Smart Grid Control with Fuzzy Integrator for Micro Hydro Connected to Low Voltage Distributor PT. PLN (Persero).
Smart Grid Control with Fuzzy Integrator for Micro Hydro
Connected to Low Voltage Distribution PT. PLN (Persero)
Lie Jasa1 , IGA Raka Agung2, I Putu Ardana3, Ardyono4 ,Mauridhy Hery Purnomo5
1,2,3
Electrical Engineering Department,Udayana University, Bali, Indonesia
4,5
Electrical Engineering Department Sepuluh Nopember Institute of Technology Surabaya, Indonesia
1
liejasa@unud.ac.id, 2puturaka@ee.unud.ac.id, 3ardana@ee.unud.ac.id, 4priyadi@ee.its.ac.id, 5hery@eits.ac.id
Abstract— The capacity of electrical energy supply PT. PLN
(persero) insufficient to public demand in Indonesia. Micro
Hydro Power Plant ( MHPP ) is a small-scale power plants which
relatively easy to developed in remote areas. The generated
energy by MHPP must be transmitted to the power distribution
network. In this study researchers wanted to answer the
problems how to make a model auto control which connects the
MHPP with power network distribution PT.PLN(Persero).The
results of this studies is a MHPP can be auto controlled by I, PI,
PID and Fuzzy-I controller. Smart control of Fuzzy-I controller
make the system to stable with a small overshoot values. It is
better than I, PI or PID controller.
Keyword : Micro hydro, Energy, Fuzzy
I.
INTRODUCTION
Impact of excessive energy use for this is the cause of air
pollution, global warming and climate change. Water energy
is an environmentally friendly energy source, green, unlimited
and renewable nature. All countries in the world today
continues to conduct research on water energy, wind and solar,
which is used as one of the future energy development policy
options. Proven installation of Renewable Energy is currently
in parts of the world increased to 30%. [1],[2]
The energy plays an important role for population in the
Indonesia. The energy demand is significantly increases every
year but the energy resource is limited and decreases
especially conventional energy. Hydropower[3] is one of clean
energy resources in the world. It is also the most reliable and
effectively cost renewable energy resource among the others.
Small hydropower schemes are getting increasingly popular
because of its simplicity design, easy in operation, and lower
environment.
The energy produced by the micro-hydro power plant
(MHPP) should be used by everyone. But the frequency
output of MHPP should to match with the frequency of the
network PT. PLN (Persero). This research proposes to find
model control system about it.
This study focused on discussing the frequency control of
the generator mounted on the MHPP to be set for frequency
changes (Δf) by using a low voltage reference of PT.
PLN(Persero). This control is using fuzzy logic consisting of
7- rule member’s ship function to control error (e) and change
of error (de).
Block Control of micro hydro set including the
components of governor, valves, turbine and generator is
made in the transfer function. Fuzzy logic uses to reduce the
error from occurring plant using Matlab. Fuzzy logic
controller has 2 input e and de and one output u.
II.
LETERATURE REVIEW
A. Hydraulics power theory
Theorem of water flow is used to determine the amount
of energy that can be generated from the flowing water. The
total extractable hydraulic power from the flowing water is
given by the expression of Pin = ρ x g x Q x H, where Pin is the
hydraulic power input to the wheels (W), ρ is the density of
water (kg/m3), g is the acceleration due to gravity (9,81m/s2),
Q is the volumetric water flow rate (m3/s) and H is the
difference in total energy line upstream and downstream of the
wheel (m). The angular velocity ω (rad/s) of the wheels is
calculated from the number of revolutions N at the given load
in revolutions per minute (RPM) of the wheel as : ω = 2 x π x
N/60. The shaft torque τ (Nm) is the product of the force F of
water striking the blades of the water wheel (N) and the
moment arm length (m) which, in this case, is the radius of the
pulley r. Force is equal to the differences in the mass obtained
from the two load cells time the acceleration due to gravity. τ
= m x g x r. Subsequently the mechanical power output Pout
available at the wheel shaft is determined from the measured
torque τ and the corresponding angular speed of the wheel ω
as : Pout = ω x τ = 2 x π x N x τ/60. By calculating the power of
output and input, the mechanical efficiency η of the wheel is
therefore: η = Pout / Pin x 100%
Automatic control system of micro-hydro is built in a
closed loop. First some water are flow in the valve, it continue
to the spill way and rotate the turbine. The control system of
MHPP as shown at Figure 1
B. Governor Controller
Control for hydro power plant, hydraulic mechanical
governor and electro-hydraulic, PID Controller [4] is used
commonly. MHPP in Gambuk, Bali[4],[5],[6] don’t have a
controller for control the system. Because It does not use a
controller to control the system. Frequency output never stable
if load changes. This condition is very difficult when
connecting with a grid of PT. PLN as shown in Fig 1.
1
y ( k) = y ( k) + μ( k)
(5)
e(k) is the error between the command input ym(k) and MHPP
output yp(k) and ∆e(k) is the change in position error. The term
F[e(k), ∆e(k)] is a nonlinear mapping of e(k) and ∆e(k) base
on fuzzy logic. The term μ(k) =[e(k),∆e(k)] represents a
compensation or correction term, so that the compensated
command signal y’m(k) is simply the sum of the external
command signal ym(k) and μ(k).
