







































S. Hema et al. /Future Technology                                                                                                   May 2025| Volume 04 | Issue 02 | Pages 
11-21 

11 

 

 

 

Article 

Hybrid boost-cuk converter with bat-chicken 

swarm-optimized PI controller for photovoltaic 

grid systems 
S. Hema1*, S. Sreedevi2, K. Harinath Reddy3, Siddheswar Kar4, Ananthan Nagarajan5,  

S. Sengottaian6 

1Department of Biomedical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, 

Chennai-600062, India 
2Department of Electrical and Electronics Engineering, Sriram Engineering College, Perumalpattu - 602 024, India 
3Department of Electrical and Electronics Engineering, Annamacharya University, Rajampet, India 
4Department of Electrical Engineering, Medi-Caps University, Indore, Madhya Pradesh, India 
5Department of Electrical and Electronics Engineering, Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering 

College, Chennai 62, India 
6Department of Electrical and Electronics Engineering, Viswam Engineering College, Madanapalle-517 325, Andhra 

Pradesh 

A R T I C L E   I N F O 
 

Article history: 
Received 10 February 2025  
Received in revised form 
14 March 2025 
Accepted 26 March 2025 
 
Keywords:  
PV system, Hybrid Boost-Cuk converter,  
Bat-Chicken swarm optimized PI controller,  
BESS, 3ϕ VSI  
 
*Corresponding author 
Email address: 
hemas04517@gmail.com 
 
DOI: 10.55670/fpll.futech.4.2.2 

 

A B S T R A C T 
 

Recently, the reduction of greenhouse gas emissions and fuel consumption has 
been attended to by adopting the Photovoltaic (PV) system. Due to their 
intermittent nature, energy generated by PV systems is unpredictable for 
microgrid operation. Therefore, in this research, a novel hybrid Boost-Cuk 
converter is developed to efficiently increase the low voltage received from the 
PV system. Subsequently, the Bat-Chicken swarm optimized Proportional 
Integral (PI) controller is exploited to adjust the PI controller's parameters. 
Furthermore, the intermittency and instability of PV systems are addressed by 
adding a Battery Energy Storage System (BESS) to the microgrid to provide a 
steady and continuous power supply. This output is delivered to the grid via a 
Three Phase Voltage Source Inverter (3ϕ VSI), and the grid synchronization is 
accomplished with the aid of a PI controller. In order to validate the efficacy of 
the developed work, it is executed using the MATLAB/Simulink tool and 
compared with traditional topologies. The outcomes reveal that the developed 
research attains an efficacy of 93%, ensuring effective grid synchronization. 

1. Introduction 

More fossil fuels are used to produce power, which 
increases environmental pollution. In addition to being the 
primary source of electrical production worldwide, fossil 
fuels are the main contributors to environmental degradation 
[1]. To reduce the negative effects of using fossil fuels, 
renewable energy systems (RES) like solar, wind, biomass, 
and hydraulic energies have received much attention [2]. 
Clean energy, such as PV, has drawn more and more attention 
as the environmental pollution issues brought on by 
conventional fossil fuels become more noticeable [3-5]. 
Effectively converting solar into affordable power without 
wasting energy is the main goal of all PV systems. Due to its 

plentiful resources and pollution-free benefits, grid-tied PV 
power generation technology has experienced rapid 
expansion [6-7]. Large-scale PV power-generation networks' 
ongoing grid integration results in a decline in the system's 
short-circuit capacity, which lowers the voltage support 
capacity [8]. However, Energy Storage Systems (ESSs) have 
been installed to guarantee a reliable power supply due to the 
variable nature of PV production systems during the day and 
their unavailability at night [9-10]. Numerous meteorological 
factors, including solar radiation, temperature, wind speed, 
precipitation, humidity, dust deposition, air pressure, and 
technical factors like inverter loss and PV array losses, affect 
the performance of solar PV power stations [11-12].   

 

 

Future Technology 

Open Access Journal 

https://doi.org/10.55670/fpll.futech.4.2.2 

 

 

 

 

 

 

May 2025| Volume 04 | Issue 02 | Pages 11-21 

Journal homepage: https://fupubco.com/futech 

 

ISSN 2832-0379 

mailto:hemas04517@gmail.com
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S. Hema et al. /Future Technology                                                                                                   May 2025| Volume 04 | Issue 02 | Pages 11-21 

12 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Since PV systems depend on ambient temperature and 

solar irradiance, their output power typically varies during 
the day [13, 14]. The Quadratic Boost Converter, which 
achieves high voltage gain with a single switch, is represented 
by S. Chitra Selvi et al. [15]. However, QBC's high-frequency 
switching results in better switching losses, which reduces 
the system's effectiveness. Ahmed et al. [16] presented an 
interleaved Boost Converter with high conversion efficiency 
and lower switching losses. However, this converter requires 
more components, enhancing the overall cost and complexity. 
A transformerless boost converter that achieves high voltage 
gain without requiring high-duty cycles is designed by Ahmed 
et al. [17]. However, its increased input current ripple impacts 
the associated load's performance. Haider et al. [18] 
presented the high-gain Cuk converter sustaining a smooth 
current waveform because of the capacitors and inductors at 
both input and output sides. However, the operation and 
implementation of this converter are complex, and dynamic 
operation leads to high current stress on switches.  

