher@mun.ca
Mohammad Tariq Iqbal
Department of Electrical Engineering
Memorial University of Newfoundland
St. John’s, NL, Canada
tariq@mun.ca
This paper is presented in 32nd Annual Newfoundland Electrical and Computer Engineering Conference (NECEC-2023) IEEE
Installing solar photovoltaic systems over water bodies
utilizing floating technology is a novel concept. Depending on the
solar cell type and weather, a typical PV module converts 4–18%
of the incident solar radiation into electricity. The remaining solar
radiation that strikes the PV is transformed into heat, which
sharply raises its temperature. The power production of solar cells
changes as the temperature changes. Due to this dependence on
temperature, solar PV systems built on the surface of water benefit
from significantly lower ambient temperatures due to the cooling
action of water. On average efficiency of floating-type solar panels
are 11% higher compared to ground-installed solar panels [5].
Thus, the implementation of floating PV panels seems to be a
complete match to expand the blue economy.
III. MATHEMATICAL MODELING OF A HYBRID
SYSTEM
A. SYSTEM SIZING
A location for an offshore fish farm project has been chosen
in Newfoundland, Canada, close to Red Island in Placentia Bay,
refer to Fig. 1. It has a total of eight fish cages and circumference
of each cage is 160 m. The actual energy demand (kWh/day) is
collected from the site, given as input to HomerPro software and
the techno-commercial feasibility of the designed system is carried
[6]. The schematic of the designed system can be seen in Fig. 2.
Canadian Solar-made CS6U-340M PV panels are selected, please
refer to Table 1 for a list of key specifications/details of the system.
Fig. 1. Project Site (Offshore Fish Farm)
Fig. 2: Schematic of the Designed System
Table 1: List of key Specifications of System
Sr Description Unit/Symbol Value
1 Total Designed Solar
Power by HomerPro kW 366
2 Nominal Max. Power
of Single PV Module W/Pmax 340
3 Total No. of PV
Modules No 1077
4 Battery Bank Size kWhr 542.1
5 Nominal Capacity of
One Battery Cell kWhr 1.39
6 Total No. of Battery
Cells No 390
7 DC Bus Voltage VDC 360
8 AC Bus Voltage
(Phase-Phase) VAC 208
9 Total Load kW 80
10 Diesel Generator
Rating kVA 99
B. MAXIMUM POWER POINT TRACKING
The energy output of the PV cells is largely dependent on the
location of the sun and the resultant sun rays’ direction. Any
change in the location and rays of the sun would have a direct
consequence on the power produced by solar cells. Further to this,
the relation between I-V and P-V is not linear in the case of PV
cells. Therefore, the output of the PV cells is constantly changing.
The analysis of the P-V & I-V curve of the PV states that there is
only one specific and unique point where the most optimized
power can be obtained from the module, called the “maximum
power point (MPP). The power produced by the cell on either side
of the MPP would be less and hence to improve the conversion
efficiency of PV installation it is very necessary to track that point
and ensure the operation of PV cells on MPP.
The maximum power point tracker (MPPT) is a device,
essentially a DC-DC converter, equipped with an intelligent
algorithm in a microprocessor that helps to track the output power
of a PV array, the MPPT finds the optimal power output point and
ensures the operation of the PV cells at that particular point. Since
PV cells are exposed to fairly changing irradiance and
temperature, MPPT remains constantly busy in finding the MPP
with respect to changing weather. Further to this, any change in
load (resistance) also causes MPP to change and the power output
of PV cells is no longer optimized. The model of the PV system
along with a MPPT controller is shown in Fig. 3.
There are many prevalent techniques/algorithms to track the
MPP i.e., Perturb & Observe (P&O), Hill Climbing, Incremental
Conductance (INC), and Neural Network Control. The INC
This paper is presented in 32nd Annual Newfoundland Electrical and Computer Engineering Conference (NECEC-2023) IEEE
algorithm is applied in this paper considering its superior
performance in tracking the MPP in changing weather conditions,
reliable robustness, and accuracy. In addition, INC offers better
efficiency and is easy to implement, as well.
MPPT Algo rithm
+
_
I
PWM
Controller
VGate
u
I
ref
e
I
Load
PV Panel DC-DC
Converter
Fig. 3. PV system along with MPPT Controller
INC algorithm follows a key point that the slope of the P-V
curve of the PV module is zero at MPP (
= 0). To find the MPP,
the algorithm is designed to compare the incremental conductance
(
) with the array conductivity (
). The fundamental equation
driving the operation of INC is as follows
𝛥𝑃
𝛥𝑉 =𝛥(𝑉𝐼)
𝛥𝑉 = 𝐼 𝛥𝑉
𝛥𝑉 + 𝑉 𝛥𝐼
𝛥𝑉 = 𝐼 + 𝑉 𝛥𝐼
𝛥𝑉
1
𝑉×𝛥𝑃
𝛥𝑉 =𝐼
𝑉+𝛥𝐼
𝛥𝑉
The PV Module’s output power is differentiated with respect to
voltage and equated to zero to get the Incremental Conductance.
