SlideShare a Scribd company logo
1 of 28
Chapter 3

OPERATION CONTROL STRATEGY AND
SIMULATION OF PV SYSTEM
INTERCONNECTED WITH EU

1
Chapter 3

The performance of PV power system interconnected with EU can be
improved through an application of advanced control method. This
chapter introduces an application of an artificial neural network on the
operation control of the PV/EU to improve system efficiency and
reliability. There are two modes of PV system operation. As is said
before.
This chapter focus on the operation control of a hybrid system consists
of PV system accompanied with or without battery storage
interconnected with EU taking into account the variation of solar
radiation and load demand during the day. Different feed forward neural
network architectures are trained and tested with data containing a
variety of operation patterns. A simulation is carried out over one year
using the hourly data of the load demand, insolation and temperature at
Zafarâna site, Egypt as a case study.
2
Chapter 3

It introduces also a complete computer simulation program of PV
system interconnected with EU. The proposed computer simulation uses
hysteresis current control and instantaneous p-q (real- imaginary) power
theory. A computer simulation program has been designed to simulate
phase voltage of the inverter leg, phase-to-phase voltage of the inverter
leg, current in each IGBT's, DC input current to the inverter, AC output
current of the inverter that injected to the load/grid, load current, grid
current, power output of the inverter and finally power factor of the
inverter.
The following Figure represents the proposed configuration of PV
system which can feed a part of the load demand of 500kW.

3
Chapter 3
In v e rte r
D C /A C

B o o s t C o n v e rte r
D C /D C
L

F ilte r

b

V

500 kW
P V s u b s y s te m

V
C
IG B T

b

V

L
in v a

0 .4 /2 2 k V
500 kV A
f

in v b

in v c

b

D C
L in k

C

f

S te p -U p
T ra n sfo rm e r

1 3 2 /2 2 k V
500 kV A

~
EU

S1

S3

S2
S te p -D o w n
T ran sfo rm er

2 2 /0 .4 k V
500 kV A

S te p -D o w n
T ra n sfo rm e r

Fig. 3-1 PV/Load/EU System Block Diagram.

L oad
380 V ,
50 H z

4
Chapter 3

3-2 METHODOLOGY OF CONTROL STRATEGY

R
ad
i

at
io
n

3-2-1 Control strategy Issue of PV System Connected to EU without
BS.
D C /D C
V

D C /A C

F ilt e r

dcpv

S 3

S 2

Output

Input

E U

t

S 1

L oad

Fig. 3-2 Single-Line Diagram for the Control Strategy of the PV/EU
System
5
Chapter 3

.Power flows in Fig. 3-2 must satisfy the following equations

Ppv (t) ± Pg (t) = P (t)
L
Ppv (t) = ON pv * Ppv, out (t)
Where;
Ppv(t)
: The power from PV system, kW.
Pg(t)
: The power to or from EU, kW.
PL(t)
: The Load demand, kW.
t
: The hourly time over one year.
ONpv
: Optimum number of PV system.
Ppv,out(t)
: The output power from one PV module (see chapter 2).
Pg(t) is positive when the PV power is less than the load demand and
negative when PV power greater than the load demand.
6
Chapter 3

3-2-2

Control Strategy Issue of PV/BS
System Connected to EU

The design and installation of this system are more
complicated and expensive, but it is more reliable
than the PV/EU without BS. In this type of intertie
system, the load demand has both PV system, EU
and BS as shown in Fig. 3-3.

7
Ra
di
a ti

on

Chapter 3

D C /A C

C o n tro lle r

D C /D C

S4

F ilte r

0

1
B a tte ry

S 3
S2

Output

E U

Input

S 1

L oad

Fig. 3-3 Single-line Diagram for the control strategy of the PV/EU/BS
System
8
Chapter 3

3-3-2 Modeling of a DC/AC Inverter

There are two power inverters topology for utility
interface:T h re e -P h a se
E le c tric U tility

1- Line Commutated Inverter, LCI.
P

2. Voltage Source Inverter, VSI

+

P

dc

G
V

dc

G

1

C

V
V

G

3

V

G

in v

L

5

in v a

f

in v b

in v c

4

G

6

G

2

C

D C
L in k

f

C o n s ta n t F re q u e n c y
P W M In v e rte r

Fig. 3-5 Circuit Diagram of the Three-Phase Voltage Source Inverter
9
Chapter 3

3-4 APPLICATION AND RESULTS
3-4-1 Operation control strategy of PV System
Connected to EU.
Figure 3-11 shows the structure of the proposed three layers
NN. X1, X2 and t are the three-input training matrix which
represent electrical power generated from PV, load demand,
and time respectively.

