SlideShare a Scribd company logo
1 of 9
Download to read offline
IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE)
e-ISSN: 2278-1676,p-ISSN: 2320-3331, Volume 10, Issue 4 Ver. I (July – Aug. 2015), PP 82-90
www.iosrjournals.org
DOI: 10.9790/1676-10418290 www.iosrjournals.org 82 | Page
Allocation of Reactive Power Compensation Devices to Improve
Voltage Profile Using Reactive Participation Index
Antamil, Ardiaty Arief and Indar Chaerah Gunadin
Department of Electrical Engineering, UniversitasHasanuddin, Indonesia
Abstract: This study proposed new method of improving voltage profile utilizing addition of inversed reduced
Jacobian matrix elements vertically with the aim of determining location of reactive power compensation
installation.This method is tested using actual network in Indonesia. In this analysis, enhancement of power
system stability includes of voltage improvement and increase in stability index. By using this proposed method
several buses appear as an ideal place for installation of capacitors. The results are also compared to different
configuration to validate and demonstrate the effectiveness of the method.
Keywords – voltage profile, voltage stability, voltage collapse, modal analysis, steady-state analysis, reactive
power compensations, reactive participation index.
I. INTRODUCTION
Power system stability has been considered as a main requisitefor a safe and trustworthy process in a
power system for over ninety years[1-3]. Voltage stability is a common problem that occurs anywhere in the
world.Nowadays, electrical systems are thoroughly stressed and running at the stability limit with smaller
capacity and margin [4] hence may cause congestion problems [5, 6]. This occurs due to the small and large
disturbances that affect the stability of operation.In addition, increasein active and reactive power also
contributes to the decrease in the voltage. Voltage dropdue to uncontrolled reactive power can lead the system to
collapse.
As the system are getting stressed,it is necessary for an evaluation of the weak point where potential
instability occurs, so that preventive action can be taken earlier and to avoid cascading failures. As it is well
known, that voltage problem has resilient relation with reactive power injections. To find out the weak points in
a system, there are several algorithms in the growing literature. One of the advanced method developed is Modal
Analysis by [7]. In this technique,relationship between voltage (V) and reactive power (Q) is used to exploit the
most contributed bus to system instability.The system is voltage stable, if the injection of reactive power
increases and at the same time voltage magnitude also increases. The system is voltage unstable if at the same
time reactive power increased and the voltage magnitude decreases[7, 8].
To overcome the voltage drop as described above, it is required compensation equipment to maintain
the voltage magnitude remains at the desired level. There are many type of reactive compensation devices, such
as: capacitor banks, static Var compensator (SVC) or static compensator (STATCOM). These reactive
compensation devices have imperative function in improving voltage stability. Capacitor banks is one of the
foremost and commonly used reactive compensators equipment. Capacitors have a very important role in the
power system network because apart from being usedas reactive power compensation device, it can help to
increase active power delivery and reduce transmission losses[9-15], therefore overall it can improve voltage
profile of the system. However, installation of capacitor banks should be at the right buses so it can perform
effectively.
Various methods have been developed for placement of capacitor. References [16, 17] create Loss
Sensitivity Factor to find capacitor placement location. Artificial bee colony algorithm is applied for capacitor
allocation in [18]. Paper [19] designs two-stage approach using fuzzy logic and bat algorithm to determine
location and size of capacitor. Authors in[20] propose opposition based differential evolution algorithm for
reconfiguration and capacitor placement. However, these works only focus on the network losses reduction. In
[21], fast decoupled method was employed to determine size for capacitor, but this work only assesses the
voltage improvement, not the network losses. Nonetheless, the appropriate location and size of capacitor can
reduce both network losses as well as enhance voltage stability.
It is essential to develop an effective method that able to confirm both voltage stability of the system