Following are the key relationships that derive the operation of the
INC algorithm. 𝛥𝐼
𝛥𝑉 = 1
𝑉 𝑎𝑡 𝑡ℎ𝑒 𝑀𝑃𝑃
≥
𝐿𝑒𝑓𝑡 𝑆𝑖𝑑𝑒 𝑜𝑓 𝑡ℎ𝑒 𝑀𝑃𝑃
𝛥𝐼
𝛥𝑉 ≤ 1
𝑉 𝑅𝑖𝑔ℎ𝑡 𝑆𝑖𝑑𝑒 𝑜𝑓 𝑡ℎ𝑒 𝑀𝑃𝑃
The complete system consists of PV system, MPPT controller,
inverter, battery bank, synchronous generator, and variable load
is modeled in MATLAB/Simulink, refer to Fig. 4. Some of the
key parts of the modeled system are explained below.
C. DC-DC CONVERTER
DC-DC converter is implied in the system as part of the multi-
stage power processing system. The converter has a pivotal role in
achieving the MPP of PV modules, the output is DC voltage, and
it is exposed to handle small power only [7]. DC-DC converter
along with the DC-AC inverter forms the multi-stage system and
this configuration offers the freedom of operation of PV voltage
in a wide range. Further, it also uncouples the direct connection
between AC output and PV module so that a double-line-
frequency ripple of PV voltage is not induced by AC power swell.
The buck converter is used as a DC-DC converter due to its
high efficiency, simple configuration, and low voltage ripple. The
DC output voltage level in accordance with the inverter DC link is
maintained by the buck converted which is 360V DC in our case.
The output voltage (𝑉) is lower than the input voltage (𝑉) and
this is achieved by controlling the duty cycle (D) of switch S, the
duty cycle is a scalar that has a value between 0 & 1. The important
equations describing the operation and designing of Buck
converter are as follows
𝑉= 𝐷. 𝑉
𝐿 = 𝑉×(𝑉− 𝑉)
𝛥𝐼× 𝑓
× 𝑉
𝛥𝐼 is the inductor ripple current which is taken as any value
between 0.2-0.4 of maximum output current. The output
capacitor is designed to lower down the ripples on the output
voltage and it is designed considering the following expression.
𝐶 = 𝛥𝐼
8 × 𝑓
× 𝛥𝑉
The values of the inductor and capacitor computed according
to the above-said equations are 0.346mH & 1.2mF,
respectively.
D. DC-AC INVERTER
Stable DC output from the buck converter is fed to the three-
phase Voltage Source Inverter (VSI) which converts it to the
desired AC voltage i.e. 208V (phase-phase). Among various
available PWM techniques, Sinusoidal Pulse Width Modulation
Technique (SPWM) is used because of its unique offerings i.e. low
Total Harmonic Distortion (THD), simplicity and better
controlling schemes. The desired output voltage waveform and
reduction in THD is achieved by controlling the width of SPWM
pulses. THD is a very relevant and concerned parameter when non-
linear components are involved, most of the semiconductor devices
which are the heart of renewable energy systems, depict non-linear
behavior. Therefore, the combination of SPWM and filters
provides a great solution in the reduction of harmonics and
resultant losses. SPWM reduces the low-order harmonics and
filters are used to reduce high-order harmonics [8].
E. LCL FILTER
The level of power quality supplied to the load is gaining
more and more attention due to its direct effects on the
(3)
(4)
(9)
(8)
(10)
(5)
(6)
(7)
This paper is presented in 32nd Annual Newfoundland Electrical and Computer Engineering Conference (NECEC-2023) IEEE
performance of the connected load. Higher the power quality,
lower the losses and better the performance of load. As discussed
above, filters are necessary to control and eliminate the higher-
order harmonics. LCL filter is used to reduce the harmonic
distortion in the inverter output waveform and low ratings of
inductor and capacitor are used to make the system more
economical.
Designing of LCL filter is a complex process and it starts with
computing the inverter side inductor with the help of the following
equation.
𝐿=𝑈
16 × 𝑓
× 𝛥𝐼
𝑓
is the frequency of the system and DC bus voltage is represented
by 𝑈. 𝛥𝐼 is referred to as current ripple and can be computed by
following equation.
𝛥𝐼 = 0.1 ×𝑃𝑛 ×√2
𝑉
The value of DG side inductor Lg and filter Capacitor 𝐶, are
computed according to the following equations.
𝐿= 0.6 × 𝐿
𝐶=
×
The value of the inductor and capacitor computed according to
above-said equations are 0.450mH & 0.081mF, respectively.
IV. MODELING OF COMPLTE SYSTEM IN
MATLAB/SIMULINK
The individual modeling of all the components described
above in section III is put together and a complete model is
assembled on MATLAB/Simulink, refer to Fig. 4, which is a very
useful tool to model the actual behavior of components/equipment
through block-based programming and mathematical relationship.
The complete PV system consists of 72 parallel and 15 series
strings, each module is of 340W (CanadianSolar CS6U-340M).
