Power Quality Acquire of Intelligent Controller based Superior Gain

Re-Lift Luo Converter Intended for PV Linked Microgrid Integration

E. RAJENDRAN1, V. RAJI2, V. K. DINESH PRABU3

1Department of Electrical and Electronics Engineering & HOD/ECE,

S. K .P. Engineering College, Tiruvannamalai, Tamil Nadu,

INDIA

2Department of Computer Science and Engineering,

S. K .P. Engineering College, Tiruvannamalai, Tamil Nadu,

INDIA

3Electrical and Electronics Engineering,

S. K .P. Engineering College, Tiruvannamalai, Tamil Nadu,

INDIA

Abstract: - Power converters-based renewable energy sources such as photovoltaic (PV) and wind energy are

more popular for residential and commercial applications. Because, of their eco friendlessness and cost

effective operation. A Re-Lift Luo Converter integrated with renewable sources to the utility microgrid along

with Intelligent Controller strategies is proposed. The solar photovoltaic system provides voltage to the

inverter through a Re-lift Luo converter. The Bidirectional Battery converter along with battery system is used

to achieve energy control management for the proposed system. In this paper the grid synchronization with

DSTATCOM devices controlled by PI controller with D-Q theory transformation is achieved. Under this work,

DSTATCOM has been used to improve the power quality under different loading conditions. The LC filter is

employed to develop the output of the inverter. The input of the PV and battery systems are DC bus power

source, as well as AC power injected into the grid network. The obtained results indicate that proposed

approach delivers better performance with superior efficiency and nominal harmonics. The entire proposed

system is validated through a MATLAB simulation and Hardware experimental prototype.

Key-Words: - Photovoltaic (PV), Energy Storage System (ESS), Adaptive Neuro-Fuzzy Inference System

(ANFIS), Maximum Power Point Tracking (MPPT), Voltage Source Inverter (VSI), Pulse

Width Modulation (PWM).

Received: February 3, 2023. Revised: November 26, 2023. Accepted: December 7, 2023. Published: January 16, 2024.

1 Introduction

The microgrids are playing major role and drawing

awareness from engineers and scientists for the

period of the last few decades. There could be DC

bus as well as AC bus bars running around where

the sources and loads with suitable voltage ratings

connected. microgrids are generally including

renewable energy sources. The renewable energy

sources distribute power into the microgrid using

power electronic converters. Consequently, that

the energy is properly transformed into the bus bars

with changed voltage ratings. The stand alone

storage system is required in the microgrid. In

addition to that, the renewable energy harvested

from the solar photovoltaic system can be stored

the energy during the periods, at the same time as

the solar irradiances are available. The stored

energy can be used during the periods whereas the

solar energy is not presented, particularly for the

period of the night time. While the microgrid

include voltage bus bars of DC and AC voltages by

way of high and low voltage paths, it is necessary

with the intention of multiple output power

electronic converters can be employed. As a result,

a lot of topological variants for multiple output

power conversion systems in addition to control

schemes for a variety of applications have been

description in the novel, and a few of the milestone

contributions are reviewed herein as a result that

the research gaps could be identified.

A new DC to DC converter topology by way of

a high power conversion efficiency moreover wide

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E. Rajendran, V. Raji, V. K. Dinesh Prabu

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range of operation with zero voltage switching as

well as lower output inductance has been proposed

and validated, [1]. The developed a three port DC

to DC converter through high voltage gain. The

authors have demonstrated how it could be used for

battery charging powered from a solar photovoltaic

resource, [2]. The design of a solar photovoltaic

simulator as a result that the research activities

correlated to solar photovoltaic systems could be

carried out effortlessly in a laboratory for the

period of day or night. The multiport DC to DC

converters have been generally suggested for utilize

in microgrids as fine, [3].