and location to improve the stability.This study enhances modal analysis technique for the effective placement
of capacitor banks. Modal analysis is an analytic solutions approach that can give information about the voltage
stability in a complex power system. In this work, the element of inversed reduced Jacobian matrix is added
vertically to compute Reactive Participation Index (RPI). RPI informs about participation of a specific bus in
improving voltage magnitude at critical buses based on its reactive power injection. The bus with the biggest
RPI has the biggest influence in enhancing voltage profile after injected reactive power hence it is chosen as the
Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive
DOI: 10.9790/1676-10418290 www.iosrjournals.org 83 | Page
location of capacitor banks placement. This method is simple but accurate and do not need complicated
computational processes.
This paper consist of five parts. Part 1 is introduction, Part 2 isthe breakdown of modal analysis
approach and development of participation factor, Part 3describes method proposed, Part 4 informs about the
South Sulawesi interconnected system in Indonesia as the case study, Part 5 presentsresearch data, results
analysis, and validation,Part 6 is the final conclusion and closing of this research.
II. BREAKDOWN OF MODAL ANALYSIS APPROACH TO COMPUTE REACTIVE PARTICIPATION
INDEX (RPI)
To evaluate the system stability, it often requires extensive and in-depth examination of the condition
of the system. Therefore linearized steady state analysis is used to see the problems that exist on the voltage and
reactive power.
∆P
∆Q
=
JPθ JPV
JQθ JQV
∆Q
∆V
(1)
Where :
P = Incremental change in bus real power
Q = Incremental change in bus reactive power injection
 = Incremental change in bus voltage angle
V = Incremental change in bus voltage magnitude
The stability of the power system is influenced by P & Q factors. However, for voltage stability
analysis purpose, it is necessary to note relationship between V and Q. For that purpose P is considered constant
at all node, hence change of active power is considered 0 (zero), hence,
0
∆Q
=
JPθ JPV
JQθ JQV
∆θ
∆V
Then obtained,
∆Q = JQV − JQθJPθ
−1
JPθ ∆V (2)
Then,
∆Q = JR ∆V
∆V = JR
−1
∆Q (3)
Where,
JR = JQV − JQθJPθ
−1
JPθ
JR is the reduced Jacobian matrix. This matrix make a discern between P,Q and V so it is easier to
perform voltage stability analysis.This approach computationally efficient rather than performing full Jacobian
matrix. This JR demonstrate direct relationship between reactive power injection and voltage magnitude for each
buses. Each buses which most contributed to the voltage instability can be obtained by extracting reactive
participation index from JR
-1
. To see voltage changes on each buses, equation 3 is formed in matrix, hence,
∆V1
∆V2
⋮
∆Vm
=
℘11 ℘12 ⋯ ℘1n
℘21
⋮
℘22 ⋯
⋮ ⋱
℘2n
⋮
℘m1 ℘m2 ⋯ ℘mn
−1
∆Q1
∆Q2
⋮
∆Qm
(4)
To obtain the best location among weak buses then elements of inversed JR are summed up vertically.
The highest reactive participation index is ideal for capacitor placement. Every voltage changes in each buses
depend on multiplication between elements of inversed JR and Q. Reactive participation index (RPI) can be
used to determine which buses is the most ideal for capacitor placement, which is formulated as,
Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive
DOI: 10.9790/1676-10418290 www.iosrjournals.org 84 | Page
℘11 ℘12 ⋯ ℘1n
℘21
⋮
℘22 ⋯
⋮ ⋱
℘2n
⋮
℘m 1 ℘m 2 ⋯ ℘mn
RPI 1 RPI 2 ⋯ RPI n
+ (5)
Eigenvalue of reduced Jacobianmatrix is used to portray how close the system to instability. As the
system becomes more stressed, eigenvalue will become smaller.The smaller the eigenvalue is, the closer the
system to instability. When minimum eigenvalue is equal to zero, then system is collapse since it undergoes
infinite changes for reactive power changes. The formula for eigenvalue is as follow:
 = Eigen [JR] (6)
III. PROPOSED METHOD FOR FINDING IDEAL BUSES
Figure 1 shows the flowchart of the proposed method. To perform this research new method is
developed using new technique of finding ideal buses for capacitor placement as described in Part II.
Figure 1. Flowchart of reactive participation index method for placement of capacitors
Figure 1 shows process of improving voltage profile of the system. When all of the area of the system
is 0.95<V<1.05 pu, then the process is stop. Stability of system is measure by extracting eigenvalue.
IV. THE TEST SYSTEM: THE SOUTH SULAWESI SYSTEM IN INDONESIA
The proposed method is simulated at a real large power system in Indonesia, the South Sulawesi System.