10
Chapter 3

Iutputs

W

(1)

W

X1

(2)

Outputs
Signal to S1 ( 1 or 0)
Signal to S2 (1 or 0)

X2

Signal to S3 (1 or 0)

Time

bais

Fig. 3-11 Structure of the Proposed Three Layers NN
used for Control Strategy of PV/EU.
11
Chapter 3

200

Pg
PLoad
Ppv

Power, MW

150
100
50
0
-50
-100
1 2

3 4 5 6

7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Time, Hour

Fig. 3-13 Optimal Operation of the PV/EU to Feed the Load Demand during January (winter)
12
Chapter 3

200

Pg

Power, MW

150

PLoad
Ppv

100

50

0

-50

-100
1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Time, Hour

Fig. 3-14 Optimal Operation of the PV/ EU to Feed the Load Demand during July
(summer).
13
Chapter 3

Figures 3-16 displays the output of the proposed
NN of 3+6+3 for month of January using test data.

Fig. 3-17 Outputs of Neural Network for Month of July.
14
Chapter 3

3-4-2 Operation control strategy of PV/BS
System Connected to EU
In This Item we insert BS to feed critical load . The
Critical load equal to 18% of a maximum load demand.
A new subroutine computer program has been proposed
and written using Matlab software to simulate the PV/BS
system. The flowchart of this program is shown in Fig. 318. The output of this program has been used to be the
input of NN. The outputs of NN are four trip signals that
send to switches S1, S2, S3 and S4 as shown in Fig. 3-3.
15
Chapter 3

F o r i= 1 :1 :1 2 m o n th

F o r tim e = 1 :1 :2 4 h r

B a tte rie s a r e c h a r g e d
i.e . S 4 = 1 a n d th e lo a d
fe d fro m g rid

yes

If
0 .1 < R a d < 0 .2 o r
In v e rte r fa ilu r e

N o
F e e d th e lo a d S 1 = O N

yes

P

pv

yes

N o

(t) > P L (t)

P p v ( t)= P L ( t)

N o

If S O C (t) >
0 .8 * s iz e o f b a tte r y

N o
If S O C (t) >
0 .2 * s iz e o f b a tte r y

N o

S u rp lu s p o w e r s e n d to
B a tte ry S 4 = 1 , S 1 = O N
yes
yes

S u r p lu s p o w e r s e n d to
E U S3= O N , S2=O FF

L o a d fe e d fro m E U ;
S1=O FF, S2=O N

L o a d fe e d fr o m b a tte ry
S1= O N , S4= 0

E nd

Fig. 3-18 Flowchart of the Proposed
Computer Program for PV/EU
Accompanied with BS.

F ro m E n d o f P ro g r a m F ig . 2 -5

16
Chapter 3

Figure 3-19 shows the structure of the proposed
three layers NN. X1, X2, X3, X4 and t are the five-input
training matrix and represent state of charge, electrical power
generated from PV, electrical power for EU, load demand and
time respectively.
W
W
(1)

(2)

Iutputs

Outputs

X1

Signal to S1( 1 or 0)

X2

Signal to S2(1 or 0)

X3

Signal to S3 (1 or 0)

X4

Signal to S4 (1 or 0)

Time

Fig. 3-19 Structure of the Proposed Three Layers NN used
for Control Strategy of PV/EU Accompanied with BS.
bais

17
Chapter 3

Fig. 3-11 Operation control Strategy of PV/EU accompanied
with BS using NN
18
Chapter 3

3-5 SIMULATION RESULTS OF PV/EU
The circuit of Fig. 3-1 is simulated using Matlab/simulink
version 6 as shown in the following Figure.
The output power from PV solar cells array as shown in Fig.
3-27 have been applied to the inverter to feed the load with the
EU. The total power load level is 300 kW with load current
455.8 Ampere for duration 0.3 Sec. After 0.3 Sec., the load
has changed from 300 kW to 100 kW with load current 151.93
Ampere for duration from 0.3 Sec. to 0.5 Sec. as shown in Fig.
3-27.

19
f the PV System Connected with EU.

Chapter 3

20
Chapter 3

Fig. 3-27 Simulated of Generated Power from PV, Load Demand
and EU Power from/to EU.
21
Chapter 3

The following Figures show simulation results of the
proposed control strategy.