 
Figure 1. Block diagram of PV-based grid system 

A quadratic Cuk converter was developed by H. 
Gholizadeh et al. [19] that reduces electromagnetic 
interference by maintaining a stable input current with 
minimal ripple. Nevertheless, the converter is effective; there 
are some power losses because of the extra components and 
switching operations. Therefore, this paper uses a hybrid 
Boost-Cuk converter to enhance the low voltage of the PV 
system. The PI controller is exploited to manage the function 
of the hybrid Boost-Cuk converter, and its parameters are 
tuned by the optimization algorithm. In order to address 
nonlinear, non-differentiable, and multi-modal optimization 
issues, the particle swarm optimization approach was 
introduced by Demir et al. [20]. However, it cannot ensure 
that the best solution will be found, especially for extremely 
complicated or multi-modal issues. In Shamseldin et al. [21] 
research, a Harmony Search (HS) optimization algorithm is 
developed, which sustains a good balance between 
exploration and exploitation. Nevertheless, the performance 
of HS is significantly affected by the initial harmony memory, 
which leads to suboptimal solutions. The Cuckoo Search 
Optimization technique improves accuracy and efficiency in 
optimization tasks while exhibiting reasonable convergence 
rates. Nevertheless, the algorithm's effectiveness is reduced 
by the initial fixed parameters, necessitating improvements 
for improved performance [22]. In Amador-Angulo et al. [23], 
a Chicken search optimization algorithm is developed that has 
shown competitive performance on a wide range of 
benchmark problems. The computational cost is high for large 
and complex problems, limiting its practical applications. As a 
result, the Bat-Chicken swarm optimization algorithm is 
exploited to fine-tune the PI controller’s parameters. The 
main motivations of this research are: 
• Implementing the hybrid Boost-Cuk converter that 

effectively enhances the low output voltage of the PV 
system. 

• The parameters of the PI controller are fine-tuned with the 
aid of the Bat-Chicken swarm optimization algorithm. 

• The battery is exploited to store the surplus energy from 
the PV system, and a bidirectional DC-DC converter is 
implemented to perform the battery's charging and 
discharging operations.  

 

 

Abbreviations 

AC  Alternating Current 

BA  Bat Algorithm 

BESS  Battery Energy Storage System 

CN  Chick Group 

CSO  Chicken Swarm Optimization 

DC  Direct Current 

ESS  Energy Storage System 

G2V  Grid to Vehicle 

HN  Hen Group 

HS  Harmony Search 

LPF  Low Pass Filter 

PI  Proportional-Integral 

PV  Photovoltaic 

PWM  Pulse Width Modulation 

QBC  Quadratic Boost Converter 

RES  Renewable Energy System 

RN  Rooster Group 

SRF-PLL  Synchronous Reference Frame-Phase Locked Loop 

V2G  Vehicle to Grid 

VSI  Voltage Source Inverter 

 

 

 

 



S. Hema et al. /Future Technology                                                                                                   May 2025| Volume 04 | Issue 02 | Pages 11-21 

13 

 

2. Proposed methodology 

Figure 1 reveals the block diagram of the developed PV-
based grid system. The PV system generates low voltage 
because of varying environmental conditions, which is 
boosted with the aid of a hybrid boost-Cuk converter. 
Nevertheless, the voltage of the developed converter, which is 
regulated by a PI controller, is unstable, and its parameters 
are tuned by a Bat-Chicken swarm optimization algorithm. 
After that, the Pulse Width Modulation (PWM) generator 
produces PWM pulses to better operate the developed 
converter. A Bidirectional DC-DC Converter enables charging 
and discharging operations, and battery voltage is regulated 
by a PI Controller. Subsequently, the DC power from the 
converter is transformed into AC power with the aid of 3ϕ 
VSI. Then, the PI controller is employed to regulate the 
function of the inverter, and the PWM generator is exploited 
to improve the functioning of the inverter. Furthermore, the 
obtained AC power is delivered to the 3ϕ grid with the aid of 
an LC filter, which provides harmonic less power to the grid.     

2.1 PV system  
Solar cells are semiconductors that generate Direct 

Current (DC) over PV panels by absorbing solar energy on 
frontal surfaces. As seen in Figure 2, the PV panel circuit is 
built with a diode, series resistance(RS), a photocurrent(Iph), 
and resistance that are connected in parallel (Rp) to indicate a 
current leakage.  

 
Figure 2. Circuit of PV system 

By applying Kirchhoff’s law, the current equation becomes, 

 𝐼 = 𝐼𝑝ℎ − 𝐼𝐷 − 𝐼𝑝                             (1) 

𝐼𝑝 =
𝑉+𝑅𝑆𝐼

𝑅𝑝
                             (2) 

The current via the diode is denoted as 𝐼𝐷and the magnitude 
of the diode current is denoted as, 

𝐼𝐷 = 𝐼𝑠𝑑 (𝑒𝑥𝑝 (
𝑞.(𝑉+𝑅𝑆.𝐼)

𝑛.𝐾.𝑇
) − 1)                           (3) 

Where 𝐾 stands for the Boltzmann constant and 𝐼𝑠𝑑reverse 
saturation current. Climate circumstances cause the obtained 
PV voltage to decrease, so a converter is required to enhance 
the voltage to power the grid. The hybrid Boost-Cuk converter 
approach used in this work is explained in the following part.  

