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
17
Embed
Design and Analysis of PID and Fuzzy-PID Controller for Voltage Control of DC Microgrid , IGST Asia 2015
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
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