This section gives a brief review on the case study system.
South Sulawesi is located in the center of Indonesia and it is an interconnected system comprises of many
different power generations which are associated by transmission lines of 150 kV, 70 kV and 30 kV. This system
has unique attribute where the main cost-effective power generation centers are located in the northern part of the
system, whereas the predominant load center is located in the southern part. Figure 2 shows the interconnected
system of South Sulawesi. The total power generations in the northern part of the system is around 559 MW with
details as follow [22] :
 Bakaru hydro power plant (PLTA Bakaru) 127.7 MW
 Suppa diesel power plant (PLTD Suppa) 62.2 MW
 Sengkang steam and gas power plant (PLTGU Sengkang) 320 MW
 Barru steam power plant (PLTU Barru) 50 MW
Whereas total generation in the southern part is 444 MW from:
 Tello power plants (gas, steam and diesel) 169 MW
 BiliBili hydro power plant 20 MW
 Sewatama diesel power plant 15 MW
Start
End
Data
Power Flow
Voltage
Stability Limit
Stability Level
New Reactive
Participation Index
Setup Compensation
Device
Yes No
Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive
DOI: 10.9790/1676-10418290 www.iosrjournals.org 85 | Page
 Jeneponto steam power plant 240 MW
with total load of the system is around 860 MW.
Figure 2. The South Sulawesi interconnected power system, Indonesia [23]
V. RESULTS AND ANALYSIS
The simulation uses data from the Indonesian state electricity company (PT. PLN) as of 11 November
2014). Figure 3 shows initial voltage profile condition of the system. There are several under voltage stability
buses which potentially lead the system to voltage collapse. Table 1 below shows the unstable buses with their
voltages.
Figure 3. Voltage profile of Sulsel system at peakload [23]
0.9
0.92
0.94
0.96
0.98
1
1.02
1.04
1.06
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31
VoltageMagnitude(pu)
Bus
Voltate Stability Limit
Lower Limit 0.95 pu
Upper Limit 1.05 pu
Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive
DOI: 10.9790/1676-10418290 www.iosrjournals.org 86 | Page
Table 1. Under voltage buses
Buses /Substations Voltage Magnitude (pu)
12/Pangkep(150) 0.934
13/Bosowa 0.925
14/Kima 0.931
17/Mandai 0.935
18/Daya 0.933
19/Tello(150) 0.932
20/Tello(70) 0.932
21/Tallo Lama(150) 0.932
26/Tallo Lama(70) 0.94
27/TanjungBunga 0.937
28/Panakkukang 0.931
In order to find ideal buses for capacitor banks then the reactive participation index (RPI) at all load
buses are calculated. At the first iteration, bus 14 (Kima) has the highest RPI, hence this bus is selected as the
location for reactive power injection. For the first time, the injection is 10 MVar and this is repeated until the
highest value of RPI changes to other bus. For optimal size of capacitors found for bus 14 (Kima) is 80 MVar.
Then at the next process, bus 13 (Bosowa) has the biggest RPI, and chosen as location for the second reactive
power injection. The optimal size for capacitors at this bus is 50 MVar. Figure 4 shows the RPI value for every
steps in determining location for reactive power injection, which is concluded in Table 2. There are totally of
210 MVar reactive compensation injections needed to bring the system back to the stability limit. Figure 5
shows the voltage profile of the system before and after capacitor banks placement. All voltage at all buses are
between the stability limit. Network losses around 24.251 MW and reactive losses 29.869 MW.
Figure 4. Reactive Participation Index of each load buses
Table 2. Buses, Size and Number of Capacitor based on proposed method
Bus No. Substations Injected MVar
13 Bosowa 50
14 Kima 80
17 Mandai 60
20 Tello 20
Total 210
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31
ReactiveParticipationIndex
Bus
1st Iteration
2nd Iteration
3rd Iteration
4th Iteration
Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive
DOI: 10.9790/1676-10418290 www.iosrjournals.org 87 | Page
Figure 5. Voltage profile shows an improvement after capacitor installation
Figure 6 and 7 show the increase of eigenvalue for every iterations and comparison of eigenvalue
before and after reactive power injection, respectively. As can be seen in Figure 6, there is an improvement in
stability in every iteration. Eigenvalue increases from 1.7379 to 1.753. Eigenvalue at initial state 1.7096 and
potentially increase to 1.753 if 210 MVar of capacitor banks are injected to the system. This informs that the
system is more stable after the injection of reactive power.
Figure 6. Increase eigenvalue in each iteration
