performance and control of micro-grid fed by renewable

Performance and Control of Micro-Grid fed by Renewable

Energy Generating Sources by using fuzzy logic controllers

Kayam Bhagawath Srinivas 1 , *N.M. Girish Kumar2

1PG Student, 2Associate Professor

Department Of EEE

S.V. College of Engineering, Tirupati-517507, India [email protected] , *[email protected] .

Abstract

This paper proposes a Design and Control of Micro-Grid fed by Renewable Energy

Generating Sources by using fuzzy logic controllers. The machine used for wind energy

conversion is doubly fed induction generator (DFIG) and a battery bank is connected to a

common DC bus of them. A sun powered photovoltaic (PV) exhibit is utilized to change over sun

oriented power, which is emptied at the basic DC transport of DFIG utilizing a DC-DC help

converter in a practical manner. The voltage and recurrence are controlled through a circuitous

vector control of the line side converter, which is joined with hang attributes. It changes the

recurrence set point dependent on the vitality level of the battery, which backs off over charging

or releasing of the battery. The framework is additionally ready to work when wind power

source is inaccessible. Both breeze and sun oriented vitality squares, have greatest power point

following (MPPT) in their control calculation. The framework is intended for complete

programmed activity taking thought of all the handy conditions. A simulation model of system is

developed in Matlab and simulation results are presented for various conditions e.g. unviability

of wind or solar energies, unbalanced and nonlinear loads, low state of charge of the battery.

I. INTRODUCTION

There are numerous remote areas on the planet, which don't approach power. There are

likewise numerous spots, which are associated with the network, be that as it may, they don't get

power for up to 10-12 hours in the day and because of it, monetary exercises of occupants

endure. A significant number of such places are wealthy in sustainable power source (RE)

sources, for example, wind, sun based and bio-mass. A self-ruling age framework using locally

accessible RE sources, can extraordinarily diminish the reliance on the network control, which is

prevalently fossil power. Wind and sun based vitality sources, are more most loved than bio-

mass based framework as last is helpless to store network issue. In any case, wind and sunlight

based energies experience the ill effects of abnormal state of intensity inconstancy, low limit use

factor joined with erratic nature. Because of these components, firm power can't be ensured for

independent framework. While the battery vitality stockpiling (BES) can be useful of bringing

Journal of Information and Computational Science

Volume 9 Issue 12 - 2019

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down power vacillation and expanding consistency, usage factor can be expanded by working

every vitality source at ideal working point. The ideal working point additionally called as

greatest power point following (MPPT), requires guideline of the working purpose of wind

vitality generator and sun based PV (Photovoltaic) cluster in term of speed and voltage to

separate most extreme electrical vitality from information asset. The MPPT can be accomplished

by power gadgets (PE) based control. PE based control can likewise help vitality the executives

for BES. Numerous creators have announced self-ruling sunlight based PV frameworks [1-2] and

self-sufficient breeze vitality frameworks [3-4]. In any case, self-ruling framework with just one

wellspring of vitality, requires enormous size of capacity and related PE parts. A crossover

vitality framework comprising of at least two kind of vitality sources, has capacity to decrease

the BES prerequisite and builds unwavering quality. Wind and sun based energies are regular

partners for hybridization. Both have been known to be corresponding to one another in day by

day just as yearly example of the conduct. Recognizing points of interest of this mix, numerous

creators have introduced self-ruling breeze sun powered cross breed frameworks [5-10]. The

most loved machine for little wind control application, is changeless magnet synchronous

generator [4-5]. It is conceivable to accomplish gearless design with PMSG, be that as it may, it

requires 100% evaluated converter notwithstanding costlier machine [11].

II. SYSTEMCOMPONENTS DESCRIPTION

A solitary line chart of the proposed sustainable power source age framework (REGS)

encouraged miniaturized scale network is appeared in Fig. 1. The equivalent has been intended

for area having most extreme power request and normal power request of 15 kW and 5 kW,

individually. The evaluated limit of both breeze and sun oriented vitality hinder in REGS, is

taken as 15 kW. The limit usage factor of 20% is considered for both vitality squares, which is

sufficient to give entire day vitality prerequisite of the village. As appeared in a schematic

outline, the breeze vitality source is detached utilizing a 3-post breaker from the system if there

should arise an occurrence of inadequate breeze speed. The DC side of both RSC and LSC

alongside HV side of sun based converter, is associated at the battery bank. RSC helps the breeze

vitality framework to keep running at the ideal pivot speed as required by W-MPPT calculation.

The LSC controls the system voltage and recurrence. The vitality stream chart of the framework

is appeared in Fig. 2. The plan approach of significant parts of REGS, is appeared following sub-

segments.