Figure 1 : Micro Hydro Power Plant
The block control of system micro hydro[7] is set firstly the
volume of water that passes through the penstock with a valve .
The water from the penstock is to turn a turbine that coupled
with the generator. The output of the generator will be paired
frequency sensors and compared with a reference frequency of
PT . PLN ( Persero ) . The difference value of frequency will
be used by the controller to set the valve again, and so on . As
shown in Figure 2
Figure 3 : Alternatif Micro Hidro Controller
The equations governing the I controller are as follows
e ( k) = y ( k) − y ( k)
u( k) = u( k − 1) + Kie.( k)
(6)
(7)
yin is input reference yp is output frequency and e is error.
Controller changes a value of error until zero or a very small
value.
Figure 2 : Design System Control Micro Hydro[5]
C. Micro Hydro Controller
The control system of MHPP been developed in many
studies, such as PI control and PID. Everything is based on
conventional, because to settings of gain Ki, Kp and Kd by trial
and error. In this study the authors emphasize the Fuzzy
integrator controller. Alternative controller of MHPP can be
choices as shown at figure 3. Where the fuzzy precompensation function of regulating of errors that appears
before input into the control Integrator.
The equations (1) error as shown in. yp = yin – e where
e= y −y
(1)
e( k) = y ( k) − y ( k)
(2)
∆e( k) = e( k) − e( k − 1)
(3)
μ( k) = F( e( k) , ∆e( k)
(4)
D.Fuzzy Pre-Compensated I C ontroller
Pre-compesated[8] of hybrid fuzzy I controller, was
developed to combine the advantages of I controller and
fuzzy pre-compesated fuzzy controller. The quantity e’(k) is
the pre-compenseted position error between the precompenseted position error input ym’(k) and MHPP output
yp(k), and ∆e(k) is the pre-compensanted position error. As
shown in Figure 4 bellow .
Figure 4 : Block Diagram of Fuzzy Pre-compensated I
controller.
D.Data Simulation of MHPP Plants
Data simulation in this paper uses combination data
research, total rate capacity change from 50 KW to 5 KW, the
normal operating load of 25 KW was changed to 1 KW. This
2
is done to adjust with the existing MHPP plant, detail as
shown in Table 1.
Table 1. Data plant MHPP simulation
No
1.
2.
3.
4.
Data
Total rated capacity
Normal Operating Load
Inertia Constant H
Regulation R
Value
5 Kw
1 Kw
7.75 seconds (2
Connected to Low Voltage Distribution PT. PLN (Persero)
Lie Jasa1 , IGA Raka Agung2, I Putu Ardana3, Ardyono4 ,Mauridhy Hery Purnomo5
1,2,3
Electrical Engineering Department,Udayana University, Bali, Indonesia
4,5
Electrical Engineering Department Sepuluh Nopember Institute of Technology Surabaya, Indonesia
1
liejasa@unud.ac.id, 2puturaka@ee.unud.ac.id, 3ardana@ee.unud.ac.id, 4priyadi@ee.its.ac.id, 5hery@eits.ac.id
Abstract— The capacity of electrical energy supply PT. PLN
(persero) insufficient to public demand in Indonesia. Micro
Hydro Power Plant ( MHPP ) is a small-scale power plants which
relatively easy to developed in remote areas. The generated
energy by MHPP must be transmitted to the power distribution
network. In this study researchers wanted to answer the
problems how to make a model auto control which connects the
MHPP with power network distribution PT.PLN(Persero).The
results of this studies is a MHPP can be auto controlled by I, PI,
PID and Fuzzy-I controller. Smart control of Fuzzy-I controller
make the system to stable with a small overshoot values. It is
better than I, PI or PID controller.
Keyword : Micro hydro, Energy, Fuzzy
I.
INTRODUCTION
Impact of excessive energy use for this is the cause of air
pollution, global warming and climate change. Water energy
is an environmentally friendly energy source, green, unlimited
and renewable nature. All countries in the world today
continues to conduct research on water energy, wind and solar,
which is used as one of the future energy development policy
options. Proven installation of Renewable Energy is currently
in parts of the world increased to 30%. [1],[2]
The energy plays an important role for population in the
Indonesia. The energy demand is significantly increases every
year but the energy resource is limited and decreases
especially conventional energy. Hydropower[3] is one of clean
energy resources in the world. It is also the most reliable and
effectively cost renewable energy resource among the others.
Small hydropower schemes are getting increasingly popular
because of its simplicity design, easy in operation, and lower
environment.
The energy produced by the micro-hydro power plant
(MHPP) should be used by everyone. But the frequency
output of MHPP should to match with the frequency of the
network PT. PLN (Persero). This research proposes to find
model control system about it.
This study focused on discussing the frequency control of
the generator mounted on the MHPP to be set for frequency
changes (Δf) by using a low voltage reference of PT.