Figure 7. Eigenvalue of initial and proposed capacitor installation
0.9
0.92
0.94
0.96
0.98
1
1.02
1.04
1.06
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31
VoltageMagnitude(pu)
Bus
Limit (0.95<V1.05 pu)
Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive
DOI: 10.9790/1676-10418290 www.iosrjournals.org 88 | Page
To evaluatethe robustness of proposed method above, this results are compared using 3 different
configurations. 1st
configuration using same capacity of capacitor but divided by 4 evenly at all buses with high
RPI which is as shown below,
Table 3. Placement and size of MVar injection for 1st
configuration
Bus No. Injected Mvar
Bus 13 52.5
Bus 14 52.5
Bus 17 52.5
Bus 20 52.5
Total 210
Figure 8 shows the voltage profile of the system after the injection of capacitors based on Table 3.
Eventhough with the same total injection of 210 MVar, but there are still several buses with under voltage
condition. Buses 21, 27 and 28 are still under stability limit (<0.95 pu) and minimum eigenvalue is achieved
only 1.7453. This configuration generate losses of active power around 24.756 MW and reactive power 30.827
MVar. This means dividing the MVar injection into 4 equal size is no better than the proposed method which is
present lower nework losses
Figure 8. Voltage profile of 1st
configuration
2nd
configuration using same size of capacitor, but total 210 MVar are injected at one single bus. In this
configuration, the simulations are done by injecting 210 MVar at each of these buses: 13, 14, 17, and 20
separetely, and test is performed one by one. Figure 9 shows voltage profile of the system if 210 MVar capacitor
installed. None of the voltage profile based on these placement meet voltage stability required for the system.
Table 4 presents the eigenvalue and network losses of 2nd
configuration. The lowest losses can be achieved in
this configuration is installation at bus 14 but still higher than proposed method.
Figure 9. Voltage profile 2nd
configuration.
0.9
0.95
1
1.05
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31
VoltageMagnitude(pu)
Bus
Voltage Stability Limit
Pu
Upper limit
0.9
0.92
0.94
0.96
0.98
1
1.02
1.04
1.06
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31
VoltageMagnitude(pu)
Bus 14 Bus 13 Bus 17 Bus 20
Bus
Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive
DOI: 10.9790/1676-10418290 www.iosrjournals.org 89 | Page
Table 4. Eigenvalue and network losses 2nd
configuration
Bus No. Eigenvalue
Network Losses
MW MVar
14 1.7791 24.366 34.009
13 1.7562 24.869 34.967
17 1.7193 31.417 47.117
20 1.7184 28.876 41.766
3rd
Configuration using buses with small RPI of the proposed method and using the same size of
capacitors. Bus 1, 4, 6 and 9 are chosen, since they have small RPI. Each of them are injected 52.5 MVar.
Figure 10 shows the voltage profile of the South Sulawesi system after the injection of capacitors based on 3rd
configuration. As can be seen, misplacement of capacitor injection can also increase voltage higher than 1.05
pu, which cause over voltages. Improper placement of these capacitor can lead system out of voltage stability
limit which degrade system quality. Eigenvalue obtained is 1.7099. Losses of active power and reactive power
are 23.021 MW and 32.687 MVar, respectively. This configuration generate higher reactive power losses and
lower stability than proposed method.
Figure 10. Voltage profile of 3rd
configuration
VI. CONCLUSIONS
Conclusions that can be taken from this research are:
1. Based on simulation results, before capacitors installation at peak load, some areas are under voltage and
this condition potentially interfere system stability. These bus are buses 12 13, 14, 17, 18, 19, 20, 21, 26,
27 and 28. 4 Based on proposed method bus 14, 13, 17 and 20 are the best buses for reactive power
injection.
2. By using reactive participation index, it is successfully choose the right buses for capacitors placement to
improve voltage profile compared to 3 other configurations.
3. Method used in this paper demonstrates its strength to overcome problem in voltage stability. By using the
method, voltage profile improved with minimum injection of capacitor in size and number. Voltage profile
is align in 0.95<V<1.05 pu.
REFERENCES
[1] A. Arief, "Under Voltage Load Shedding Using Trajectory Sensitivity Analysis Considering Dynamic Loads,"
Universal Journal of Electrical and Electronic Engineering, vol. 2, No. 3, pp. 118 - 123, DOI:
10.13189/ujeee.2014.020304, 2014.
[2] A. Arief, et al., "Under voltage load shedding in power systems with wind turbine-driven doubly fed induction
