Design and Analysis of PID and Fuzzy-PID Controller for

Voltage Control of DC Microgrid

Presented By : Dr. Francisco M. Gonzalez-Longatt

Deptt. Of Electrical Engg.

University of Loughborough, Loughborough, UK

Co-Author:

R. K. Chauhan and Dr. B. S. Rajpurohit

School of Computing & Electrical Engg

Indian Institute of Technology Mandi,

India

Dr. R. E. Hebner

Center for Electromechanics

University of Texas Austin,

USA

Dr. S. N. Singh

Deptt. of Electrical Engineering

Indian Institute of Technology Kanpur,

India

Stability issues are more prevalent in microgrids than in a

large electric grid because power and energy ratings are

much lower.

In dc systems there is no reactive power interactions,

which seems to suggest that there are no frequency stability

issues.

System control seems to be oriented to voltage stability.

There is a change in the power and load due to demand

variations. This change leads to create fluctuations in the

voltage level.

2

The objective is to keep the DC microgrid voltage at the

reference DC level (i.e. at 124V here).

A PID controller is designed for the DC microgrid voltage

control.

A fuzzy PID controller also designed which is taking the

advantage of PID experiences and Fuzzy knowledge.

Both the controllers is compared based on the performance

parameters.

3

4

Public

Utility

SDT

Load

Home-2

PV Plant

+

-

Voltage

Sensor

Load

Home-4

PV Plant

Load

Home-1

PV Plant Load

Home-3

PV Plant

PWM

Controller

Filter

Vg

Vd

+

-

5

00:00 12:00 24:00

0

5

10

Time (Hour)

Pow

er (

kW

)Home 1

00:00 12:00 24:00

0

5

10

15

Time (Hour)

Pow

er (

kW

)

Home 2

00:00 12:00 24:00

0

2

4

6

Time (Hour)

Pow

er (

kW

)

Home 3

Consumed Power

Solar Power

00:00 12:00 24:00

0

2

4

6

Time (Hour)

Pow

er (

kW

)

Home 4

6

00:00 5:00 10:00 15:00 20:00 24:00-10

-5

0

5

10

15

20

25

Time (Hour)

Pow

er

(kW

)

Consumed Power

Solar Power

Grid Power

• The output of the PID controller can be expressed as

(1)

• Transfer function can be expressed as:

7

PID

Controller

eVg(s)

u(s)+ -

Vo(s)Vd(s) Fuzzy PID Controllere(s)

Vg(s)uf(s)

+-

Vo(s)Vd(s)

Fuzzification Inference Defuzzification

Fuzzy

Knowledge Based Rule Based

PID

1( ) ( ) ( ) ( )p i du s K e s K e s K Se s

S

(2)

where

( ) 1( )

( )p i d

u sG s K K K s

e s s

( ) de s V Vg

( ) d oe s V V

8

System fuzzy-pid: 2 inputs, 3 outputs, 49 rules

e (7)

ec (7)

Kp (7)

Ki (7)

Kd (7)

Fuzzy-PID

(Mamdani)