Figure 3-28 Simulated phase voltage of the inverter leg.
22
Chapter 3

Figure 3-30 Simulated switch current in IGBT's
23
Chapter 3

Figure 8 Simulated of inverter current injected to the load/EU
24
Chapter 3

Figure 9 simulated of load current
25
Chapter 3

Figure 10 simulated grid current
from /to EU.
26
Chapter 3

Figure 11 Simulated power factor of the grid.
27
Chapter 3

Figure 12 simulated of the inverter power factor.
28

More Related Content

What's hot

Power fuzzy adaptive control for wind turbine
Power fuzzy adaptive control for wind turbinePower fuzzy adaptive control for wind turbine
Power fuzzy adaptive control for wind turbineIJECEIAES
 
Design of Three Phase Matrix Converter AC-AC Utility Power Supply using SPWM ...
Design of Three Phase Matrix Converter AC-AC Utility Power Supply using SPWM ...Design of Three Phase Matrix Converter AC-AC Utility Power Supply using SPWM ...
Design of Three Phase Matrix Converter AC-AC Utility Power Supply using SPWM ...IJERA Editor
 
MPPT control design for variable speed wind turbine
MPPT control design for variable speed wind turbine MPPT control design for variable speed wind turbine
MPPT control design for variable speed wind turbine IJECEIAES
 
Optimization for Electric Power Load Forecast
Optimization for Electric Power Load Forecast Optimization for Electric Power Load Forecast
Optimization for Electric Power Load Forecast IJECEIAES
 
Design of a wind power generation system using a
Design of a wind power generation system using aDesign of a wind power generation system using a
Design of a wind power generation system using aeSAT Publishing House
 
Three-level modified sine wave inverter equipped with online temperature moni...
Three-level modified sine wave inverter equipped with online temperature moni...Three-level modified sine wave inverter equipped with online temperature moni...
Three-level modified sine wave inverter equipped with online temperature moni...TELKOMNIKA JOURNAL
 
ANFIS Control of Energy Control Center for Distributed Wind and Solar Generat...
ANFIS Control of Energy Control Center for Distributed Wind and Solar Generat...ANFIS Control of Energy Control Center for Distributed Wind and Solar Generat...
ANFIS Control of Energy Control Center for Distributed Wind and Solar Generat...IRJET Journal
 
B021201015023
B021201015023B021201015023
B021201015023theijes
 
Novel Adaptive Controller for PMSG Driven Wind Turbine To Improve Power Syste...
Novel Adaptive Controller for PMSG Driven Wind Turbine To Improve Power Syste...Novel Adaptive Controller for PMSG Driven Wind Turbine To Improve Power Syste...
Novel Adaptive Controller for PMSG Driven Wind Turbine To Improve Power Syste...IJMERJOURNAL
 
Indirect Control of a Doubly-Fed Induction Machine for Wind Energy Conversion
Indirect Control of a Doubly-Fed Induction Machine for Wind Energy ConversionIndirect Control of a Doubly-Fed Induction Machine for Wind Energy Conversion
Indirect Control of a Doubly-Fed Induction Machine for Wind Energy ConversionIAES-IJPEDS
 
Electronic photonic arithmetic logic unit for high-speed computing
Electronic photonic arithmetic logic unit for high-speed computingElectronic photonic arithmetic logic unit for high-speed computing
Electronic photonic arithmetic logic unit for high-speed computingShreyanDatta
 
Power Optimization and Control in Wind Energy Conversion Systems using Fracti...
Power Optimization and Control in Wind Energy Conversion Systems using Fracti...Power Optimization and Control in Wind Energy Conversion Systems using Fracti...
Power Optimization and Control in Wind Energy Conversion Systems using Fracti...IRJET Journal
 

What's hot (20)

Power fuzzy adaptive control for wind turbine
Power fuzzy adaptive control for wind turbinePower fuzzy adaptive control for wind turbine
Power fuzzy adaptive control for wind turbine
 
Design of Three Phase Matrix Converter AC-AC Utility Power Supply using SPWM ...
Design of Three Phase Matrix Converter AC-AC Utility Power Supply using SPWM ...Design of Three Phase Matrix Converter AC-AC Utility Power Supply using SPWM ...
Design of Three Phase Matrix Converter AC-AC Utility Power Supply using SPWM ...
 
MPPT control design for variable speed wind turbine
MPPT control design for variable speed wind turbine MPPT control design for variable speed wind turbine
MPPT control design for variable speed wind turbine
 
Conceptual study on Grid-to-Vehicle (G2V) wireless power transfer using singl...
Conceptual study on Grid-to-Vehicle (G2V) wireless power transfer using singl...Conceptual study on Grid-to-Vehicle (G2V) wireless power transfer using singl...
Conceptual study on Grid-to-Vehicle (G2V) wireless power transfer using singl...
 
Optimization for Electric Power Load Forecast
Optimization for Electric Power Load Forecast Optimization for Electric Power Load Forecast
Optimization for Electric Power Load Forecast
 
Design of a wind power generation system using a
Design of a wind power generation system using aDesign of a wind power generation system using a
Design of a wind power generation system using a
 
Three-level modified sine wave inverter equipped with online temperature moni...
Three-level modified sine wave inverter equipped with online temperature moni...Three-level modified sine wave inverter equipped with online temperature moni...
Three-level modified sine wave inverter equipped with online temperature moni...
 