The battery bank comprised of 1365Ah (542.1kWh), each battery
is 12V & 105Ah (1.39kWh). There are 30 batteries connected in
series and 15 parallel strings. Although the PV system can fulfil
the energy demand of the selected site but due to the intermittent
nature of renewable energy sources, a backup DG is also
considered to improve the reliability of the power system.
Although the originally system doesn’t need such a large rating of
DG but the existing infrastructure of the site has 99kVA
synchronous DG so, the same is considered in the model. The real-
time model of the synchronous DG is developed in MATLAB to
address the possible constraints of synchronization with PV
system and smooth power flow to the variable load. The control
system is developed for the DG to regulate its operation and to
gain more precise control on active power generation according to
design parameters. Further, the controller also ensures a robust
response against all possible real-time load variations.
Fig. 4. Complete System Modelled in MATLAB/Simulink
Since power output of PV is largely dependant on weather
(irradiance and temperature), which is always changing, therefore,
the analysis of changing weather on PV power output and its
corresponding affect on whole power system network is very
necessary. The dynamic response of system is evaluated by
exposing it to variable irradiance and temperature, refer to Fig 5.
The response time and behaviour of system is found satisfactory.
MPPT controller is efficiently achieving MPP despite of drastic
changes in weather and ensuring maximum power generation from
PV in all cases. The PV power generation following the variable
irradiance and temperature can be seen in Fig. 6.
Fig. 5. Variable Irradiance and Temperature
Fig. 6. PV Voltage and Current due to inputs shown in Fig. 5
(11)
(13)
(14)
(12)
This paper is presented in 32nd Annual Newfoundland Electrical and Computer Engineering Conference (NECEC-2023) IEEE
Fig. 7. Battery Charging and Discharging
Fig. 8. Variable Load (Load Switching)
Fig. 9. PV, Generator and Load Current
The power flow from PV to load is the priority and in case of
excess power, the battery bank is charged. If PV is not producing
enough power to meet the load demand then DG is capable of
supplying the deficit and excess power shall again charge the
battery bank, refer to Fig. 7. Synchronization of PV and DG is
achieved using Phase-Lock Loop (PLL). But to ensure fuel
optimization, DG only comes to action if the load is more than
30%.
The total load of the aquaculture site is 80 kW which is a
combination of three feed blowers (30kW, 22kW & 22kW) and
6kW is the auxiliary load (lights, sensors, etc).In the real world,
the load is always changing as well and variation of load could
also impact and disturb the operation of power sources and
network Therefore, the variability of load is applied, refer to Fig.
8 and its impact is analyzed. The response time of the system is
found satisfactory and both power sources (PV and Gen) are
capable of supplying power smoothly to the variable load in
changing weather conditions, refer to Fig 9. The load demand is
primarily fulfilled by PV (inverter current).
V. CONCLUSION
The results presented here prove the satisfactory response of
the designed system against all possible dynamic changes. The
MPPT is found very efficient in tracking and achieving the MPP
despite of variations in weather. The controller for the
synchronous generator is very robust to respond to the changes in
load, managing the mechanical inertia of DG accordingly, and
coordinating with PLL to ensure smooth synchronization with the
PV system. The results endorse the profoundness of the overall
performance of the designed system and further confirms the
capability of the designed PV system to fully meet the energy
needs of fish farm and reliance on DGs can be minimized to the
lowest possible value. It would not only bring environmentally
friendly and economical energy but would reduce the operational
cost and enhance the sustainability of Canadian aquaculture
industry.
REFERENCES
[1] Menicou, M., & Vassiliou, V. (2010). Prospective energy needs in
Mediterranean offshore aquaculture: Renewable and sustainable energy
solutions. Renewable and Sustainable Energy Reviews, 14(9), 3084–3091.
https://doi.org/10.1016/j.rser.2010.06.013
[2] Al-Saidi, M.; Lahham, N. Solar energy farming as a development
innovation for vulnerable water basins. Dev. Pract. 2019, 29,619–634
[3] Bayrak G, LebeliM(2011) A PV based automation system for fish farms: an
application study. In 2011 7th International conference on electrical and
electronics engineering (ELECO). IEEE
[4] Fourie CM et al (2017) A solar-powered fish pond management system for
fish farming conservation. In 2017 IEEE 26th International symposium on
industrial electronics (ISIE). IEEE
[5] Choi Young-Kwan. A study on power generation analysis of floating PV
system considering environmental impact. 2014;8(1):75–84.
[6] Asgher, M.N., Iqbal, M.T. (2023). Design and Simulate a Floating Solar
Photovoltaic System for an Offshore Aquaculture Site in Canada. Jordan
Journal of Electrical Engineering
[7] H. B. Massawe, “Grid Connected Photovoltaic Systems with SmartGrid
functionality,” M.S. Thesis, Dept.ElKraft, NTNU, Trondheim, Norway,
2013
[8] Sahoo, Sarat Kumar, A. Ramulu, Saachi Batta, and Shweta
Duggal."Performance analysis and simulation of three phase voltage source
inverter using basic PWM techniques." In International Conference on
Sustainable Energy and Intelligent System. SEISCON 2012, IET 2012,
pp.257-263.