2.2 Hybrid boost-cuk converter 
The hybrid Boost-Cuk converter (Figure 3) integrates 

both Boost and Cuk converters to enhance the PV system's 
low voltage. The number of switches and diodes in a 
converter directly impacts its complex operation and control. 
Since each switch needs a gate drive signal to be controlled, 
this increase takes place. The developed converter has two 
stages of operation.  
Stage 1: 
When switch 𝑆 is active at 𝑡𝑜, this stage is initiated (Figure 4). 
Considering that twice the input voltage is the same as the 
voltage across 𝐶1and input voltage is similar to 𝑉𝐶2. Then, half 

of the output voltage is the same as the voltage across 𝐶3 and 
𝐶4. During this mode, the voltage across 𝐿1  is positive. 
Consequently, the current flowing via the inductor is linearly 
increased. 

 
Figure 3. Hybrid boost-cuk converter 

𝑉𝐿1 = 𝑉𝑃𝑉 + 𝑉𝐶1 + 𝑉𝐶2                            (4) 

𝑉𝐶2(𝑡𝑜) =
1

2
𝑉𝐶1(𝑡𝑜) = 𝑉𝑃𝑉                                              (5) 

𝑉𝐿1 = 4𝑉𝑃𝑉                                       (6) 

∆𝐼𝐿1 =
4𝑉𝑃𝑉

𝐿1
(𝑡1 − 𝑡𝑜) =

4𝐷𝑉𝑃𝑉

𝐿1𝑓𝑠
                                            (7) 

In this mode, the inductor 𝐿1 receives energy from the input 
source and  𝐶1 and𝐶2. The voltage across the inductor 𝐿2 is,  

𝑉𝐿2 = 𝑉𝑃𝑉 + 𝑉𝐶2 = 2𝑉𝑃𝑉                            (8) 

∆𝐼𝐿2 =
2𝑉𝑃𝑉

𝐿2
(𝑡1 − 𝑡0) =

2𝐷𝑉𝑃𝑉

𝐿2𝑓𝑠
                           (9) 

Inductor 𝐿2's current rises linearly as a result of the positive 
voltage across it. In this mode, 𝐿2 receives energy from the 
input source and capacitor 𝐶2.  

𝑉𝐿3 = 𝑉𝑃𝑉                           (10) 

∆𝐼𝐿3 =
𝑉𝑃𝑉

𝐿3
(𝑡1 − 𝑡0) =

𝑉𝑃𝑉𝐷

𝐿3𝑓𝑠
                         (11) 

∆𝐼𝐿1 = 2∆𝐼𝐿2                           (12) 

𝑡1 − 𝑡0 = 𝐷𝑇                           (13) 

Where 𝐷𝑇 is the amount of time it takes for the switch to turn 
on and 𝐷 is its duty cycle. A higher anode voltage activates a 
diode because diodes 𝐷1 and𝐷2share a cathode. Diode 𝐷1's 
anode voltage is equal to 𝑉𝑃𝑉 , while diode 𝐷2′s anode voltage 
is equal to−(𝑉𝐶1 + 𝑉𝐶2). As a result, 𝐷2is reverse-biased. The 
voltage across the diode 𝐷3is calculated as follows because 
the switch is on. 

𝑉𝐷3 = 𝑉𝑂 − 𝑉𝐶4 =
𝑉𝑂

2
                         (14) 

Furthermore, diode 𝐷5 is reverse-biased. In this mode, the 
output capacitor 𝐶𝑂 is charging capacitors 𝐶3 and 𝐶4 and diode 
𝐷4 is forward-biased. However, the load is also delivered by 
the output capacitor. The nominal power determines the 
maximum input current in the developed converter. For a 
100% efficiency assumption, the following expressions are 
obtained:  

𝑉𝑂(𝑚𝑎𝑥) × 𝐼𝑂 = 𝑉𝑖𝑛 × 𝐼𝑖𝑛(𝑚𝑎𝑥)                                                       (15) 

𝐼𝑖𝑛(𝑚𝑎𝑥) =
𝑉𝑂(𝑚𝑎𝑥)×𝐼𝑂

𝑉𝑖𝑛
                          (16) 

𝑉𝐶3 + 𝑉𝐶4 = 𝑉𝑂                           (17) 

As 𝐶3 = 𝐶4 and its voltage is half the output voltage.  