A. Wind Turbine and Gear

The wind turbine catches the motor vitality of the wind what's more, gives driving torque

to DFIG. The estimation of caught mechanical power is given as,



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Here Vw, and r, are wind speed and range of wind turbine individually. Cp is the

coefficient of execution of wind turbine and is numerically inferred as [13],

Fig. 1 Schematic of isolated micro-grid network fed by renewable energy source using battery

storage

1

⋋1 =

1

⋋+0.08𝛽 -

0.035

𝛽3+1 (3)

ë and â are the tip speed ratio(TSR) and the turbine blade pitch angle, respectively.TSR is related

to the of the turbine speed ùr, turbine radius r and wind speed Vw as,

The rated capacity of wind generator used in proposed scheme is 15 kW at a rated wind

speed (Vwr) of 9 m/s and rotational speed (ùrm) of 198 rad/s. The optimum TSR (ë*) and turbine

radius, are taken 5.67 and 4.3 m, respectively. The control action maintains W-MPPT till the

machine speed reaches ùrm. Having known ë*, Vwr and ùrm, gear ratio çG is determined from

(5) as,



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B. DFIG

An outside power stream in DFIG, is through both stator and rotor. Disregarding

misfortunes, at most extreme breeze speed, the ostensible intensity of DFIG (Pe) is identified

with appraised air hole control

(Pag) as, Pe= Pag/(1+|spmax |)) (6)

Spmax is the slip comparing to the turbine speed, ωrm and its worth is - 0.267. The speed scope

of DFIG is the speed comparing to slip 0.3 to - 0.267. Expecting air hole power(Pag) equivalent

to mechanical info control, the electrical power rating of the machine Pe comparing to most

extreme information control, is {15/(1+0.267)} =11.83 kW. At the point when the breeze turbine

is in administration, the total polarizing power prerequisite of machine is given by RSC.

Henceforth 11.83 kW limit of DFIG is satisfactory to change over mechanical power from 15

kW breeze vitality framework to electrical vitality. Taking extra edge because of electrical

misfortunes, a 12.5 kW machine is picked,

C. Transformer

The heap and stator terminals are associated with the LSC through a crisscross

transformer, which additionally gives unbiased to single stage loads at 415 V side. The most

extreme total worth of rotor slip, is 0.3 and as needs be, the most extreme rotor voltage Vrmax

winds up 125 V(0.3×415 V). The voltage at the LV side of crisscross transformer is additionally

picked to be equivalent to Vrmax Accordingly the transformer has a voltage proportion 415/125

V and its HV windings are associated with the stator and the load. The crisscross transformer

should meet the joined kVA prerequisite of burden just as associated channels. Appropriately, a

20 kVA transformer is picked, which is adequate to move evaluated control alongside gathering

responsive power prerequisite of the associated loads and channels at pinnacle request.

D. Battery Sizing

The most extreme working slip of machine is 0.3. The DFIG speed comparing to this slip

is 110 rad/s. At this slip, the line voltage of rotor Vrmax become 125 V (415×0.3). The required

DC transport voltage (Vdc) for PWM control is as,

𝑉𝑑𝑐 >{2 √(2

3 )𝑉𝐿}𝑚𝑖 (7)

VL is the higher of the line voltage of low voltage (LV) side of the crisscross transformer and the

rotor voltage at most astounding slip. The most extreme working slip is 0.3 and in like manner

the most astounding rotor voltage just as LV side of crisscross transformer is 125 V. The

regulation file, mi is picked to be solidarity. In light of these data sources, the DC transport

voltage Vdc required for working of PWM control must not be under 204 V. In the introduced

plan, Vdc is taken 240 V. The proposed smaller scale network is intended to give load



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prerequisite of 5 kW with no producing hotspot for an up to 12 hours. Taking extra 20% edge for

vitality misfortunes during trade of vitality, the required battery stockpiling limit ends up 72

kWhr. At the DC transport voltage of 240 V, the Ampere-Hour (AH) rating of battery ends up

300 AH (72,000/240). This is accomplished utilizing 40 quantities of 12V, 150 Ok lead corrosive

batteries separated similarly into two parallel circuits. A lead corrosive battery bank can be

securely worked between 2.25 V and 1.8 V per cell. This makes the most extreme battery voltage

Vbmax and least battery voltage Vbmin to be 270 V what's more, 216 V, individually. A battery

bank can be accepted to a DC source with invented capacitor Cb, interior obstruction Rin

associated in arrangement. Notwithstanding it, another obstruction Rb is associated over the

battery to signify vitality channel because of self release of battery. Cb in arrangement with the

battery means voltage change due to charging and releasing. The estimation of Cb is resolved as

[14],

𝐶𝑏= kwh*3600*1000/{0.5*( 𝑉𝑏𝑚𝑎𝑥2 − 𝑉𝑏𝑚𝑖𝑛2 )} (8)

Substituting factors in (8), Cb is acquired 19753 F.