H010425863
H010425863H010425863
H010425863
 
ANFIS Control of Energy Control Center for Distributed Wind and Solar Generat...
ANFIS Control of Energy Control Center for Distributed Wind and Solar Generat...ANFIS Control of Energy Control Center for Distributed Wind and Solar Generat...
ANFIS Control of Energy Control Center for Distributed Wind and Solar Generat...
 
B021201015023
B021201015023B021201015023
B021201015023
 
Csl7 30 j15
Csl7 30 j15Csl7 30 j15
Csl7 30 j15
 
Novel Adaptive Controller for PMSG Driven Wind Turbine To Improve Power Syste...
Novel Adaptive Controller for PMSG Driven Wind Turbine To Improve Power Syste...Novel Adaptive Controller for PMSG Driven Wind Turbine To Improve Power Syste...
Novel Adaptive Controller for PMSG Driven Wind Turbine To Improve Power Syste...
 
Indirect Control of a Doubly-Fed Induction Machine for Wind Energy Conversion
Indirect Control of a Doubly-Fed Induction Machine for Wind Energy ConversionIndirect Control of a Doubly-Fed Induction Machine for Wind Energy Conversion
Indirect Control of a Doubly-Fed Induction Machine for Wind Energy Conversion
 
[7]
[7][7]
[7]
 
Digital Control for a PV Powered BLDC Motor
Digital Control for a PV Powered BLDC MotorDigital Control for a PV Powered BLDC Motor
Digital Control for a PV Powered BLDC Motor
 
Electronic photonic arithmetic logic unit for high-speed computing
Electronic photonic arithmetic logic unit for high-speed computingElectronic photonic arithmetic logic unit for high-speed computing
Electronic photonic arithmetic logic unit for high-speed computing
 
F010424451
F010424451F010424451
F010424451
 
Power Optimization and Control in Wind Energy Conversion Systems using Fracti...
Power Optimization and Control in Wind Energy Conversion Systems using Fracti...Power Optimization and Control in Wind Energy Conversion Systems using Fracti...
Power Optimization and Control in Wind Energy Conversion Systems using Fracti...
 
Performance analysis and enhancement of direct power control of DFIG based wi...
Performance analysis and enhancement of direct power control of DFIG based wi...Performance analysis and enhancement of direct power control of DFIG based wi...
Performance analysis and enhancement of direct power control of DFIG based wi...
 
Modeling and control of two five-phase induction machines connected in series...
Modeling and control of two five-phase induction machines connected in series...Modeling and control of two five-phase induction machines connected in series...
Modeling and control of two five-phase induction machines connected in series...
 

Similar to Chapter3

Fuzzy logic based MPPT technique for a single phase Grid connected PV system ...
Fuzzy logic based MPPT technique for a single phase Grid connected PV system ...Fuzzy logic based MPPT technique for a single phase Grid connected PV system ...
Fuzzy logic based MPPT technique for a single phase Grid connected PV system ...THOKALA SOWMYA
 
Modeling and simulation of three phases cascaded H-bridge grid-tied PV inverter
Modeling and simulation of three phases cascaded H-bridge grid-tied PV inverterModeling and simulation of three phases cascaded H-bridge grid-tied PV inverter
Modeling and simulation of three phases cascaded H-bridge grid-tied PV inverterjournalBEEI
 
Improving efficiency of Photovoltaic System with Neural Network Based MPPT Co...
Improving efficiency of Photovoltaic System with Neural Network Based MPPT Co...Improving efficiency of Photovoltaic System with Neural Network Based MPPT Co...
Improving efficiency of Photovoltaic System with Neural Network Based MPPT Co...IJMER
 
Modeling and simulation of three phases cascaded H-bridge grid-tied PV inverter
Modeling and simulation of three phases cascaded H-bridge grid-tied PV inverterModeling and simulation of three phases cascaded H-bridge grid-tied PV inverter
Modeling and simulation of three phases cascaded H-bridge grid-tied PV inverterjournalBEEI
 
Dual – MPPT Control of a Photovoltaic System
Dual – MPPT Control of a Photovoltaic SystemDual – MPPT Control of a Photovoltaic System
Dual – MPPT Control of a Photovoltaic SystemIJTET Journal
 
An Overview of MPPT for Photovoltaic Panels Using Various Artificial Intellig...
An Overview of MPPT for Photovoltaic Panels Using Various Artificial Intellig...An Overview of MPPT for Photovoltaic Panels Using Various Artificial Intellig...
An Overview of MPPT for Photovoltaic Panels Using Various Artificial Intellig...IRJET Journal
 
