The document discusses the design and analysis of PID and fuzzy-PID controllers aimed at voltage control in DC microgrids, emphasizing stability challenges and voltage fluctuation due to demand variations. It highlights the effectiveness of the fuzzy-PID controller in achieving superior performance parameters compared to the standard PID controller. The findings suggest that intelligent fuzzy control can enhance voltage stability and control in DC microgrid systems.

1. 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

2. 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

3. 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. 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. 5
00:00 12:00 24:00
0
5
10
Time (Hour)
Power(kW)
Home 1
00:00 12:00 24:00
0
5
10
15
Time (Hour)
Power(kW)
Home 2
00:00 12:00 24:00
0
2
4
6
Time (Hour)
Power(kW)
Home 3
Consumed Power
Solar Power
00:00 12:00 24:00
0
2
4
6
Time (Hour)
Power(kW)
Home 4

6. 6
00:00 5:00 10:00 15:00 20:00 24:00
-10
-5
0
5
10
15
20
25
Time (Hour)
Power(kW) Consumed Power
Solar Power
Grid Power

7. • The output of the PID controller can be expressed as
(1)
• Transfer function can be expressed as:
7
PID
Controller
e
Vg(s)
u(s)
+ -
Vo(s)Vd(s) Fuzzy PID Controller
e(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 s
G s K K K s
e s s
   
( ) de s V Vg 
( ) d oe s V V 

8. 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
Degreeofmembership
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
Ki
Degreeofmembership
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. 9
e
ec
NB 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
ec
NB 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
ec
NB 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. 10
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
0
20
40
60
80
100
120
140
160
180
Time (Sec)
Voltage(Volt)
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 25:00
110
120
130
140
150
160
170
Time (Hour)
PID Controller
Voltage(Volt)
Solid Line is the Measured Voltage
Dotted Line is the Desired Voltage
Dashed line is the Simulated Voltage

11. 11
00:00 02:30 05:00 07:30 10:00 12:30 15:00 17:30 20:00 22:30 25:00
110
115
120
125
130
135
140
145
Time (Sec)
Fuzzy PID Controller
Voltage(Volt)
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 2
0
20
40
60
80
100
120
140
160
Time (Sec)
Voltage(Volt)
Measured Grid Voltage
Simulated Grid Voltage
Desired Grid Voltage

12. 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

13. 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

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16. Acknowledgement
The authors would like to acknowledge the financial
support received by
DST-UKIERI
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17. Thanks!
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