A choice of configurations of multiple output

DC to DC converters has been discussed in article,

[4]. A quadratic boost converter through lofty

voltage gain has been presented, [5]. In the research

article, [6], the developed a harmonic reduction

scheme is a cascaded cell-based islanded

microgrid. The developed a high step up DC to DC

converter with a Ćuk-derived quadratic boost

converter, [7]. A dual-output DC to DC converter

among the relift Luo converter as the interior

converter has been presented in this article. The

proposed system is proved to be more beneficial by

way of increased voltage gain, which enables the

system to be operational even through low solar

irradiance otherwise when the battery state of

charge becomes especially low, [8].

An artificial neural network controlled based

battery charging scheme has been proposed and

validated, [9]. A hybrid energy storage system

powered from the solar photovoltaic system has

been developed, [10]. Correspondingly, in solar

powered battery based energy storage system has

been designed for applications in AC low voltage

systems and for catering power used for nonlinear

load applications, [11]. The detailed study of power

electronic conversion systems are powered by a

solar photovoltaic source. The author of for this

work made the study in the viewpoint of reliability

study, [12]. A multifunction converter powered

from a solar photovoltaic source primarily for

water pumping applications has been developed,

[13].

The developed a DC to DC converter through a

three winding coupled inductor to facilitate

provides non isolation, reduced voltage stress in

addition to high voltage gain features. The

increased voltage gain and reduced switching

losses, least ripple on the output DC voltage and

linearity in control for maximum possible range of

output voltage as well as loading conditions are

several of the basic requirements of a power

electronic converter, [14]. In this kindness, several

authors have derived new conversion schemes

using the traditional converters like the SEPIC

converter, Cuk converter and Luo converter. For

example in reference, [15], the modified crucial

SEPIC topology for getting high voltage gain.

Additional, the authors have developed high

voltage gain quasi-SEPIC converter.

This paper identified the frequency scope of

interactions in a viewpoint of d-q frame

impedances in addition to pinpoint that the ac

voltage regulation was the major reason of

instability, masking the special effects of phase-

locked loop on power transmission systems, [16].

The existing a normalized gradient adaptive

regularization factor neural filter supported control

is presented for a three phase grid connected solar

PV battery energy storage microgrid arrangement.

Here, a used incremental conductance technique is

utilized for the peak power taking out of a PV

array, [17].

A matchless control is developed for

resynchronization of the grid throughout

reconnection of the grid after the mitigation of a

failure. The overall system control system is

flexible under various practically happening

situations such as disconnection of the PV array,

battery and the grid from the arrangement, [18].

Based on the above mention survey, the proposed

Re-lift Luo converter through Adaptive Neuro-

Fuzzy Inference System (ANFIS) algorithm used

PV system, the voltage and supplying the reactive

power, power quality issues are overcome for

microgrid integration. The role of the document is

mentioned below,

 To extract the maximum power from PV

system using Re-lift Luo converter through

Neuro Fuzzy Logic algorithm.

 To achieve the high gain output DC voltage

with Proposed MPPT and Re-Lift Luo

converter.

 To achieve the power management system for

the proposed Bidirectional Battery converter

along with battery system.

 To achieve the grid synchronization using D-Q

theory and PI controller.

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2 Materials and Method

Fig. 1: Proposed Simulation Block Diagram

 To demonstrate the characteristics of the

PV and the battery systems are analysed

using MATLAB Simulink and hardware

model environment.

In this proposed system implementing an

innovative DC-DC multi-source converter

configuration based grid interactive microgrid

consists of Photovoltaic (PV) and Energy Storage

System (ESS) is proposed as shown in Figure 1.

The planned system design makes use of solar as

well as batteries for an efficient storage system.

The battery is used to achieve the energy

management of the proposed method. The optimal

DC voltage is extracted from the PV panel using

ANFIS based MPPT is injected into a proposed

converter, which helps to improvise the DC voltage.