Design and Implementation of Maximum Power Point Tracking Using Fuzzy Logic C...
Design and Implementation of Maximum Power Point Tracking Using Fuzzy Logic C...Design and Implementation of Maximum Power Point Tracking Using Fuzzy Logic C...
Design and Implementation of Maximum Power Point Tracking Using Fuzzy Logic C...paperpublications3
 
Investigation of Interleaved Boost Converter with Voltage multiplier for PV w...
Investigation of Interleaved Boost Converter with Voltage multiplier for PV w...Investigation of Interleaved Boost Converter with Voltage multiplier for PV w...
Investigation of Interleaved Boost Converter with Voltage multiplier for PV w...ecij
 
Performance of Maximum Power Point Tracking Algorithm based Photovoltaic Arra...
Performance of Maximum Power Point Tracking Algorithm based Photovoltaic Arra...Performance of Maximum Power Point Tracking Algorithm based Photovoltaic Arra...
Performance of Maximum Power Point Tracking Algorithm based Photovoltaic Arra...IRJET Journal
 
Design of PV backup system for data center
Design of PV backup system for data centerDesign of PV backup system for data center
Design of PV backup system for data centerMohamed Abbas
 
IRJET- Analysis of LVRT Capability of Grid Connected Solar Photovoltaic System
IRJET- Analysis of LVRT Capability of Grid Connected Solar Photovoltaic SystemIRJET- Analysis of LVRT Capability of Grid Connected Solar Photovoltaic System
IRJET- Analysis of LVRT Capability of Grid Connected Solar Photovoltaic SystemIRJET Journal
 
Solar energy based impedance-source inverter for grid system
Solar energy based impedance-source inverter for grid systemSolar energy based impedance-source inverter for grid system
Solar energy based impedance-source inverter for grid systemIJECEIAES
 
Voltage support to grid under unbalance rodriguje
Voltage support to grid under unbalance rodrigujeVoltage support to grid under unbalance rodriguje
Voltage support to grid under unbalance rodrigujeDeepak Gehlot
 
Integral Backstepping Control for Maximum Power Point Tracking and Unity Powe...
Integral Backstepping Control for Maximum Power Point Tracking and Unity Powe...Integral Backstepping Control for Maximum Power Point Tracking and Unity Powe...
Integral Backstepping Control for Maximum Power Point Tracking and Unity Powe...IJECEIAES
 
Design of Hybrid Solar Wind Energy System in a Microgrid with MPPT Techniques
Design of Hybrid Solar Wind Energy System in a Microgrid with MPPT Techniques Design of Hybrid Solar Wind Energy System in a Microgrid with MPPT Techniques
Design of Hybrid Solar Wind Energy System in a Microgrid with MPPT Techniques IJECEIAES
 

Similar to Chapter3 (20)

Output feedback nonlinear control of three-phase grid-connected PV generator
Output feedback nonlinear control of three-phase grid-connected PV generatorOutput feedback nonlinear control of three-phase grid-connected PV generator
Output feedback nonlinear control of three-phase grid-connected PV generator
 
A random PWM control strategy for a three level inverter used in a grid conne...
A random PWM control strategy for a three level inverter used in a grid conne...A random PWM control strategy for a three level inverter used in a grid conne...
A random PWM control strategy for a three level inverter used in a grid conne...
 
Fuzzy logic based MPPT technique for a single phase Grid connected PV system ...
Fuzzy logic based MPPT technique for a single phase Grid connected PV system ...Fuzzy logic based MPPT technique for a single phase Grid connected PV system ...
Fuzzy logic based MPPT technique for a single phase Grid connected PV system ...
 
Modeling and simulation of three phases cascaded H-bridge grid-tied PV inverter
Modeling and simulation of three phases cascaded H-bridge grid-tied PV inverterModeling and simulation of three phases cascaded H-bridge grid-tied PV inverter
Modeling and simulation of three phases cascaded H-bridge grid-tied PV inverter
 
Improving efficiency of Photovoltaic System with Neural Network Based MPPT Co...
Improving efficiency of Photovoltaic System with Neural Network Based MPPT Co...Improving efficiency of Photovoltaic System with Neural Network Based MPPT Co...
Improving efficiency of Photovoltaic System with Neural Network Based MPPT Co...
 
Maximum power control for photovoltaic system using intelligent strategies
Maximum power control for photovoltaic system using intelligent strategiesMaximum power control for photovoltaic system using intelligent strategies
Maximum power control for photovoltaic system using intelligent strategies
 
Modeling and simulation of three phases cascaded H-bridge grid-tied PV inverter
Modeling and simulation of three phases cascaded H-bridge grid-tied PV inverterModeling and simulation of three phases cascaded H-bridge grid-tied PV inverter
Modeling and simulation of three phases cascaded H-bridge grid-tied PV inverter
 
A novel optimization of the particle swarm based maximum power point tracking...
A novel optimization of the particle swarm based maximum power point tracking...A novel optimization of the particle swarm based maximum power point tracking...
A novel optimization of the particle swarm based maximum power point tracking...
 