generators," Electric Power Systems Research, vol. 96, pp. 91-100, DOI: 10.1016/j.epsr.2012.10.013, 2013.
[3] Z. Y. Dong and P. Zhang, Emerging Techniques in Power System Analysis: Springer, 2009.
[4] A. Arief, et al., "Under voltage load shedding incorporating bus participation factor," in 2010 Conference
Proceedings IPEC, 2010, pp. 561-566.
0.9
0.92
0.94
0.96
0.98
1
1.02
1.04
1.06
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31
VoltageMagnitude(pu)
Bus
Voltage Stability Limit
Pu
Upper Limit
Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive
DOI: 10.9790/1676-10418290 www.iosrjournals.org 90 | Page
[5] M. Bachtiar Nappu, et al., "Transmission management for congested power system: A review of concepts, technical
challenges and development of a new methodology," Renewable and Sustainable Energy Reviews, vol. 38, pp. 572-
580, DOI:10.1016/j.rser.2014.05.089, 2014.
[6] M. B. Nappu, et al., "Market power implication on congested power system: A case study of financial withheld
strategy," International Journal of Electrical Power & Energy Systems, vol. 47, pp. 408-415, 2013.
[7] B. Gao, et al., "Voltage stability evaluation using modal analysis," IEEE Transactions on Power Systems, vol. 7, pp.
1529-1542, 1992.
[8] C. Sharma and M. G. Ganness, "Determination of Power System Voltage Stability Using Modal Analysis," in
International Conference on Power Engineering, Energy and Electrical Drives, POWERENG, 2007, pp. 381-387.
[9] S. Devi and M. Geethanjali, "Optimal location and sizing of Distribution Static Synchronous Series Compensator
using Particle Swarm Optimization," International Journal of Electrical Power & Energy Systems, vol. 62, pp. 646-
653, 2014.
[10] A. A. El-Fergany, "Involvement of cost savings and voltage stability indices in optimal capacitor allocation in radial
distribution networks using artificial bee colony algorithm," International Journal of Electrical Power & Energy
Systems, vol. 62, pp. 608-616, 2014.
[11] I. K. Kiran and J. Laxmi.A, "Shunt Versus Series Compensation in the Improvement of Power System Performance,"
IndianJournals.com, vol. Volume 2, No 1, 2010.
[12] C.-S. Lee, et al., "Capacitor placement of distribution systems using particle swarm optimization approaches,"
International Journal of Electrical Power & Energy Systems, vol. 64, pp. 839-851, 2015.
[13] A. Zeinalzadeh, et al., "Optimal multi objective placement and sizing of multiple DGs and shunt capacitor banks
simultaneously considering load uncertainty via MOPSO approach," International Journal of Electrical Power &
Energy Systems, vol. 67, pp. 336-349, 2015.
[14] V. U. Reddy, et al., "Capacitor placement for loss reduction in radial distribution network: a two stage approach,"
Journal of Electrical Engineering, vol. 12, No. 2, pp. 114-119, 2012.
[15] O. P. Mahela, et al., "Optimal Capacitor Placement Techniques in Transmission and Distribution Networks to
Reduce Line Losses and Voltage Stability Enhancement: A Review," IOSR Journal of Electrical and Electronics
Engineering (IOSR-JEEE), vol. 3, no. 4, pp. 1-8, 2012.
[16] A. Elsheikh, et al., "Optimal capacitor placement and sizing in radial electric power systems," Alexandria
Engineering Journal, vol. 53, pp. 809-816, 2014.
[17] K. R. Devabalaji, et al., "Optimal location and sizing of capacitor placement in radial distribution system using
Bacterial Foraging Optimization Algorithm," International Journal of Electrical Power & Energy Systems, vol. 71,
pp. 383-390, 2015.
[18] A. A. El-Fergany and A. Y. Abdelaziz, "Capacitor placement for net saving maximization and system stability
enhancement in distribution networks using artificial bee colony-based approach," International Journal of Electrical
Power & Energy Systems, vol. 54, pp. 235-243, 2014.
[19] V. U. Reddy and A. Manoj, "Optimal Capacitor Placement for Loss Reduction in Distribution Systems Using Bat
Algorithm," IOSR Journal of Engineering, vol. 2, No. 10, pp. 23-27, 2012.
[20] R. MuthuKumar and K. Thanushkodi, "Capacitor Placement and Reconfiguration of Distribution System with Hybrid
Fuzzy-Opposition based Differential Evolution Algorithm," IOSR Journal of Electrical and Electronics Engineering
(IOSR-JEEE), vol. 6, no. 4, pp. 64-69, 2013.
[21] M. R. Amin and R. B. Roy, "Determination of Volume of Capacitor Bank for Static VAR Compensator,"
International Journal of Electrical and Computer Engineering (IJECE), vol. 4, No. 4, August 2014, pp. 512-519,
2014.
[22] Mudakir, "Database Sistem Simulasi 2015," AP2B PT. PLN (Persero) Wilayah VIII, Sulselbar2014.
[23] P. PLN(Persero), Rencana Usaha Penyediaan Tenaga Listrik PT PLN (Persero) 2013 - 2022, 2013-2022.