A power output obtained from a PV panel or array

is fed into the Re-lift Luo converter and the

enhanced output from the converter is converted to

AC through a 3 phase Voltage Source Inverter

(VSI), which is injected to the grid after suitable

synchronization. A PI controller is implemented

to maintain the constant voltage of the DC link

and enhance the grid’s performance. The PWM

generators are employed in this method, based on

the error signal can able to generate the proper

pulses and supplied to the Inverter as well as Re-lift

Luo converter. The harmonic present in VSI is

rectified using LC filter; thereby the quality power

has been safely injected into the microgrid. Under

this work, DSTATCOM has been used to improve

the quality of power under different loading

conditions and also reduces the Total Harmonics

Distortion (THD) and satisfies the IEEE harmonics

standard level.

2.1 Re-Lift Luo Converter

The Re-Lift Luo converter comprises of three

diodes D1, D2, D3; three capacitors C1, C2, C3; three

inductors L1, L2, L3; two power switches S1, S2 as

well as an output capacitor C0 as shown in Figure

2. The Capacitors C2 and C3 acquire a voltage

boosting characteristic which makes the capacitor

voltage VC two times upper than the source voltage

VPV. The inductor L3 serves as a ladder joint for

connecting the capacitors C2 and C3 in order to raise

the capacitor voltage VC1.The source instantaneous

current IPV= iL1 + iL2 + iL3 +iC2 +iC3 flows when the

power switches S1 and S2 are turned ON as

illustrated in Figure 3. Meanwhile, the inductors L1

and L3 store the energy from the source. The

inductor L2 gets charged with the energy received

from both the source and capacitor C1. The current

flowing during the inductors L1, L2 and L3 get to

increased.

The source current IPV becomes zero when the

power switches S1 and S2 are in OFF condition as

illustrated in Figure 4. The discharging of inductor

L1 takes place and the inductor current iL1 flows via

path C2 − L3 − C3 − D3 − C1 and results in charging

of capacitor C1. For the moment the inductor L2

discharges energy and the current iL2 flows to the

load R and output capacitor C0.The current iL1 and

iL2 reject at this stage. By means of considering

capacitors C2 and C3 value as very large, during

steady state condition VPV= VC2=VC3. At the switch

ON condition, VL3 = VPV. The peak-to-peak current

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ripple of inductor L3 is expressed by the equation

as follows:

𝛥𝑖𝐿3 = 𝑉𝑃𝑉𝐾

𝐿3 (1)

At the switch OFF condition,

𝛥𝑖𝐿3 = 𝑉𝐿3(1 − 𝐾)𝑇

𝐿3 (2)

The voltage across the inductor L3 is given as,

𝑉𝐿3 = 𝑘

1 − 𝑘 𝑉𝑃𝑉 (3)

During the period kT, the switch is in ON

condition as well as the current iL1 increases

whereas during period (1-K) T, the switch is in

OFF condition with the current iL1 decreases. VPV

and – (VC1- 2VPV - VL3) are the related voltages

supplied to the inductor L1. Thus,

𝐾𝑇𝑉𝑃𝑉 = (1 − 𝐾)𝑇 (𝑉𝐶1 − 2𝑉𝑃𝑉

−𝑉𝐿3) (4)

Therefore,

𝑉𝐶1 = 2

1 − 𝐾 𝑉𝑃𝑉 (5)

Similarly, during the period KT, the switch is

in ON condition in addition to the current iL2

increases whereas during the period (1-K) T, the

switch is in OFF condition and the current iL2

decreases. (𝑉𝑃𝑉 − 𝑉𝐶1 − 𝑉0) and − (𝑉0 −

2𝑉𝑃𝑉 − 𝑉𝐿3) are the related voltages supplied to

the inductor L2.