Dual – MPPT Control of a Photovoltaic System
Dual – MPPT Control of a Photovoltaic SystemDual – MPPT Control of a Photovoltaic System
Dual – MPPT Control of a Photovoltaic System
 
An Overview of MPPT for Photovoltaic Panels Using Various Artificial Intellig...
An Overview of MPPT for Photovoltaic Panels Using Various Artificial Intellig...An Overview of MPPT for Photovoltaic Panels Using Various Artificial Intellig...
An Overview of MPPT for Photovoltaic Panels Using Various Artificial Intellig...
 
Design and Implementation of Maximum Power Point Tracking Using Fuzzy Logic C...
Design and Implementation of Maximum Power Point Tracking Using Fuzzy Logic C...Design and Implementation of Maximum Power Point Tracking Using Fuzzy Logic C...
Design and Implementation of Maximum Power Point Tracking Using Fuzzy Logic C...
 
Investigation of Interleaved Boost Converter with Voltage multiplier for PV w...
Investigation of Interleaved Boost Converter with Voltage multiplier for PV w...Investigation of Interleaved Boost Converter with Voltage multiplier for PV w...
Investigation of Interleaved Boost Converter with Voltage multiplier for PV w...
 
Performance of Maximum Power Point Tracking Algorithm based Photovoltaic Arra...
Performance of Maximum Power Point Tracking Algorithm based Photovoltaic Arra...Performance of Maximum Power Point Tracking Algorithm based Photovoltaic Arra...
Performance of Maximum Power Point Tracking Algorithm based Photovoltaic Arra...
 
Design of PV backup system for data center
Design of PV backup system for data centerDesign of PV backup system for data center
Design of PV backup system for data center
 
IRJET- Analysis of LVRT Capability of Grid Connected Solar Photovoltaic System
IRJET- Analysis of LVRT Capability of Grid Connected Solar Photovoltaic SystemIRJET- Analysis of LVRT Capability of Grid Connected Solar Photovoltaic System
IRJET- Analysis of LVRT Capability of Grid Connected Solar Photovoltaic System
 
Solar energy based impedance-source inverter for grid system
Solar energy based impedance-source inverter for grid systemSolar energy based impedance-source inverter for grid system
Solar energy based impedance-source inverter for grid system
 
Voltage support to grid under unbalance rodriguje
Voltage support to grid under unbalance rodrigujeVoltage support to grid under unbalance rodriguje
Voltage support to grid under unbalance rodriguje
 
Integral Backstepping Control for Maximum Power Point Tracking and Unity Powe...
Integral Backstepping Control for Maximum Power Point Tracking and Unity Powe...Integral Backstepping Control for Maximum Power Point Tracking and Unity Powe...
Integral Backstepping Control for Maximum Power Point Tracking and Unity Powe...
 
Design of Hybrid Solar Wind Energy System in a Microgrid with MPPT Techniques
Design of Hybrid Solar Wind Energy System in a Microgrid with MPPT Techniques Design of Hybrid Solar Wind Energy System in a Microgrid with MPPT Techniques
Design of Hybrid Solar Wind Energy System in a Microgrid with MPPT Techniques
 
Modeling and Fuzzy Logic Control of PV Based Cascaded Boost Converter Three P...
Modeling and Fuzzy Logic Control of PV Based Cascaded Boost Converter Three P...Modeling and Fuzzy Logic Control of PV Based Cascaded Boost Converter Three P...
Modeling and Fuzzy Logic Control of PV Based Cascaded Boost Converter Three P...
 

Recently uploaded

Artificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraArtificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraDeakin University
 
Key Features Of Token Development (1).pptx
Key  Features Of Token  Development (1).pptxKey  Features Of Token  Development (1).pptx
Key Features Of Token Development (1).pptxLBM Solutions
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure servicePooja Nehwal
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Scott Keck-Warren
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Allon Mureinik
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsMemoori
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 3652toLead Limited
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticscarlostorres15106
 
Maximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptxMaximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptxOnBoard
 
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersEnhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersThousandEyes
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 

Recently uploaded (20)

Artificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraArtificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning era
 
Key Features Of Token Development (1).pptx
Key  Features Of Token  Development (1).pptxKey  Features Of Token  Development (1).pptx
Key Features Of Token Development (1).pptx
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)
 
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptxE-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
 