More Related Content

What's hot

MICROCONTROLLER BASED SOLAR POWER INVERTER
MICROCONTROLLER BASED SOLAR POWER INVERTERMICROCONTROLLER BASED SOLAR POWER INVERTER
MICROCONTROLLER BASED SOLAR POWER INVERTERIAEME Publication
 
Open-Delta VSC Based Voltage Controller in Isolated Power Systems
Open-Delta VSC Based Voltage Controller in Isolated Power SystemsOpen-Delta VSC Based Voltage Controller in Isolated Power Systems
Open-Delta VSC Based Voltage Controller in Isolated Power SystemsIJPEDS-IAES
 
International Journal of Engineering Research and Development
International Journal of Engineering Research and DevelopmentInternational Journal of Engineering Research and Development
International Journal of Engineering Research and DevelopmentIJERD Editor
 
Improvement of Power Quality using Fuzzy Logic Controller in Grid Connected P...
Improvement of Power Quality using Fuzzy Logic Controller in Grid Connected P...Improvement of Power Quality using Fuzzy Logic Controller in Grid Connected P...
Improvement of Power Quality using Fuzzy Logic Controller in Grid Connected P...IAES-IJPEDS
 
Next Generation Researchers in Power Systems_Tao Yang_UCD EI
Next Generation Researchers in Power Systems_Tao Yang_UCD EINext Generation Researchers in Power Systems_Tao Yang_UCD EI
Next Generation Researchers in Power Systems_Tao Yang_UCD EITao Yang
 
Improved Power Quality by using STATCOM Under Various Loading Conditions
Improved Power Quality by using STATCOM Under Various Loading ConditionsImproved Power Quality by using STATCOM Under Various Loading Conditions
Improved Power Quality by using STATCOM Under Various Loading ConditionsIJMTST Journal
 
Comparison of PI and ANN Control Techniques for Nine Switches UPQC to Improve...
Comparison of PI and ANN Control Techniques for Nine Switches UPQC to Improve...Comparison of PI and ANN Control Techniques for Nine Switches UPQC to Improve...
Comparison of PI and ANN Control Techniques for Nine Switches UPQC to Improve...MABUSUBANI SHAIK
 