S. Hema et al. /Future Technology                                                                                                   May 2025| Volume 04 | Issue 02 | Pages 11-21 

14 

 

 
Figure 4. Stages of developed converter 

 

 
Figure 5. Switching the waveform of the converter 

Stage 2: 
When the switch is turned off at 𝑡1, this mode is started. As a 
result, diode 𝐷2 is forward-biased and diode 𝐷1 is reversed-
biased. Consequently, diodes 𝐷2, 𝐷3 and 𝐷5 provide the 
necessary path to move the energy stored in inductors 𝐿1 and 
𝐿2 to capacitors 𝐶1 and 𝐶2, and the output. The energy held in 
capacitors 𝐶3 and 𝐶4 is transferred to the load when diodes, 
𝐷3and 𝐷5 are turned on, while the diode 𝐷4is reverse-biased.       

𝑉𝐿1 = 𝑉𝑃𝑉 + 𝑉𝐶1 + 𝑉𝐶2 + 𝑉𝐶4 − 𝑉𝑂 = 4𝑉𝑃𝑉 −
𝑉𝑂

2
                       (18) 

Owing to the negative voltage through𝐿1, it's current reduces 
linearly 

∆𝐼𝐿1 = (4𝑉𝑃𝑉 −
𝑉𝑂

2
) ×

(𝑡2−𝑡1)

𝐿1
= (4𝑉𝑆 −

𝑉𝑂

2
)

(1−𝐷)

𝐿1𝑓𝑠
                    (19) 

Based on the volt-second balance for the inductor 𝐿1, the 
following expression is obtained: 

4𝑉𝑃𝑉𝐷𝑇 = (
𝑉𝑂

2
− 4𝑉𝑃𝑉) (1 − 𝐷)𝑇                         (20) 

When diode  𝐷2 is active, the subsequent expressions are 
calculated, 

𝑉𝐿2 = −𝑉𝐶1 = −2𝑉𝑆                          (21) 

∆𝐼𝐿2 =
−2𝑉𝑃𝑉(1−𝐷)

𝐿2𝑓
                          (22) 

In mode 2, capacitors 𝐶3 and 𝐶4 are connected in parallel, 

𝑉𝐶3 = 𝑉𝐶4                                            (23) 

Figure 5 displays the switching waveform of the developed 
converter. After that, the PI controller is exploited to stabilize 
the voltage of the developed converter, and its parameters are 
tuned by the Bat-Chicken swarm optimization algorithm. 

 

2.3 Bat-chicken swarm optimized PI controller 
 A Bat-Chicken swarm-optimized PI controller integrates 

the BA and CSO to tune the PI controller’s parameters. This 
hybrid approach combines the exploration efficacy of BA and 
adaptive hierarchy-based dynamics of CSO to optimize the PI 
controller’s performance. Figure 6 reveals the flowchart of 
the Bat-Chicken swarm-optimized PI controller. It initializes 
a population of potential solutions that represent distinct 𝐾𝑃  
and 𝐾𝐼 pairs. BA highlights the phenomenon of echolocation 
by approaching the prey that has been identified, as bats 
search for it separately. This implies that a single random 
person is persuading the entire swarm to deviate in search of 
food. 

 
Figure 6. Flowchart of Bat-Chicken swarm optimized PI controller 

By shifting their current position, the entire swarm converges 
to the optimal solution across generations. The flight of a bat 
is:  

𝑄𝑖
(𝑡)

= 𝑄𝑚𝑖𝑛
(𝑡)

+ (𝑄𝑚𝑎𝑥
(𝑡)

− 𝑄𝑚𝑖𝑛
(𝑡)

) . 𝛽                                          (24) 

𝑉𝑖
(𝑡+1)

= 𝑉𝑖
(𝑡)

+ [𝑋𝑖
(𝑡)

− 𝑋𝑏𝑒𝑠𝑡
(𝑡)

] . 𝑄𝑖                                               (25) 



S. Hema et al. /Future Technology                                                                                                   May 2025| Volume 04 | Issue 02 | Pages 11-21 

15 

 

𝑋𝑖
(𝑡+1)

= 𝑋𝑖
(𝑡)

+ 𝑉𝑖
(𝑡)

                                           (26) 

Where 𝑋𝑖
(𝑡+1)

is the position of𝑖𝑡ℎbat at generation,𝑡, 𝑉𝑖
(𝑡)

 is the 

velocity of a single bat and𝑄𝑖
(𝑡)

 is the actual pulse frequency. 

Within the interval𝑄𝑖
(𝑡)

𝜖[𝑄𝑚𝑖𝑛, 𝑄𝑚𝑎𝑥], the output pulse 

frequency is fluctuating. The output pulse is specified by the 
random number 𝛽 ∈  [0, 1], and the current best solution at 

the moment is shown by 𝑋𝑏𝑒𝑠𝑡
(𝑡)

. The two halves of the BA 

search process are exploitation and exploration. While 
exploitation guides the search in the vicinity of the current 
solutions, exploration refers to the discovery of new 
solutions. Since both processes usually rely on the variation 
operators, they can’t be carried out concurrently. However, 
striking a balance between exploration and exploitation sets 
the control parameters. More ideal parameter configurations 

exist. Two exploration strategies and the parameter 𝑟𝑖
(𝑡)

 are 

used in the BA to balance the exploration and exploitation 
parts of the search process. The first exploration strategy is 
more exploratory in character, whereas the second method, 
which is given as: 

𝑋𝑛𝑒𝑤 = 𝑋𝑜𝑙𝑑 + 𝜖. 𝐴
(𝑡)