E. Sunlight based PV System

The fundamental component of a sun powered PV framework is the sunlight based cell,

which depends on crafted by Rey-Boué et al [15]. The sunlight based boards are designed to

such an extent that the open circuit voltage of the sunlight based string stays not exactly the most

reduced downstream voltage of sunlight based converter or DC transport voltage, Vdc. The cell

numbers (Nc) in a string, is a component of its DC voltage and cell open circuit voltage Vocc as,

𝑁𝑐 = 𝑉𝑑𝑐𝑚/𝑉𝑜𝑐𝑐 (9)

The estimation of Vocc dependent on a run of the mill financially accessible cell qualities and its

worth, is taken as 0.64 V.

As assessed in sub-area (D), the base battery voltage can tumble down upto 216 V. Sun based

exhibit voltage (us) can change up to 3%, which is because of assembling resistance of electrical

amounts of module. Consequently Vdcm is taken as 210 V and as needs be, the required

quantities of cell, Nc as got from (9) comes to be 328 cells. To equally disperse the cells in a

standard arrangement, 324 cells are taken, which are separated in 9 modules of 36 cells each.

The proportion of Vocc to cell voltage at most extreme power point (MPP), Vmpc for an average

module trademark is 1.223. In like manner, the module voltage at MPP progresses toward

becoming (Vmpc x 36) 18.83 V and us winds up 169.47 V. At 15 kW sunlight based exhibit

limit, the aggregate string current at MPP moves toward becoming {15000/(9*18.83)}88.5 A.

The quantity of string in the sun oriented cluster is picked to be 11, as needs be module current at

MPP, Imp ends up 8.04 A. The proportion of short out current Isc to Imp for a run of the mill

module is 1.081 and likewise Isc is taken as 8.69 A.



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F. High Pass Filter

To diminish voltage swells, a high pass channel is utilized at stator terminal, which time

consistent ought to be not exactly essential recurrence for example 20 ms. Additionally, it ought

to be tuned a large portion of the exchanging recurrence. The exchanging recurrence is 10 kHz

and as needs be the channel to be intended for 5 kHz. In the present conspire, an arrangement RC

channel comprising of 5 Ω opposition and 15 F capacitance, is associated at the stator terminals

of DFIG. The channel gives under 5.43 Ω impedance for symphonious voltage having in excess

of 5 kHz recurrence.

III. CONTROL ALGORITHM

As appeared in Fig.1, REGS comprises of three converters, which control depictions, are

given as pursues.

A. Control of Solar Converter

A sun powered converter, which is a lift type DC-DC converter used to clear sun based

power with inserted S-MPPT rationale. It depends on steady conductance strategy [16]. The

SMPPT through insightful exchanging manages us so as the sun based framework works at

MPP. The stream graph of the MPPT calculation is appeared in Fig.3.

B. Control of LSC

Since the inland wind turbine creates control just for 0-70% of the time, the framework

ought to be intended to work at the point when no wind power is accessible. As appeared in the

control chart in Fig. 4, i* qs comprises of two parts. The first segment, iqs1 compares to the

power segment of DFIG current, when wind turbine is in task. The second segments iqs2 relates

to the power part drawn at the point when stator of DFIG isn't associated with the heap terminal.

1) Frequency Set point f*s Computation:

The stator recurrence is constrained by the LSC. In spite of the fact that the framework

needs to create evaluated recurrence, a hang trademark has been fused which gives recurrence set

point as,

𝑤𝑒∗ = 2*𝜋*[50+{2*(𝑉𝑑𝑐 – 240)/(𝑉𝑑𝑐-240)/(𝑉𝑑𝑐𝑚𝑎𝑥 -𝑉𝑑𝑐𝑚𝑖𝑛 )}] (10)

where Vdcmin,Vdcmax and Vdc are the base, most extreme and momentary DC transport

voltage, individually. Vdcmax is taken as 272.5 V, which is the transport voltage comparing

Vbmax during charging. So also, Vdcmin is being taken as 213.5 V, which transport voltage

compares Vbmin and the battery being released. With these figures, the recurrence fluctuates

from 49 Hz to 51 Hz.