Analysis and Simulation of Solar PV Connected with Grid Accomplished with Boo...
Analysis and Simulation of Solar PV Connected with Grid Accomplished with Boo...Analysis and Simulation of Solar PV Connected with Grid Accomplished with Boo...
Analysis and Simulation of Solar PV Connected with Grid Accomplished with Boo...YogeshIJTSRD
 
Close Loop Control of Induction Motor Using Z-Source Inverter
Close Loop Control of Induction Motor Using Z-Source InverterClose Loop Control of Induction Motor Using Z-Source Inverter
Close Loop Control of Induction Motor Using Z-Source InverterIJSRD
 
Simulation of unified power quality conditioner for power quality improvement...
Simulation of unified power quality conditioner for power quality improvement...Simulation of unified power quality conditioner for power quality improvement...
Simulation of unified power quality conditioner for power quality improvement...Alexander Decker
 
Integration of Unified Power Quality Controller with DG
Integration of Unified Power Quality Controller with DGIntegration of Unified Power Quality Controller with DG
Integration of Unified Power Quality Controller with DGIJRST Journal
 

What's hot (20)

Modeling and design of an adaptive control for VSC-HVDC system under paramete...
Modeling and design of an adaptive control for VSC-HVDC system under paramete...Modeling and design of an adaptive control for VSC-HVDC system under paramete...
Modeling and design of an adaptive control for VSC-HVDC system under paramete...
 
MICROCONTROLLER BASED SOLAR POWER INVERTER
MICROCONTROLLER BASED SOLAR POWER INVERTERMICROCONTROLLER BASED SOLAR POWER INVERTER
MICROCONTROLLER BASED SOLAR POWER INVERTER
 
Open-Delta VSC Based Voltage Controller in Isolated Power Systems
Open-Delta VSC Based Voltage Controller in Isolated Power SystemsOpen-Delta VSC Based Voltage Controller in Isolated Power Systems
Open-Delta VSC Based Voltage Controller in Isolated Power Systems
 
At4101261265
At4101261265At4101261265
At4101261265
 
Modeling and control of a hybrid DC/DC/AC converter to transfer power under d...
Modeling and control of a hybrid DC/DC/AC converter to transfer power under d...Modeling and control of a hybrid DC/DC/AC converter to transfer power under d...
Modeling and control of a hybrid DC/DC/AC converter to transfer power under d...
 
International Journal of Engineering Research and Development
International Journal of Engineering Research and DevelopmentInternational Journal of Engineering Research and Development
International Journal of Engineering Research and Development
 
C1102031116
C1102031116C1102031116
C1102031116
 
Improvement of Power Quality using Fuzzy Logic Controller in Grid Connected P...
Improvement of Power Quality using Fuzzy Logic Controller in Grid Connected P...Improvement of Power Quality using Fuzzy Logic Controller in Grid Connected P...
Improvement of Power Quality using Fuzzy Logic Controller in Grid Connected P...
 
Next Generation Researchers in Power Systems_Tao Yang_UCD EI
Next Generation Researchers in Power Systems_Tao Yang_UCD EINext Generation Researchers in Power Systems_Tao Yang_UCD EI
Next Generation Researchers in Power Systems_Tao Yang_UCD EI
 
Improved Power Quality by using STATCOM Under Various Loading Conditions
Improved Power Quality by using STATCOM Under Various Loading ConditionsImproved Power Quality by using STATCOM Under Various Loading Conditions
Improved Power Quality by using STATCOM Under Various Loading Conditions
 
Comparison of PI and ANN Control Techniques for Nine Switches UPQC to Improve...
Comparison of PI and ANN Control Techniques for Nine Switches UPQC to Improve...Comparison of PI and ANN Control Techniques for Nine Switches UPQC to Improve...
Comparison of PI and ANN Control Techniques for Nine Switches UPQC to Improve...
 
Analysis and Simulation of Solar PV Connected with Grid Accomplished with Boo...
Analysis and Simulation of Solar PV Connected with Grid Accomplished with Boo...Analysis and Simulation of Solar PV Connected with Grid Accomplished with Boo...
Analysis and Simulation of Solar PV Connected with Grid Accomplished with Boo...
 
