a novel mrac algorthim for maximum power point … · isolation. in fig.2 the photovoltaic system...

A NOVEL MRAC ALGORTHIM FOR MAXIMUM POWER POINT TARCKING

1Yandrathi Ramya, Student, Department of Electrical Engineering K L University,Vaddeswaram,India

2Pedavalli Lavanyasri, Student, ,Department of Electrical Engineering K L University,Vaddeswaram,India

3Yadlapalli Sainath,Assistant Professor, Department of Electrical Engineering K L University,Vaddeswaram,India

ABSTRACT

A MRAC method for Maximum Power Point Trackingin PV system is presented. By combining

the robustness of RCC and MRAC with the accuracy of fractional order, this paper proposed

method can improve the tracking accuracy in the conventional MPPT. First the ripple correlation

control level and then the model reference adaptive control of second level architecture can

reduce the complexity of the system in the environment of photovoltaic systems. When the MPP

is approached there the small oscillations are eliminate at the MPP. To improve the MPPT in this

paper proposed multilevel adaptive control algorithms and mainly focused on MRAC algorithm,

it also compensate underdamped characteristics of the conversion systems. MATLAB/Simulink

software is used to simulate a PV power system and verify the system with the proposed

algorithms with various simulation models. An enhanced MPPT algorithm, implemented on a

field programmable gate array. At the end a boost DC-DC converter, carried out is to evaluate,

performance of the system. The experimental simulation results are shown that this method can

improve the performance simultaneously.

Index Terms-MPPT, MRAC, Photo voltaic system, RCC.

I. INTRODUCTION

In the last three decades research scholars did, a great interest in using the solar energy

applications and this solar technology had been extremely growing day to day. These solar

technology applications are widely used in urban rural areas, satellites, and electrical drivers, etc.

Nowadays solar technology is utilizing as an alternative of thermal energy source for generating

electrical power. A PV cell is one kind of semiconductor material which photocurrent can cross

the p-n junction of the energy gap. However the characteristics between PV diffusion current and

ambient conditions can be described with dynamic behavior as fractional order diffusion [1], [2].

It is required to keep a PV system operation near the maximum power point is to enhance the

power efficiency.

Many research scholars are implemented MPP tacking (MPPT) algorithms in PV systems such

as observation, perturbation, and hill climbing [3], constant or fractional voltage/current [4],[5],

and particle swarm optimization(PSO). There in PV cell power generation systems are the key

problems can be optimize, with the effective solar arrays, meanwhile to enhance the hole system

stability. Recently the power control methods are generating effective output, of solar technology

including multiple method of numerical models. In this paper a novel technological Lyapunov,

MRAC algorithm is implemented. FLC need very less knowledge of the PV system

mathematical model provides an effective performance under different atmospheric conditions

[6]-[9]. Here the main drawback is conventional FLCs are fixed on fuzzy fields. There Neural

International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 1 (2017) © Research India Publications. http://www.ripublication.com

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Network and Fuzzy logic technologies are developed for quick convergence of efficient

performance in different areas of conditions but the development of these technologies are bit

difficult [6]-[9]. Tackle this difficulty an ideal MPPT control techniques are implemented easy,

andinexpensive, rapid convergence of Maximum Power Point of minor oscillations at the output

voltage.

In this article we are implemented a multilevel MPPT control methods could be interconnect

with Model Reference Adaptive Control (MRAC), and Ripple Correlation Control (RCC)[10]-

[13].

Fig.1. MPPT control algorithm.

In Fig.1 shows the control level of array voltage Vpv,and Ppv are push the inputs of the RCC.

Then Ripple Correlation Control unit find the d(t) duty-cycle, is to produce highly generated

energy for the load in the state-of-art. Then other controller is will generate the duty-cycle is to

measure with RCC, control unit is to give into another controller for MRAC architecture of PV

system is increased to reduce the transient oscillationson the output voltage. To protect plant

from oscillations displaying and a critically damped systems are implemented the reference

model of Fig.1. The proposed referenced model is utilized some reference model parameters of

both feedback and feed forward controllers areCb. and Cf. When we alter/adjust accurate

parameters of controller is enable the plant output is to relative to the output of reference model

to get error convergence to become zero, also it obtained the maximum power. The two level

controllers are reduce the complexity of the control systemmainly RCC is used for slow dynamic

and MRAC is for fast dynamics. Our proposed two level algorithms are effectively working of

the decoupled RCC and MRAC levels are having stability analysis.

II. RELATED WORK

The photovoltaic systems having the current-voltage characteristics under various stages of solar

isolation. In Fig.2 the photovoltaic system regulates the current and voltage, there solar panels

are used to convert dc-dc is interface with MPPT will produce the maximum power[10],[11].

Fig.2. is integration of control system which contains boost-converter is used for delivering the

optimal power.


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Fig.2. Boost converter system with MPPT controller.

There in boost converter in fig.2 shows voltage, and current getting from MPPT controller, it

yields the duty-cycle. This duty-cycle,of the transistor is like array of voltage from Eq.1.