                                                            (27) 

It employs the random walk, which is a type of local search 
that is more concerned with taking advantage of the best 
solution available at the moment. Let's observe that 𝑋𝑜𝑙𝑑  in 
the equation displays the current best solution, whereas 𝑋𝑛𝑒𝑤 

presents the new best solution. 𝐴
(𝑡)

is the average loudness, 
while 𝜖 is the random number in the range (−1,1). Chickens 
are a unique species of poultry animal due to their sociable 
character, and they usually work together to obtain food. 
Hens, chicks, and roosters are the three distinct groups of 
individuals that make up chicken flocks. Based on varying 
foraging hierarchies, the group exhibits a distinct foraging 
capacity. In this hierarchy, hens chase after roosters because 
they are better at foraging than they are, and chicks follow 
suit since they are less skilled at foraging.  

The intelligent optimization algorithm's optimization 
object is the objective function that requires an optimal 
solution. Its independent variable parameters are composed 
of 𝑛 𝑗 −dimensional space vectors 𝑋, where 𝑛 is any positive 
integer, and 𝑗 is the dimensionality. The Chicken Optimization 
Algorithm is divided into 3groups based on the number of 
vectors 𝑋. The first RN individuals with the lowest fitness 
value are assigned to the rooster group 𝑅𝑖; the  Chick Group 
(CN) individuals with the highest fitness value are assigned to 
the chick group 𝐶𝑖; and the remaining Hen Group(HN) 
individuals are allocated to the hen group 𝐻𝑖. The 
corresponding numbers of individuals in each group within 
the colony are thus denoted by the letters Rooster Group 
(RN), HN, and CN. 

𝑅𝑖 = {𝑅1, 𝑅2, ⋯ , 𝑅𝑅𝑁}                          (28) 

𝐶𝑖 = {𝐶1, 𝐶2, ⋯ , 𝐶𝐶𝑁}                          (29) 

𝐻𝑖 = {𝐻1, 𝐻2, ⋯ , 𝐻𝐻𝑁}                          (30) 

The rooster group’s location succession is: 

𝑅𝑖,𝑗
𝑡+1 = 𝑅𝑖,𝑗

𝑡 [1 + 𝑟𝑎𝑛𝑑𝑛(0, 𝛿2)]                         (31) 

𝛿2 = {

1,   𝑓𝑖 ≤ 𝑓𝑠

𝑒
𝑓𝑠−𝑓𝑖
|𝑓𝑖|+𝜖

,     𝑓𝑖>𝑓𝑠

𝑆𝜖[1, 𝑛],     𝑠 ≠ 𝑖

                          (32) 

Where 0, 𝛿2 is a Gaussian-distributed random number that 
obeys a 0 mean and variance of 𝛿2 and 𝑅𝑖,𝑗

𝑡 is the position of 

the 𝑖𝑡ℎ rooster in the 𝑗𝑡ℎ  dimension following 𝑡 iterations, the 
random rooster index, or 𝑆, is a small but significant integer 
that prevents the denominator from 0, while the individual's 
fitness value is denoted by 𝑓. The hen group’s location 
succession is: 

𝐻𝑖,𝑗
𝑡+1 = 𝐻𝑖,𝑗

𝑡 + 𝑘1 ∗ 𝑟𝑎𝑛𝑑 ∗ (𝑅𝐻𝑖
𝑡 − 𝑀𝑖,𝑗

𝑡 ) + 𝑘2 ∗ 𝑟𝑎𝑛𝑑 ∗ (𝑅𝐻𝑡 −

𝐻𝑖,𝑗
𝑡 )                                                                               (33) 

𝑘1 = 𝑒
𝑓𝐻𝑖−𝑓𝑟𝐻𝑖

|𝑓𝐻𝑖|+𝜖                            (34) 

𝑘2 = 𝑒𝑓𝑅𝐻−𝑓𝐻𝑖                                             (35) 

The position of the 𝑖𝑡ℎ hen in the 𝑗𝑡ℎ  dimension following 
t iterations is denoted by 𝐻𝑖,𝑗

𝑡 . A random number among 

0 𝑎𝑛𝑑 1 is called a rand. 𝑅𝐻𝑖
𝑡  is the position of the 𝑖𝑡ℎ hen's 

leader rooster after 𝑡 iterations;𝑅𝐻𝑡 is the position of the 
randomly chosen individuals between the other roosters and 
hens, excluding the hen and leader cock, after 𝑡 iterations; 
𝑘1denotes the rooster's influence factor and 𝑘2 represents the 
random individual effect factor. Where 𝑓𝐻𝑖  represents the 𝑖𝑡ℎ 
hen's fitness value. The rooster leading the hen has a fitness 
value of 𝑓𝑟𝐻𝑖 . Where Eq. contains 𝑓𝑅𝐻 , the random person's 
fitness value. Location succession of the hen groups is: 

𝐶𝑖,𝑗
𝑡+1 = 𝐶𝑖,𝑗

𝑡 + 𝐹 ∗ (𝐻𝑖𝑗
𝑡 − 𝐶𝑖,𝑗

𝑡 )                         (36) 