Vulnerability_Management_GRC_by Sohang Sengupta.pptx
Vulnerability_Management_GRC_by Sohang Sengupta.pptxVulnerability_Management_GRC_by Sohang Sengupta.pptx
Vulnerability_Management_GRC_by Sohang Sengupta.pptx
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping Elbows
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial Buildings
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
 
Maximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptxMaximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptx
 
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersEnhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 

Chapter3

  • 1. Chapter 3 OPERATION CONTROL STRATEGY AND SIMULATION OF PV SYSTEM INTERCONNECTED WITH EU 1
  • 2. Chapter 3 The performance of PV power system interconnected with EU can be improved through an application of advanced control method. This chapter introduces an application of an artificial neural network on the operation control of the PV/EU to improve system efficiency and reliability. There are two modes of PV system operation. As is said before. This chapter focus on the operation control of a hybrid system consists of PV system accompanied with or without battery storage interconnected with EU taking into account the variation of solar radiation and load demand during the day. Different feed forward neural network architectures are trained and tested with data containing a variety of operation patterns. A simulation is carried out over one year using the hourly data of the load demand, insolation and temperature at Zafarâna site, Egypt as a case study. 2
  • 3. Chapter 3 It introduces also a complete computer simulation program of PV system interconnected with EU. The proposed computer simulation uses hysteresis current control and instantaneous p-q (real- imaginary) power theory. A computer simulation program has been designed to simulate phase voltage of the inverter leg, phase-to-phase voltage of the inverter leg, current in each IGBT's, DC input current to the inverter, AC output current of the inverter that injected to the load/grid, load current, grid current, power output of the inverter and finally power factor of the inverter. The following Figure represents the proposed configuration of PV system which can feed a part of the load demand of 500kW. 3
  • 4. Chapter 3 In v e rte r D C /A C B o o s t C o n v e rte r D C /D C L F ilte r b V 500 kW P V s u b s y s te m V C IG B T b V L in v a 0 .4 /2 2 k V 500 kV A f in v b in v c b D C L in k C f S te p -U p T ra n sfo rm e r 1 3 2 /2 2 k V 500 kV A ~ EU S1 S3 S2 S te p -D o w n T ran sfo rm er 2 2 /0 .4 k V 500 kV A S te p -D o w n T ra n sfo rm e r Fig. 3-1 PV/Load/EU System Block Diagram. L oad 380 V , 50 H z 4
  • 5. Chapter 3 3-2 METHODOLOGY OF CONTROL STRATEGY R ad i at io n 3-2-1 Control strategy Issue of PV System Connected to EU without BS. D C /D C V D C /A C F ilt e r dcpv S 3 S 2 Output Input E U t S 1 L oad Fig. 3-2 Single-Line Diagram for the Control Strategy of the PV/EU System 5
  • 6. Chapter 3 .Power flows in Fig. 3-2 must satisfy the following equations Ppv (t) ± Pg (t) = P (t) L Ppv (t) = ON pv * Ppv, out (t) Where; Ppv(t) : The power from PV system, kW. Pg(t) : The power to or from EU, kW. PL(t) : The Load demand, kW. t : The hourly time over one year. ONpv : Optimum number of PV system. Ppv,out(t) : The output power from one PV module (see chapter 2). Pg(t) is positive when the PV power is less than the load demand and negative when PV power greater than the load demand. 6
  • 7. Chapter 3 3-2-2 Control Strategy Issue of PV/BS System Connected to EU The design and installation of this system are more complicated and expensive, but it is more reliable than the PV/EU without BS. In this type of intertie system, the load demand has both PV system, EU and BS as shown in Fig. 3-3. 7
  • 8. Ra di a ti on Chapter 3 D C /A C C o n tro lle r D C /D C S4 F ilte r 0 1 B a tte ry S 3 S2 Output E U Input S 1 L oad Fig. 3-3 Single-line Diagram for the control strategy of the PV/EU/BS System 8
  • 9. Chapter 3 3-3-2 Modeling of a DC/AC Inverter There are two power inverters topology for utility interface:T h re e -P h a se E le c tric U tility 1- Line Commutated Inverter, LCI. P 2. Voltage Source Inverter, VSI + P dc G V dc G 1 C V V G 3 V G in v L 5 in v a f in v b in v c 4 G 6 G 2 C D C L in k f C o n s ta n t F re q u e n c y P W M In v e rte r Fig. 3-5 Circuit Diagram of the Three-Phase Voltage Source Inverter 9