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2) i*ds Computation:

i* ds (k)is the charging segment of stator current required at burden terminal and is registered as,

𝑖𝑑𝑠(𝑘)∗ =𝑖𝑑𝑠(𝑘−1)+𝐾𝑝𝑣 (𝑉𝑒𝑟𝑟(𝑘)-𝑉𝑒𝑟𝑟(𝑘−1)+𝐾𝑖𝑣𝑉𝑒𝑟𝑟(𝑘)dt (11)

where Verr(k) is the voltage error

𝑉𝑒𝑟𝑟(𝑘)= 𝑉𝐿𝑚∗ - 𝑉𝐿𝑀(𝑘) (12)

VLm is sufficiency of the detected three stage line voltage at generator terminals on per unit line

premise which is gotten from the sensed line voltages (vLab, vLbc and vLca) as,

𝑉𝐿𝑀={2( 𝑉𝐿𝑎𝑏2 + 𝑉𝐿𝑏𝑐

2 + 𝑉𝐿𝑐𝑎2 )/3}1/2 (13)

VLM∗ is reference line voltage, which is kept 585 V.

3) i*qs Computation:

As talked about, i*qs is isolated into two sub-parts as,

𝑖𝑞𝑠∗ =𝑖𝑞𝑠1

∗ +𝑖𝑞𝑠2∗ (14)

i* qs1 is the quadrature part of the generator along the stator field and is registered as,

𝑖𝑞𝑠1(𝑘)∗ = -𝐿𝑚* 𝑖𝑞𝑟(𝑘)/Ls (15)

i* qs2 is the required quadrature of stator current when DFIG isn't associated with the LSC(or

load) because of low wind speed or deficiency. It is the assessed as pursues,

𝜔eerr is the error of rated frequency f*e as computed from (10) and actual frequency fe. The

evaluated values of DC quantities i*ds and i*qs are transformed to AC quantities i*sa, i*sb and

i*sc using angle θstatorflux which is derived as,

ids and iqs are changed to 3-stage amounts utilizing change point θstatorflux. The inferred 3-

stage amounts what's more, the detected stator flows in a hysteresis current controller give

changing heartbeats to the converters.



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C. Control of RSC

RSC controls the speed of turbine with the goal that the framework works at MPP

independent of differing wind conditions. It additionally gives polarizing capacity to the

generator. The control theory as appeared in Fig. 5, incorporates control calculation for assurance

of quadrature and direct parts of rotor flows, Iqr, Idr and change edge, θslip.

1) i* dr Computation:

idr is identified with charging intensity of machine in field arranged vector

control(FOVC). The no-heap charging force is to be provided through RSC and the comparing

idr is as,

where, Xm is charging reactance of the DFIG. V* Lm is the reference sufficiency of line voltage

as got from (13).

2) i* qr Computation:

In FOVC at consistent stator transition ds , the quadrature part of the rotor current, i* qr

is corresponding to the torque [17]. i* qr is gotten from yield of the PI speed controller as,

Kpr and Kir are corresponding and fundamental increases of PI speed controller. ωrerr(k) is

speed blunder among reference and detected speed as,



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Fig. 2 Energy flow diagram of isolated micro-grid network fed by renewable energy source using

battery storage

ω*r is reference generator speed which is derived from (5) as,

Here 'k' is steady factor, which modifies the breeze speed setpoint to go amiss from MPP and can

check voltage ascend if there should arise an occurrence of low burden request and high age. The

estimation of k is resolved from the two transfers to be specific, k1 and k2 as appeared in Fig. 5.

The yield of transfer tumbles to 0.85 if the DC transport voltage increments past limit esteem.

The edge estimations of both transfer, are kept 260 and 265, separately. The k accomplishes

estimations of 0.85 and 0.72 as the Vdc surpasses 260 V and 265 V, separately. The assessed

estimations of idr * and iqr * are changed to AC reference rotor flows ira *, irb * and irc *

utilizing change point θslip. θslip is resolved as,

The error signals of reference currents and sensed currents (ira, irb and irc) through hysteresis

current regulator, generate control signals for RSC.

Fig. 4 Control diagram of LSC for REGS energy fed micro-grid

3) Battery Charging Mode:

The battery charging mode, is selected as per control diagram shown in Fig. 6. The

battery charging is achieved by direct vector control of rotor current.



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Fig. 5 Control diagram of RSC for REGS fed micro-grid

IV.FUZZY LOGIC MPPT CONTROLLER

As of late fluffy rationale controllers have been presented in the following of the MPP in

PV frameworks . They have the preferred standpoint to be hearty and generally easy to plan as

they do not require the information of the careful model. They do require in the other hand the

total learning of the task of the PV framework by the creator

Fig: 6. General diagram of a fuzzy controller

where Pph (k ) is the moment intensity of the photovoltaic generator. The info E(k ) appears if

the heap task point at the moment k is situated on the left or on the privilege of the greatest

power point on the PV trademark, while the information CE(k ) communicates the moving

heading of this point.