The 𝑖𝑡ℎ chick's position in the 𝑗𝑡ℎdimension after t iterations 
is denoted by 𝐶𝑖,𝑗

𝑡 ; the matching hen's position after 

𝑡 iterations is denoted by 𝐻𝑖𝑗
𝑡; and 𝐹 is a random number 

between 0 𝑎𝑛𝑑 2.The hybrid algorithm iteratively refines 𝐾𝑝 

and 𝐾𝑖  to minimize a fitness function defined by the control 
system's performance metrics. After reaching convergence, 
the best solution is selected as the optimized 𝐾𝑃and 𝐾𝐼values 
for the PI controller. This hybrid optimization approach is 
appropriate for complex and nonlinear systems, where 
traditional tuning methods are become infeasible because of 
dynamic variability or high dimensionality.  

2.4 Battery 
The battery is represented by the electrical circuit, 

shown in Figure 7. The electrolyte, plate grids, separator 
porosity, and connecting conductors develop the equivalent 
series resistance (𝑅𝐵). The battery capacitance is represented 
by𝐶𝐵, whereas the equivalent parallel resistance (𝑅𝑝) is a 

representation of the impurities in the electrolyte and plates 
that cause the battery to gradually discharge when it is left 
disconnected (self- discharge resistance).  

 

Figure 7. Circuit diagram of battery 

 

 



S. Hema et al. /Future Technology                                                                                                   May 2025| Volume 04 | Issue 02 | Pages 11-21 

16 

 

Buck mode:  
While the switch 𝐾2 remains open(𝑢2 = 0), the switch 𝐾1 is 

controlled by a PWM signal {𝑢1𝜖{0,1}}in this mode. After that, 

the DC bus transfers the electrical energy to the battery. The 
entire system (charger-battery) functions in G2V mode. 
However, the dc-dc converter functions in buck mode. 
Considering that 𝑢1is accept either1 𝑜𝑟 0, the subsequent 
switching model is derived:  

𝐿
𝑑𝑖𝐿

𝑑𝑡
= −𝑟𝑖𝐿 − 𝑣𝐵 + 𝑢1𝑉𝐷𝐶                          (37) 

𝐶
𝑑𝑣𝐵

𝑑𝑡
= 𝑖𝐿 −

1

𝑅𝐵
𝑣𝐵 +

1

𝑅𝐵
𝑣𝐶                                            (38) 

𝐶𝐵
𝑑𝑣𝐶

𝑑𝑡
=

1

𝑅𝐵
𝑣𝐵 − (

1

𝑅𝐵
+

1

𝑅𝑝
) 𝑣𝐶                          (39) 

Boost mode:  
In this mode, the switch 𝐾1 remains open(𝑢1 = 0), but only 

switch 𝐾2 is controlled by a PWM signal{𝑢2𝜖{0,1}}. After that, 

the battery transfers its electrical energy to the DC bus. While 
the entire system (charger-battery) functions in V2G mode, 
the DC-DC power converter functions in boost mode. 
Considering that 𝑢2accept either 1 𝑜𝑟 0, the following 
switching model is derived.  

𝐿
𝑑𝑖𝐿

𝑑𝑡
== −𝑟𝑖𝐿 − 𝑣𝐵 + (1 − 𝜇2)𝑉𝐷𝐶                          (40) 

𝐶
𝑑𝑣𝐵

𝑑𝑡
= 𝑖𝐿 −

1

𝑅𝐵
𝑣𝐵 +

1

𝑅𝐵
𝑣𝑐                          (41) 

𝐶𝐵
𝑑𝑣𝐶

𝑑𝑡
=

1

𝑅𝐵
𝑣𝐵 − (

1

𝑅𝐵
+

1

𝑅𝑝
) 𝑣𝐶                         (42) 

Then, the output of the converter is fed into the VSI that 
transforms the DC to AC voltage, and grid synchronization is 
discussed below. 

2.5 𝟑𝛟 Grid Synchronization 
A passive Low-pass filter (LPF) filters the output voltage 

of a controlled VSI, as shown in Figure 8. At the point of 
common coupling, the filtered voltage that is almost 
harmonic-free is synchronized with the grid voltage. The 
connection is guaranteed by the coupling breaker. The 
filtered VSI and grid voltage are converted into the inverter's 
rotating orthogonal frame. It is presumed that the inverter's 
frame and the reference signal frame are arranged so that the 
inverter's quadrature component,𝑈𝑞𝑖𝑛𝑣denotes its magnitude 

and its direct component, 𝑈𝑑𝑖𝑛𝑣, equals zero. Since 𝑈𝑞𝑓  and 

𝑈𝑞𝑔 stand for the quadrature components, 𝑈𝑑𝑓 and 𝑈𝑑𝑔 are 

the filtered inverter voltage and the grid voltage’s direct 
components. Because of this arrangement, the direct 
components are ideal indicators of the phase shift among the 
inverter reference signal and the filtered and grid voltages. 
The initial and preliminary stage of synchronization is 
accomplished by regulating the inverter voltage to match the 
grid's magnitude. The phase-angle matching procedure is the 
second and most important stage. Where 𝑈𝑓  and 𝑈𝑔 are the 

inverter-filtered and grid voltage magnitudes, respectively, 
The inverter reference signal's phase angle is represented 
by𝜃𝑖𝑛𝑣 , the filtered VSI voltage by 𝜃𝑓  and the grid voltage by 

𝜃𝑔. 