Thus,

𝐾𝑇 (𝑉𝐶1 + 𝑉𝑃𝑉 − 𝑉0)

=(1 − 𝐾)𝑇 (𝑉𝐶1 − 2𝑉𝑃𝑉

−𝑉𝐿3) (6)

Therefore,

𝑉𝑜 = 2

1 − 𝐾 𝑉𝑃𝑉 (7)

By taking into account P0 = PIN i.e., V0I0 = VPVIPV,

the output current is:

𝐼𝑜 = 1 − 𝐾

2𝐼𝑃𝑉 (8)

The value of the inductors L1, L2, C1, C2, C3 and

C0 are obtained from the following equations,

𝐿1 = 1 − 𝐾𝑇𝑉𝑃𝑉

𝛥𝑖𝐿1 (9)

𝐿2 = 𝐾𝑇𝑉𝑃𝑉

𝛥𝑖𝐿2 (10)

𝐶1 = (1 − 𝐾)𝑇𝑖𝐿1

𝛥𝑉𝐶1

=(1 − 𝐾)𝐾𝑇

𝛥𝑉𝐶1𝐼𝑃𝑉 (11)

𝐶2 = (1 − 𝐾)𝑇 (𝑖𝐿1 + 𝑖𝐿2)

𝛥𝑉𝐶2

=𝐼𝑜𝑇

𝛥𝑉𝐶2 (12)

𝐶3 = (1 − 𝐾)𝑇 (𝑖𝐿1 + 𝑖𝐿2)

𝛥𝑉𝐶3

=𝐼𝑜𝑇

𝛥𝑉𝐶3 (13)

𝐶𝑜 =𝐾𝑇 ∗ 𝑇𝑉𝑃𝑉

4𝛥𝑉𝑜𝐿2 (14)

The converter voltage output is not stable in

addition to it is affected seriously by the non-linear

nature of the PV output. The implementation of a

valuable controller is crucial to make the converter

output constant. In this work, ANFIS is used to

control the operation of the re-lift Luo converter as

it is capable of enhancing the operation of the

converter.

Fig. 2: RE-LIFT LUO Converter Circuit.

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Fig. 3: RE-LIFT LUO Converter is ON Condition

Fig. 4: RE-LIFT LUO Converter is OFF Condition

2.2 ANFIS Based MPPT

An innovative ANFIS based Maximum Power

Point Tracking (MPPT) method is proposed to

attain as well as tracking the maximum power of

the PV module under changing the weather

conditions. The proposed input variables are PV

voltage (VPV) and PV Current (IPV) and solar cell

temperature. The output variable is only duty cycle,

which is used to control the DC-DC RE-LIFT LUO

Converter in order to keep tracking maximum

power. Since the modeling of the conventional

Fuzzy Logic Controller is based on trial and error,

the probability of obtaining the optimal

performance is low. Therefore, obtaining

membership functions and fuzzy rules can be

prepared through learning using ANFIS.

The ANFIS is able of developing the input-

output mapping of training data sets, when it is

trained with sufficient number of epochs. By

adjusting the standards of membership functions,

ANFIS generates the set of fuzzy rules in order to

create appropriate output for altered values of

inputs. When the parameters of membership

functions are adjusted otherwise changed till the

error is reduced to least value. Once all the

parameters of membership function are in tuned,

the ANFIS model becomes learning model which is

ready to be used in MPPT control system. But,

before using ANFIS learning model for MPPT

control, its results are checked by using checking

data which is different starting training data. Over

if error produced is more than desired value,

parameters of membership functions are adjusted to

bring down the error. A DC-DC Relift Luo

Converter is designed to be placed between solar

PV modules as well as load in order to transfer

maximum power to load by changing duty cycle of

DC-DC Relift Luo Converter.

2.3 Bidirectional Battery Converter

The bidirectional battery converter allows power to

flow in both directions between the battery and the

load or grid, depending on the needs of the system

as shown in Figure 5. During periods of high load

or grid demand, the battery can discharge through

the DC/AC inverter to provide additional power.

During periods of low load or grid demand, excess

power from the grid can be used to charge the

battery through the AC/DC rectifier.

Fig. 5: Bidirectional Battery Converter.