  • 10. Chapter 3 3-4 APPLICATION AND RESULTS 3-4-1 Operation control strategy of PV System Connected to EU. Figure 3-11 shows the structure of the proposed three layers NN. X1, X2 and t are the three-input training matrix which represent electrical power generated from PV, load demand, and time respectively. 10
  • 11. Chapter 3 Iutputs W (1) W X1 (2) Outputs Signal to S1 ( 1 or 0) Signal to S2 (1 or 0) X2 Signal to S3 (1 or 0) Time bais Fig. 3-11 Structure of the Proposed Three Layers NN used for Control Strategy of PV/EU. 11
  • 12. Chapter 3 200 Pg PLoad Ppv Power, MW 150 100 50 0 -50 -100 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Time, Hour Fig. 3-13 Optimal Operation of the PV/EU to Feed the Load Demand during January (winter) 12
  • 13. Chapter 3 200 Pg Power, MW 150 PLoad Ppv 100 50 0 -50 -100 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Time, Hour Fig. 3-14 Optimal Operation of the PV/ EU to Feed the Load Demand during July (summer). 13
  • 14. Chapter 3 Figures 3-16 displays the output of the proposed NN of 3+6+3 for month of January using test data. Fig. 3-17 Outputs of Neural Network for Month of July. 14
  • 15. Chapter 3 3-4-2 Operation control strategy of PV/BS System Connected to EU In This Item we insert BS to feed critical load . The Critical load equal to 18% of a maximum load demand. A new subroutine computer program has been proposed and written using Matlab software to simulate the PV/BS system. The flowchart of this program is shown in Fig. 318. The output of this program has been used to be the input of NN. The outputs of NN are four trip signals that send to switches S1, S2, S3 and S4 as shown in Fig. 3-3. 15
  • 16. Chapter 3 F o r i= 1 :1 :1 2 m o n th F o r tim e = 1 :1 :2 4 h r B a tte rie s a r e c h a r g e d i.e . S 4 = 1 a n d th e lo a d fe d fro m g rid yes If 0 .1 < R a d < 0 .2 o r In v e rte r fa ilu r e N o F e e d th e lo a d S 1 = O N yes P pv yes N o (t) > P L (t) P p v ( t)= P L ( t) N o If S O C (t) > 0 .8 * s iz e o f b a tte r y N o If S O C (t) > 0 .2 * s iz e o f b a tte r y N o S u rp lu s p o w e r s e n d to B a tte ry S 4 = 1 , S 1 = O N yes yes S u r p lu s p o w e r s e n d to E U S3= O N , S2=O FF L o a d fe e d fro m E U ; S1=O FF, S2=O N L o a d fe e d fr o m b a tte ry S1= O N , S4= 0 E nd Fig. 3-18 Flowchart of the Proposed Computer Program for PV/EU Accompanied with BS. F ro m E n d o f P ro g r a m F ig . 2 -5 16
  • 17. Chapter 3 Figure 3-19 shows the structure of the proposed three layers NN. X1, X2, X3, X4 and t are the five-input training matrix and represent state of charge, electrical power generated from PV, electrical power for EU, load demand and time respectively. W W (1) (2) Iutputs Outputs X1 Signal to S1( 1 or 0) X2 Signal to S2(1 or 0) X3 Signal to S3 (1 or 0) X4 Signal to S4 (1 or 0) Time Fig. 3-19 Structure of the Proposed Three Layers NN used for Control Strategy of PV/EU Accompanied with BS. bais 17
  • 18. Chapter 3 Fig. 3-11 Operation control Strategy of PV/EU accompanied with BS using NN 18
  • 19. Chapter 3 3-5 SIMULATION RESULTS OF PV/EU The circuit of Fig. 3-1 is simulated using Matlab/simulink version 6 as shown in the following Figure. The output power from PV solar cells array as shown in Fig. 3-27 have been applied to the inverter to feed the load with the EU. The total power load level is 300 kW with load current 455.8 Ampere for duration 0.3 Sec. After 0.3 Sec., the load has changed from 300 kW to 100 kW with load current 151.93 Ampere for duration from 0.3 Sec. to 0.5 Sec. as shown in Fig. 3-27. 19
  • 20. f the PV System Connected with EU. Chapter 3 20
  • 21. Chapter 3 Fig. 3-27 Simulated of Generated Power from PV, Load Demand and EU Power from/to EU. 21
  • 22. Chapter 3 The following Figures show simulation results of the proposed control strategy. Figure 3-28 Simulated phase voltage of the inverter leg. 22
  • 23. Chapter 3 Figure 3-30 Simulated switch current in IGBT's 23
  • 24. Chapter 3 Figure 8 Simulated of inverter current injected to the load/EU 24
  • 25. Chapter 3 Figure 9 simulated of load current 25
  • 26. Chapter 3 Figure 10 simulated grid current from /to EU. 26
  • 27. Chapter 3 Figure 11 Simulated power factor of the grid. 27
  • 28. Chapter 3 Figure 12 simulated of the inverter power factor. 28