Vpv = ipvRO(1-d)2 (1)

From E.q.1. Vpv, ipv is array of voltage and current, and RO is the load resistance. Array of

voltage, current can consists of DC terms of Vpv and Ipv as well as ripple terms of 𝑣𝑃�̂�and𝑖𝑃�̂�. It

provide the conventional MPPT algorithm is to compute the converters duty cycle. And also

increase the transient response in the MPPT control is for duty cycle and array voltage. The

complete boost converter model is dynamic in [12]. For best practical transient response analysis

we used simple equivalent circuit for control signals.

Fig.3. PV power conversion system equivalent circuit.

In Fig.3. Shownresistor R1 is to model the array of solar with array voltage 𝑣𝑃�̂�and𝑖𝑃�̂�. Array

current its terminals. As we seen in fig.3. the dynamic model is shown existing load presented at

the boost-converter of storage system.

III. PROPOSED METHODOLOGY

To propose for MPPT a multi-level algorithm is using Fig.1.firstly RCC is used to findthe duty

cycle, from this we are expecting to get maximum existing power to load in the system.

Secondly MRAC is used to regulates theconverter is, and itresponsible to duty-cycle is produced

the RCC, and prevent the voltage is to delivered the oscillations of various modifications solar

insolation. Generally Ripple Correlation Control is responsible to handles/maintains what are the


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modification existing of solar insolation, it tunes the process forRCC quickly to catch the

variations in solar system. But the RCC required lesstime with comparison of dynamic system

variations. When MRAC comparison is responsible for maintaining the characteristics in

damping from converters environmental areas variations. In MRAC the tuning processes is bit

fast to catch whenever changes present in a converter working point and the response of RCC.

However the time constant of the MRAC is very less than that of the RCC. Mainly the RCC is

used for switching the ripple converter to perturb and track the MPP from system. The RCC has

been proven with the minimum controller complexity and the implementation is very straight

forward [12].

The observation of RCC is based on derivatives with respect to time, and the array voltage VPV,

and, power PPV to become greater the zero to the MPP and lesser the zero to the MPP, and

absolutely zero to MPP.

𝑑𝑝𝑃𝑉

𝑑𝑡

𝑑𝑣𝑃𝑉

𝑑𝑡> 0 When VPV< VM (2)

𝑑𝑝𝑃𝑉

𝑑𝑡

𝑑𝑣𝑃𝑉

𝑑𝑡< 0 When VPV< VM(3)

𝑑𝑝𝑃𝑉

𝑑𝑡

𝑑𝑣𝑃𝑉

𝑑𝑡 = 0 When VPV = VM (4)

Fig.4. MRAC structure and controller structure in the proposed MRAC.

The existing RCC aim is to find the, duty-cycle is to deliver maximum power. The proposed

MRAC algorithm is used to maintain the behavior of critically damped array voltage. For MRAC

adaptive controller model with variant parameters as in fig.5 here we change the signs, then the

plant control model has positive coefficients. Whereup(t) and yp(t) is used to represent the IO of

the plant and also express model as

Gp(S) = 𝑦𝑝(𝑆)

𝑢𝑝(𝑆) =

𝑘𝑝

𝑆2+𝑎𝑝(𝑆)+𝑏𝑝 (5)


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From eq.5 the arguments kp,ap, and bp can be implied. And also chosen the model reference to

exhibit the effective output ym(t) for input r(t)

Gm(S) = 𝑦𝑚(𝑆)

𝑟(𝑆) =

𝑘𝑚

𝑆2+𝑎𝑚(𝑆)+𝑏𝑚(6)

Where positive gain is km ,am, and bm is calculate the critical damped of reference model for step

response. Objective of this model is to design up(t), so that yp(t) is asymptotically tracks ym(t).

IV. Simulation Experimental Results

A MATLAB/Simulink software are used for model designof a PV system and conformed

proposed algorithms by simulations.

Fig.5. PV Designed model

Fig.6. Converter output current and voltage.


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Fig.7. PV-array Current and Voltage.

The PV designed model is shown in fig.5 and the PV cell reference voltage and actual voltage in

fig.8

Fig.8. PV cell reference Voltage and Actual voltage


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Fig.9. Converter output Current and Voltage.

Fig.10. Change in power (dp) in RCC.


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V CONCLUSION AND FUTURE SCOPE

In this paper a PV system an MRAC approach of MPPT algorithm is proposed for delivering

optimized power from the PV array to the load. And we did a multi-level adaptive control

algorithm, it can be tackle the difficulties in the controller and it handles what are the

perturbations existing in PV system. Mainly we focused on MRAC design model, characteristics

are compensatetheunderdamped power systems. Further research we can improve the

performance of MPPT in different conditions. These environmental changes in solar irradiations

or changes in ambient temperature or even both.

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a novel mrac algorthim for maximum power point … · isolation. in fig.2 the photovoltaic system...

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