The BDC, during charging mode, operates in

buck mode due to the fact that the dc-link serves as

its input, while the ESS functions as its load. The

capacitor and inductor values during buck mode is

estimated as,

Lbuck = (VDC − VESS)Dbuck

ΔILf (15)

Cbuck = (1 − Dbuck)

(8LbuckΔVEssf ∗ f) (16)

Where, the ripple current and switching

frequency are specified using the terms ∆𝐼𝐿 and 𝑓,

respectively, while the duty ratio is specified by the

term 𝐷. In the case of the discharging mode, the

conditions are reversed as the BDC is in boost

mode, though the ESS operates as the input this

time along with the dc-link serves as the load. The

capacitor as well as inductor values in this mode

are predictable as,

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Lboost

=(VESS)∗ (Dbuck)

(ΔILf) (17)

Cboost

=(VDC)∗ (Dboost)

(8RoΔVDCf) (18)

Where, output resistance and ripple voltage are

referred as 𝑅0 and ∆𝑉𝐷𝐶 respectively.

2.4 Inverter with LC Filter

The DC-DC RE-LIFT LUO Converter in order to

keep tracking maximum DC power, which the DC

power directly fed to the 3 phase voltage source

inverter. This inverter is converts DC to AC, which

the AC power fed to the LC filter. Here, LC filter is

suppressing the harmonics content present in

inverter output. Further, the pure AC power fed to

the microgrid. Then the Grid actual real power as

well as reactive power compare to reference real

power with reactive power. The error signal fed to

PI controller, the PI fine tuning the error signal and

fed to PWM generator. Based on the PWM signal 3

phase inverter produced the output voltage of the

microgrid.

3 Results and Discussion

3.1 Simulation Results Discussion

The proposed effort is implemented in MATLAB

simulation as well as the following results are

obtained. Solar panel produced DC output voltage

is 150V as shown in Figure 6. That the 150V DC is

fed to RE-LIFT LUO Converter, it convert 150V to

769V DC as shown in Figure 7. The RE-LIFT LUO

Converter output voltage is directly fed to three

phase voltage source inverter, it convert 769V to

520V AC as shown in Figure 8 and inverter current

is 0.4A as shows the Figure 9. Inverter output

voltage is sent to LC filter, filter filtering the

harmonic content present in AC output. Further

filter output voltage connected in the microgrid

network as a result grid voltage is 300V AC and

current is 10A as shows the Figure 10 and Figure

11.

Fig. 6: Solar panel output voltage

Fig. 7: DC RE-LIFT LUO Converter Output

Voltage

Fig. 8: Inverter Output Voltage

Fig. 9: Inverter Output Current

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Fig. 10: Grid Output Voltage

Fig. 11: Grid Output current

Fig. 12: Real power waveform

Fig. 13: Reactive power waveform

The Figure 12 and Figure 13 represents the

waveforms for real and reactive power of the

statcom inverter. The Figure 14 represents the

waveforms for Power Factor of the statcom

inverter. The graphic shows that there is variation

according to the current and voltage the load

demands. As a result, the system achieves a unity

power factor, demonstrating its effectiveness.

Fig. 14: Power Factor waveform

The Figure 15 represents the waveforms for

Voltage and Current IN phase of the statcom

inverter. It was discovered that when the voltage

and current waveforms were compared, a 360V

constant voltage was maintained. An IN phase

current, or one that initially increases and then

maintains stability while having distortions, is

produced in response to the voltage. The Figure 16

represents the total harmonic distortion. The grid

current THD obtained by the proposed work is

1.18%, as can be seen from the graph.

Fig. 15: Inphase voltage and current waveform

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Fig. 16: Total Harmonics Distortion (THD)

3.2 Hardware Results Discussion

Here experimental setup of 3 phase Voltage Source

Inverter, rectifier, transformer, RELIFT-LUO

Converter, battery, Bidirectional converter and

microgrid connected load as shown in the Figure

17. Using step down transformer 230V/12V is step

downed. In this 12V AC supply is connected to the

single phase diode rectifier circuits. Here, diode

rectifier which is converts AC to DC and rectified

DC voltage level is 11.2 V. In this 11.2V DC

supply is directly fed to the RELIFT-LUO

Converter, it can be boosted up to 89.6V DC.