49 rules

-3 -2 -1 0 1 2 3

0

0.5

1

e, ec

Deg

ree

of

mem

bers

hip

NB NM NS Z PS PM PB

Membership function for FL-PID inputs error and change in error

-0.2 -0.1 0 0.1 0.2 0.3

0

0.5

1

Kp

NB NM NS Z PS PM PB

-0.06 -0.04 -0.02 0 0.02 0.04 0.06

0

0.5

1

KiDeg

ree o

f m

em

bers

hip

NB NM NS Z PS PM PB

-3 -2 -1 0 1 2 3

0

0.5

1

Kd

NB NM NS Z PS PM PB

Membership function for FL-PID outputs Kp, Ki, and Kd

9

e

ecNB NM NS Z PS PM PB

NB NB NB NB NM NM Z Z

NM NB NB NM NM NS Z Z

NS NM NM NS NS Z PS PS

Z NM NS NS Z PS PS PM

PS NS NS Z PS PS NM PM

PM Z Z PS PM PM PB PB

PB Z Z PS PM PB PB PB

e

ecNB NM NS Z PS PM PB

NB PB PB PM PM PS PS Z

NM PB PB PM PM PS Z Z

NS PM PM PM PS Z NS NM

Z PM PS PS Z NS NM NM

PS PS PS Z NS NS NM NM

PM Z Z NS NM NM NM NB

PB Z NS NS NM NM NB NB

e

ecNB NM NS Z PS PM PB

NB PS PS Z Z Z PB PB

NM NS NS NS NS Z PS PM

NS NB NB NM NS Z PS PM

Z NB NM NM NS Z PS PM

PS NB NM NS NS Z PS PS

PM NM NS NS NS Z PS PS

PB PS Z Z Z Z PB PS

Fuzzy Rules For Kd

Fuzzy Rules For Kp Fuzzy Rules For Ki

10

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

20

40

60

80

100

120

140

160

180

Time (Sec)

Volt

age (

Vo

lt)

Simulated Grid Voltage

Measured Grid Voltage

Desired Grid Voltage

00:00 02:30 05:00 07:30 10:00 12:30 15:00 17:30 20:00 22:30 25:00110

120

130

140

150

160

170

Time (Hour)

PID Controller

Volt

age

(Volt

)

Solid Line is the Measured Voltage

Dotted Line is the Desired Voltage

Dashed line is the Simulated Voltage

11

00:00 02:30 05:00 07:30 10:00 12:30 15:00 17:30 20:00 22:30 25:00110

115

120

125

130

135

140

145

Time (Sec)

Fuzzy PID Controller

Vo

ltag

e (V

olt

)

Solid Line is the Measured Voltage

Dotted Line is the Desired Voltage

Dashed line is the Simulated Voltage

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

20

40

60

80

100

120

140

160

Time (Sec)

Volt

age (

Vo

lt)

Measured Grid Voltage

Simulated Grid Voltage

Desired Grid Voltage

12

Controller

Type Time Response Parameters

Rise

time

(Sec)

Settling

time

(Sec)

Over-

shoot

(%)

Peak time

(Sec)

Steady

state

error (%)

PID 0.0148 1.6091 0.326 0.47 0.9231

FL-PID 0.0264 1.3609 0.132 0.41 0.2325

The FL-PID leaves a good impact in the sense of

performance parameters.

FL-PID is superior and better for DC microgrid voltage

controlling.

The intelligent controlling of the DC microgrid voltage which

has been done by the fuzzy method.

The paper has been able to demonstrate the potential of

fuzzy control over other conventional control.

A stable and efficient DC system can be obtained by using the

controlled voltage obtained from the proposed controllers (PID

and FL-PID).

13

• N. D. Hatziargyriou, H. Asano, H. R. Iravani, and C. Marnay, “Microgrids,” IEEE Power Energy Mag., vol.5, no.4,

pp.78–94, Jul. 2007.

• N. Pogaku, M. Prodanovic, and T. C. Green, “Modeling, analysis and testing of autonomous operation of an inverter-

based microgrid,” IEEE Trans. Power Electron, vol.22, no.2, pp.613–625, Mar. 2007.

• J. M. Carrasco, L. G. Franquelo, J. T. Bialasiewiez, E. Galvan, E Guisado, M. M. Prats, J. I. Leon, and N. M. Alfonso,

“Power-electronic systems for the grid integration of renewable energy sources: A survey,” IEEE Trans. Power

Electron, vol.53, no.4, pp.1002–1016, Jun. 2006.

• R. K. Chauhan, B. S. Rajpurohit, “DC Distribution System for energy efficient buildings,” in proc. 2014 IEEE 18th

National Power System Conference, India, Dec. 18-20, 2014, pp.1-6.

• J. C. Choi, H. Y. Jeong, D. J. Won, S. J. Ahn and S. I. Moon, “Cooperative voltage control of distributed generation and

grid connected converter in dc microgrid,” Renewable Energy and Power Quality Journal, no.2, Mar. 2013.