E(K)=Pph (k)−Pph (k−1)

Vph (k)−Vph (k−1)

CE(k) =E(k)-E(k-1)

The info E(k ) appears if the heap task point at the moment k is situated on the left or on

the privilege of the greatest power point on the PV trademark, while the information CE(k )

communicates the moving heading of this point.

The fluffy surmising is done by utilizing Madani's strategy, (Table 1), and the defuzzification

utilizes the focal point



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of gravity to figure the yield of this FLC

which is the obligation cycle:

E/∆

E

B

N

M

N

Z SP MP BP SN

Z Z Z Z Z Z Z Z

SN BP BP BP SP M

N

BN B

N

MN BP MP SP SP SN M

N

B

N

BN BP MP SP MP SN M

N

B

N

SP B

N

BN B

N

SN MP BP BP

MP B

N

M

N

SN SN SP MP BP

BP B

N

M

N

SN M

N

SP MP BP

These two variables and the control action D

for the tracking of the maximum power

point are illustrated in figure

Fig.8.Change in error

Fig.7.Error

Simulation results

Case_1. Performance of REGS fed

micro-grid with wind energy source

fig.9.Vw

fig.10.Wr



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fig.11.Cp

Fig.12.Vt

fig.13.frequency

Fig.14.Vdc

Fig.15.Wind power

Fig.16.Load power



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Simulation results by using fuzzy logic controllers

Case_1. Performance of REGS fed micro-grid with wind energy source

Fig.17.Vw

Fig.18.Wr

fig.19.Cp

Fig.20.Wind power

fig.21.Vdc

fig.22.Vt

fig.23.Frequency

Fig.24.Load power



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VI. CONCLUSION

This paper proposes a Design and Control of Micro-Grid fed by Renewable Energy

Generating Sources by using fuzzy logic controllers. REGS includes of wind and solar which

are intended to extricate the most extreme power from the sustainable power sources and at a

similar time, it gives quality capacity to the purchasers. The system has been intended for

complete computerized activity. This work additionally exhibits the estimating of the real parts.

The presentation of the framework has been exhibited for change in information conditions for

various sort of burden profiles. Under all the conditions, the power quality at the heap terminals,

remains inside adequate breaking point. The adequacy of the framework is additionally gave test

results with model in the research facility. The framework has likewise imagined the outside

battery charging by using the rotor side converter and its sensors for accomplishing rectifier task

at solidarity power factor.

VII. REFERENCES

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Transactions on Industrial Electronics, vol. 62, no. 6, pp. 3595-3606, June 2015.

[2] M. Das and V. Agarwal, “Novel High-Performance Stand-Alone Solar PV System

With High-Gain High-Efficiency DC–DC Converter Power Stages,” IEEE Transactions on

Industry Applications, vol. 51, no. 6, pp. 4718-4728, Nov.-Dec. 2015.

[3] A. B. Ataji, Y. Miura, T. Ise and H. Tanaka, “Direct Voltage Control With Slip Angle

Estimation to Extend the Range of Supported Asymmetric Loads for Stand-Alone DFIG,” IEEE

Transactions on Power Electronics, vol. 31, no. 2, pp. 1015-1025, Feb. 2016.

[4] N.A. Orlando, M. Liserre, R.A. Mastromauro and A. Dell’Aquila, “A survey of

control issues in PMSG-based small wind turbine system,” IEEE Trans. Industrial Informatics,

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[5] T. Hirose and H. Matsuo, “Standalone Hybrid Wind-Solar Power Generation System

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[6] Z. Qi, “Coordinated Control for Independent Wind-Solar Hybrid Power System,”

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[7] M. Rezkallah, S. Sharma, A. Chandra and B. Singh, “Implementation and control of

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IEEE Industry Applications Society Annual Meeting, Portland, OR, 2016, pp. 1-7.



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[8] A. Hamadi, S. Rahmani, K. Addoweesh and K. Al-Haddad, “A modeling and control

of DFIG wind and PV solar energy source generation feeding four wire isolated load,” IECON

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[9] S. K. Tiwari, B. Singh and P. K. Goel, "Design and control of autonomous wind-solar

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[10] S. K. Tiwari, B. Singh and P. K. Goel, “Design and control of micro-grid fed by

renewable energy generating sources,” 2016 IEEE 6th Inter. Conference on Power Systems

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performance and control of micro-grid fed by renewable

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