Basically multi port DC-DC converter boost

ratio 1:4, but RELIFT-LUO Converter boost ratio

1:16. But, RELIFT-LUO Converter is PWM pulses

are applied only 50% as a result achieved 50%

output voltage. In this boosted DC voltage is

directly fed to the three phase Inverter circuit. This

inverter is convert DC to AC and inverter output

voltage 86.6V AC. In this circuit LC filter is used,

the function of LC Filter is, filtering the harmonics

content present in the output power of inverter. As

result LC filter output is 90V AC.

To facilitate the LC filters output voltage is fed

to the microgrid as shown in the DSO output Figure

18. If the any load demand may be present in the

microgrid, the signal conditioner can operated and

gives the feedback to DSPIC30F4011

Microcontroller. Based on the feedback,

Microcontroller it gives the signal of Pulse driver

circuit, the pulse driver supply the firing pluses to

the three phase inverter circuit as well as RELIFT-

LUO Converter.

Based on the firing pulses inverter and

RELIFT-LUO Converter can be operated and

improve the power quality. Here, the battery is

12V, suppose solar system power is available, that

time bidirectional converter operated at buck mode,

battery can get charged. Assume that, the solar

system power is not available, that time

bidirectional converter operated at boost mode,

battery can get discharged. The battery energy is

supplied to inverter, the inverter supply grid power.

Fig. 17: Hardware Snapshot

Fig. 18: Grid Output Voltage measured by DSO

4 Conclusion

The solar PV energy generating system has come

under examination as a key energy system by

electric utilities all over the world due to its use of

renewable energy sources to produce electricity.

Moreover, study is necessary to develop modern

technology, such as highly efficient batteries or

solar panels, as these sorts of systems become more

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common in the modern world. In this study, the PV

system has a Re-Lift Luo converter, which raises

the output voltage gain of the PV system. The

converter tracks the maximum power point and

utilizes a PWM regulator to improve overall device

efficiency. Using ANFIS will improve the MPPT

controller's accuracy. The energy management for

the proposed system is achieved using a

Bidirectional Battery converter along with a battery

system. With a three-phase VSI the input DC

power is inverted. An LC filter is used to decrease

the resulting harmonics. The grid synchronization

is achieved using D-Q theory and PI controller. The

simulation is run using MATLAB, and a minimal

THD value of 1.24% was discovered. Similarly, the

experimental hardware model is also verified and

results are discussed.

Acknowledgement:

I (Dr.E.Rajendran) would express my sincere

gratitude to my beloved Chairman

Er.K.Karunanithi for his kind inspiration and

supporting in addition to providing necessary

infrastructure for completion of this project and

research paper work. I would express my sincere

gratitude to my beloved CEO Dr.R.Sakthi

Krishnan for his kind stimulation and supported to

me. I would like to express my hearty appreciation

to My Parents Mr.P. Elumalai, Mrs.E.Rukkumani

and My Beloved Wife Dr.R.Vijaya

Lakshmi,B.S.M.S., and My Sweetheart Sons

Mr.R.Renu Prasaath and Mr.R.Sriram. Finally my

corresponding authors are grateful to Dr. V.Raji

and Mr.V.K.Dinesh Prabu for supporting regularly.

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E. Rajendran, V. Raji, V. K. Dinesh Prabu

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Contribution of Individual Authors to the

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Policy)

The authors equally contributed in the present

research, at all stages from the formulation of the

problem to the final findings and solution.

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Scientific Article or Scientific Article Itself

No funding was received for conducting this study.

Conflict of Interest

The authors have no conflicts of interest to declare.

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WSEAS TRANSACTIONS on POWER SYSTEMS

DOI: 10.37394/232016.2024.19.1

E. Rajendran, V. Raji, V. K. Dinesh Prabu

E-ISSN: 2224-350X

10

Volume 19, 2024