𝑈𝑑𝑓 = −𝑈�̂�𝑠𝑖𝑛(𝜃𝑖𝑛𝑣 − 𝜃𝑓)                           (43) 

𝑈𝑑𝑔 = −𝑈�̂�𝑠𝑖𝑛(𝜃𝑖𝑛𝑣 − 𝜃𝑔)                          (44) 

𝑈𝑞𝑓 = −𝑈�̂�𝑐𝑜𝑠(𝜃𝑖𝑛𝑣 − 𝜃𝑓)                          (45) 

𝑈𝑞𝑔 = −𝑈�̂�𝑐𝑜𝑠(𝜃𝑖𝑛𝑣 − 𝜃𝑔)                          (46) 

 
Figure 8. Grid synchronization 

Utilizing the phase-shift representative value, the inverter 
frequency is adjusted to ensure that the grid and the inverter 
direct components are identical to achieve a zero phase-shift 
among the voltages.  

𝑒𝜃 = (𝑈𝑑𝑓 × 𝑈𝑞𝑔 − 𝑈𝑞𝑓 × 𝑈𝑑𝑔)                         (47) 

𝑒𝜃 = 𝑈�̂�. 𝑈�̂�𝑠𝑖𝑛(𝜃𝑓 − 𝜃𝑔)                          (48) 

When the voltage of the grid 𝜃𝑔 and the VSI voltage phase-

angle 𝜃𝑓  are equal, leading the equation (48) to be zero. While 

both voltage magnitudes are identical, this results in 𝑈𝑑𝑓 =

𝑈𝑑𝑔.  

𝑒𝜃 = 𝑈�̂�. 𝑈�̂�(𝜃𝑓 − 𝜃𝑔)                                                            (49) 

This is the same as the SRF-PLL's controlled voltage value. 
The distinction is that, in this case, the phase shift is calculated 
between two measured voltages that need to be synchronized 
rather than between a measured signal and the internal PLL 
frame. To guarantee a zero phase-shift among the voltages, 
the value is regulated to zero is denoted by 𝑒𝜃 . Since the phase 
control is solely reliant on the constancy of the voltage 
magnitudes, it is crucial to begin controlling the voltage 
magnitude before controlling the phase. Since the phase 
control is based on actual voltage levels, any disruption 
brought on by the magnitude control has a significant impact 
on it.  

3. Results and discussion 

This part analyzes the outcomes of a developed PV-based 
grid system using MATLAB/Simulink software. It also 
includes a comparison of conventional approaches with 
developed work. Table 1 displays the parameters of the 
developed research. 
Case 1: Constant temperature and intensity 
Figure 9 represents the characteristics of solar panels in 
constant temperature and intensity conditions. The 
temperature is sustained at a stable value of 35 ℃ without 
distortions. Also, the intensity value of solar panels is 
sustained to a value of 1000(W⁄(Sq.m)) without any 
fluctuations. Subsequently, the voltage of the solar panel is 
stabilized at a stable value of 310 V throughout the system. 
Likewise, the current of the solar panel gradually decreased 



S. Hema et al. /Future Technology                                                                                                   May 2025| Volume 04 | Issue 02 | Pages 11-21 

17 

 

in the starting stage, and it maintained a value of 50 A in the 
entire system. 

Table 1. Parameters of developed work 

Parameter Specification 

PV System 

Rated Power 10kW 
No. of Panels in Parallel 3 
Open Circuit Voltage 37.25V 

Cell linked in Series 36 

No. of Panels in series 12 
Short Circuit Current 8.95A 

Hybrid Boost-Cuk Converter 
C1, C2, C3and C4 22 μF 
Switching frequency 10KHz 
L1, L2 4.7mH 
CO 2200μF 

 

 
Figure 9. Characteristics of solar panel 

Figure 10 displays the developed converter’s waveform. 
The output voltage of the developed converter is linearly 
changed in the initial period, and it stabilizes at 600 V with the 
aid of the BCSO-PI controller. In the initial period, the output 
current slowly varied, and then it was sustained at a value of 
24 A with little distortions. Figure 11 reveals the battery's 
waveform. The battery's State of Charge (SOC)value is 
maintained at a stable 80 % throughout the system. The 
battery voltage is sustained at 50V without any oscillations. 
Consequently, the battery current is maintained at a constant 
2A with few fluctuations. Figure 12 illustrates the grid 
waveform. The grid voltage is stabilized at a constant value of 
420 V without any fluctuations. Likewise, the grid current is 
maintained at a stable value of 12 A throughout the system. 
The Real power waveform remains stable at approximately 
8000 W, indicating steady energy consumption or generation. 
Meanwhile, the reactive power waveform is constant at 
around 600 VAR, reflecting steady reactive power demand, as 
seen in Figure 13. 
Case 2: Varying temperature and intensity 
Figure 14 represents the characteristics of solar panels in 
varying temperatures and irradiation conditions. Initially, the 
solar panel's temperature is varied, and it is stabilized at a 
value of 35 ℃without any fluctuations. Similarly, the intensity 
of the solar panel is changed, and it maintains a constant value 
of 1000(W⁄(Sq.m))in the entire system. Likewise, the solar 
panel voltage is changed and sustained at a stable value of 

310V without any oscillations. Initially, the input current is 
randomly varied and gets sustained at a stable value of 50 A. 