• Y. Ito, Y. Zhongqing, and H Akagi, “DC microgrid based distribution power generation system,” in proc. 2004 IEEE 4th

International Conference on Power Electronics and Motion Control, vol. 3, pp. 1740-1745.

• H. Kakigano, A. Nishino, and T. Ise, “Distribution voltage control for dc microgrid with fuzzy control and gain-

scheduling control,” in proc. 2011 IEEE 8th International Conference on Power Electronics and ECCE Asia, pp. 254-

263.

• B. Singh, A. Chandra, and K. Al-Haddad, “Computer-aided modeling and simulation of active power filters,” Elect.

Mach. and Power Syst., vol.27, no.11, pp.1227–1241, 1999.

• K. Chatterjee, B. G. Fernandes, and G. K. Dubey, “An instantaneous reactive volt-ampere compensator and harmonic

suppressor system,” IEEE Trans. Power Electron., vol. 14, no. 2, pp. 381–392, Mar. 1999.

• S. Jain, P. Agarwal, and H. O. Gupta, “Design simulation and experimental investigations on a shunt active power filter

for harmonics and reactive power compensation,” Elect. Power Compon. and Syst., vol. 32, no. 7, pp. 671–692, Jul.

2003.

• F. Blaabjerg, R. Teodorescu, M. Liserre, and A.V. Timbus, “Overview of control and grid synchronization for

distributed power generation systems,” IEEE Trans. Ind. Electron., vol. 55, no.3, pp. 1398–1411, Oct. 2006.

14

• S. Buso, L. Malesani, and P. Mattavelli, “Comparison of current control techniques for active power filter

applications”, IEEE Trans. Ind. Electron., vol.45, no.5, pp.722-729, Oct. 1998.

• M. Ho, and C. Lin, “PID controller design for robust performance,” IEEE Trans. Automatic Control, vol. 48, no. 8,

pp. 1404–1409, Aug. 2003.

• G. K. I. Mann, B. G. Hu, and R. G. Gosine, “Analysis of direct action fuzzy PID controllers structures,” IEEE

Trans. Syst. Man Cybern., vol. 29, no.3, pp.371–388, Jun. 1999.

• B. K. Bose, “Expert systems, fuzzy logic and neural network, applications in power electronics and motion

control,” in proc.1994 IEEE Piscataway, NJ: IEEE Press, ch. 11, pp. 1303 - 1323.

• V. S. C. Raviraj and P. C. Sen, “Comparative study of proportional integral, sliding mode, and fuzzy logic

controllers for power converters,” IEEE Trans. Ind. Appl., vol.33, no.2, pp. 518–524, Mar./Apr. 1997.

• C. C. Lee, “Fuzzy logic in control systems: fuzzy logic controller-part I”, IEEE Trans. Syst. Man. Cybern., vol.20,

no. 2, pp. 404-418, Mar/Apr 1990.

• K. Rajani and R. Pal Nikhil R., “A robust self-tuning scheme for PI and PD-type fuzzy controllers,” IEEE Trans.

Fuzzy Syst., vol.7, no.1, pp. 2-16, Feb. 1999.

• H. Baogang, G. K. I. Mann and R. G. Gosine, “New methodology for analytical and optimal design of fuzzy PID

controllers”, IEEE Trans. Fuzzy Syst., vol.7, no.5, pp.521-539, Oct. 1999.

• Z. W. Woo, H. Y. Chung and J. J. Lin, “A PID type fuzzy controller with self-tuning scaling factors,” Fuzzy Sets and

Syst., vol.115, no.2, pp. 321-326, Oct.2000.

• I. Pan, S. Das and A. Gupta, “Tuning of an optimal fuzzy PID controller with stochastic algorithms for networked

control systems with random time delay,” ISA Trans., vol.50, no.1, pp.28-36, Jan. 2011.

• D. Chen and L. Xu, “Autonomous dc voltage control of a dc microgrid with multiple slack terminals,” IEEE Trans.

power syst., vol.27, no.4, pp.1897-1905, Nov.2012.

15

Acknowledgement

The authors would like to acknowledge the financial

support received by

DST-UKIERI

16

Thanks!

17