PLN(Persero). This control is using fuzzy logic consisting of
7- rule member’s ship function to control error (e) and change
of error (de).
Block Control of micro hydro set including the
components of governor, valves, turbine and generator is
made in the transfer function. Fuzzy logic uses to reduce the
error from occurring plant using Matlab. Fuzzy logic
controller has 2 input e and de and one output u.
II.
LETERATURE REVIEW
A. Hydraulics power theory
Theorem of water flow is used to determine the amount
of energy that can be generated from the flowing water. The
total extractable hydraulic power from the flowing water is
given by the expression of Pin = ρ x g x Q x H, where Pin is the
hydraulic power input to the wheels (W), ρ is the density of
water (kg/m3), g is the acceleration due to gravity (9,81m/s2),
Q is the volumetric water flow rate (m3/s) and H is the
difference in total energy line upstream and downstream of the
wheel (m). The angular velocity ω (rad/s) of the wheels is
calculated from the number of revolutions N at the given load
in revolutions per minute (RPM) of the wheel as : ω = 2 x π x
N/60. The shaft torque τ (Nm) is the product of the force F of
water striking the blades of the water wheel (N) and the
moment arm length (m) which, in this case, is the radius of the
pulley r. Force is equal to the differences in the mass obtained
from the two load cells time the acceleration due to gravity. τ
= m x g x r. Subsequently the mechanical power output Pout
available at the wheel shaft is determined from the measured
torque τ and the corresponding angular speed of the wheel ω
as : Pout = ω x τ = 2 x π x N x τ/60. By calculating the power of
output and input, the mechanical efficiency η of the wheel is
therefore: η = Pout / Pin x 100%
Automatic control system of micro-hydro is built in a
closed loop. First some water are flow in the valve, it continue
to the spill way and rotate the turbine. The control system of
MHPP as shown at Figure 1
B. Governor Controller
Control for hydro power plant, hydraulic mechanical
governor and electro-hydraulic, PID Controller [4] is used
commonly. MHPP in Gambuk, Bali[4],[5],[6] don’t have a
controller for control the system. Because It does not use a
controller to control the system. Frequency output never stable
if load changes. This condition is very difficult when
connecting with a grid of PT. PLN as shown in Fig 1.
1
y ( k) = y ( k) + μ( k)
(5)
e(k) is the error between the command input ym(k) and MHPP
output yp(k) and ∆e(k) is the change in position error. The term
F[e(k), ∆e(k)] is a nonlinear mapping of e(k) and ∆e(k) base
on fuzzy logic. The term μ(k) =[e(k),∆e(k)] represents a
compensation or correction term, so that the compensated
command signal y’m(k) is simply the sum of the external
command signal ym(k) and μ(k).
Figure 1 : Micro Hydro Power Plant
The block control of system micro hydro[7] is set firstly the
volume of water that passes through the penstock with a valve .
The water from the penstock is to turn a turbine that coupled
with the generator. The output of the generator will be paired
frequency sensors and compared with a reference frequency of
PT . PLN ( Persero ) . The difference value of frequency will
be used by the controller to set the valve again, and so on . As
shown in Figure 2
Figure 3 : Alternatif Micro Hidro Controller
The equations governing the I controller are as follows
e ( k) = y ( k) − y ( k)
u( k) = u( k − 1) + Kie.( k)
(6)
(7)
yin is input reference yp is output frequency and e is error.
Controller changes a value of error until zero or a very small
value.
Figure 2 : Design System Control Micro Hydro[5]
C. Micro Hydro Controller
The control system of MHPP been developed in many
studies, such as PI control and PID. Everything is based on
conventional, because to settings of gain Ki, Kp and Kd by trial
and error. In this study the authors emphasize the Fuzzy
integrator controller. Alternative controller of MHPP can be
choices as shown at figure 3. Where the fuzzy precompensation function of regulating of errors that appears
before input into the control Integrator.
The equations (1) error as shown in. yp = yin – e where
e= y −y
(1)
e( k) = y ( k) − y ( k)
(2)
∆e( k) = e( k) − e( k − 1)
(3)
μ( k) = F( e( k) , ∆e( k)
(4)
D.Fuzzy Pre-Compensated I C ontroller
Pre-compesated[8] of hybrid fuzzy I controller, was
developed to combine the advantages of I controller and
fuzzy pre-compesated fuzzy controller. The quantity e’(k) is
the pre-compenseted position error between the precompenseted position error input ym’(k) and MHPP output
yp(k), and ∆e(k) is the pre-compensanted position error. As
shown in Figure 4 bellow .
Figure 4 : Block Diagram of Fuzzy Pre-compensated I
controller.
D.Data Simulation of MHPP Plants
Data simulation in this paper uses combination data
research, total rate capacity change from 50 KW to 5 KW, the
normal operating load of 25 KW was changed to 1 KW. This
2
is done to adjust with the existing MHPP plant, detail as
shown in Table 1.
Table 1. Data plant MHPP simulation
No
1.
2.
3.
4.
Data
Total rated capacity
Normal Operating Load
Inertia Constant H
Regulation R
Value
5 Kw
1 Kw
7.75 seconds (2