 
Figure 10. Waveform of the developed converter with BCSO-PI 
controller 

 
Figure 11. Waveform of battery 

 
Figure 12. Waveform of grid 

 
Figure 13. The waveform of real and reactive power 

The waveform of the developed converter with the 
BCSO-PI controller is revealed in Figure 15. At the starting 
stage, the output voltage is linearly changed, and it is 
increased to a stable value of 600 V. Consequently, the output 
current is gradually raised and settled to a value of 24A 
without distortions. 

The R phase's THD value of 0.58% is within acceptable 
limits, representing a high-quality power signal with 
negligible harmonic interference. Also, the Y phase (0.68%) 
has slightly higher harmonic distortion than the R phase. 
Subsequently, the B phase has the lowest THD of 0.51% 



S. Hema et al. /Future Technology                                                                                                   May 2025| Volume 04 | Issue 02 | Pages 11-21 

18 

 

among the three phases, indicating a smoother power signal, 
as seen in Figure 16. 

 
Figure 14. Characteristics of solar panel 

 
Figure 15. Waveform of the developed converter with BCSO-PI 
controller 

 
Figure 16. Waveform of THD 

Figure 17 illustrates an analysis of efficiency for four 
different converters: Buck-Boost [24], High Gain Cuk [25], Z 
Source Boost [26], and the developed converter. The 
proposed converter attains the highest efficiency at 93%, 
highlighting its superior performance compared to the other 
converters. This makes it a promising choice for applications 
requiring high efficiency in power conversion. A comparative 
analysis of converter performance in terms of switching loss, 
inductor loss, capacitor loss, and diode loss for interleaved 
step-down converter [27] and Hybrid Boost-Cuk converter is 
displayed in Figure18. The Interleaved Step-Down Converter 
suffers more from inductor losses, making it less efficient in 
handling energy conversion. The Hybrid Boost-Cuk Converter 
demonstrates improvements in reducing inductor losses but 
experiences higher diode losses. Figure 19 shows the voltage 
gain for three types of converters: Transformerless [28], 
Interleaved Bi-directional [29], and the developed converter. 
The transformerless converter attains the highest voltage 
gain at all duty ratios, demonstrating superior performance in 
boosting voltage. The Interleaved Bi-directional Converter 
offers a balanced performance, providing moderate voltage 
gain. The Proposed Converter prioritizes other design 
objectives, such as reduced complexity, cost, or improved 
efficiency in specific operational conditions, over-achieving 
maximum voltage gain. Figure 20 depicts a comparative 
analysis of control approaches based on settling time and rise 
time for GWO-PI, Modified LOA-PI, and proposed PI 
controller. The BAT-CSO PI approach is the most efficient 
control method, achieving both the shortest settling time of 
0.023 s and a rise time of 0.021 s. The BAT-CSO PI approach 
offers a balanced performance with results that are not as fast 
as GWO-PI [30] but considerably better than Modified LOA-PI 
[31]. 

 
 



S. Hema et al. /Future Technology                                                                                                   May 2025| Volume 04 | Issue 02 | Pages 11-21 

19 

 

 
Figure 17. Analysis of efficiency 

 

 
Figure18. Analysis of converter performance 

Figure 19. Analysis of voltage gain 

 

 
Figure 20. Analysis of the control approach 

4. Conclusion  

This research presents the importance of a PV-based 
hybrid Boost-Cuk converter for an efficient energy generation 
process. The hybrid Boost-Cuk converter linked to the PV 
system’s output side increases output voltage while lowering 
switching loss. With less iteration before convergence, the 
applied Bat-Chicken swarm-optimized PI controller yields a 
higher gain, providing better control performance. 
Additionally, a steady power supply is guaranteed by the 
BESS, which is connected to the microgrid via a battery 
converter that ensures grid stability by supplying extra 
energy to the grid during periods of peak demand. Finally, the 
obtained DC supply harnessing 3ϕ VSI transforms the DC 
supply to AC, resulting in effective grid synchronization. The 
system's dependability and effectiveness are confirmed by 
the MATLAB/Simulink tool, which shows an efficiency of 93 
% with maximum voltage gain.   

Ethical issue 
The authors are aware of and comply with best practices in 
publication ethics, specifically with regard to authorship 
(avoidance of guest authorship), dual submission, 
manipulation of figures, competing interests, and compliance 
with policies on research ethics. The authors adhere to 
publication requirements that the submitted work is original 
and has not been published elsewhere. 

Data availability statement 
The manuscript contains all the data. However, more data will 

be available upon request from the authors. 

Conflict of interest 

The authors declare no potential conflict of interest. 

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