Modeling of static var compensator-high voltage direct current to provide pow...
Modeling of static var compensator-high voltage direct current to provide pow...Modeling of static var compensator-high voltage direct current to provide pow...
Modeling of static var compensator-high voltage direct current to provide pow...
 
The new approach minimizes harmonics in a single-phase three-level NPC 400 Hz...
The new approach minimizes harmonics in a single-phase three-level NPC 400 Hz...The new approach minimizes harmonics in a single-phase three-level NPC 400 Hz...
The new approach minimizes harmonics in a single-phase three-level NPC 400 Hz...
 
Improved 25-level inverter topology with reduced part count for PV grid-tie a...
Improved 25-level inverter topology with reduced part count for PV grid-tie a...Improved 25-level inverter topology with reduced part count for PV grid-tie a...
Improved 25-level inverter topology with reduced part count for PV grid-tie a...
 
Close Loop Control of Induction Motor Using Z-Source Inverter
Close Loop Control of Induction Motor Using Z-Source InverterClose Loop Control of Induction Motor Using Z-Source Inverter
Close Loop Control of Induction Motor Using Z-Source Inverter
 
Simulation of unified power quality conditioner for power quality improvement...
Simulation of unified power quality conditioner for power quality improvement...Simulation of unified power quality conditioner for power quality improvement...
Simulation of unified power quality conditioner for power quality improvement...
 
Reduction of total harmonic distortion of three-phase inverter using alternat...
Reduction of total harmonic distortion of three-phase inverter using alternat...Reduction of total harmonic distortion of three-phase inverter using alternat...
Reduction of total harmonic distortion of three-phase inverter using alternat...
 
Using Y-source network as a connector between turbine and network in the stru...
Using Y-source network as a connector between turbine and network in the stru...Using Y-source network as a connector between turbine and network in the stru...
Using Y-source network as a connector between turbine and network in the stru...
 
Integration of Unified Power Quality Controller with DG
Integration of Unified Power Quality Controller with DGIntegration of Unified Power Quality Controller with DG
Integration of Unified Power Quality Controller with DG
 

Viewers also liked (20)

L010616372
L010616372L010616372
L010616372
 
O01061103111
O01061103111O01061103111
O01061103111
 
D017651519
D017651519D017651519
D017651519
 
A012140107
A012140107A012140107
A012140107
 
H011117484
H011117484H011117484
H011117484
 
D017442330
D017442330D017442330
D017442330
 
J017536064
J017536064J017536064
J017536064
 
B1102021418
B1102021418B1102021418
B1102021418
 
N01212101114
N01212101114N01212101114
N01212101114
 
A017330108
A017330108A017330108
A017330108
 
O017658697
O017658697O017658697
O017658697
 
Q01741118123
Q01741118123Q01741118123
Q01741118123
 
B1803031217
B1803031217B1803031217
B1803031217
 
F017154347
F017154347F017154347
F017154347
 
E1302042833
E1302042833E1302042833
E1302042833
 
D018212428
D018212428D018212428
D018212428
 
E0812730
E0812730E0812730
E0812730
 
B011131018
B011131018B011131018
B011131018
 
Q110304108111
Q110304108111Q110304108111
Q110304108111
 
M012329497
M012329497M012329497
M012329497
 

Similar to K010418290

Selective localization of capacitor banks considering stability aspects in po...
Selective localization of capacitor banks considering stability aspects in po...Selective localization of capacitor banks considering stability aspects in po...
Selective localization of capacitor banks considering stability aspects in po...IAEME Publication
 
Ann based voltage stability margin assessment
Ann based voltage stability margin assessmentAnn based voltage stability margin assessment
Ann based voltage stability margin assessmentNaganathan G Sesaiyan
 
International Journal of Engineering Research and Development (IJERD)
International Journal of Engineering Research and Development (IJERD)International Journal of Engineering Research and Development (IJERD)
International Journal of Engineering Research and Development (IJERD)IJERD Editor
 
A Novel Approach for Power Quality Improvement in Distributed Generation
A Novel Approach for Power Quality Improvement in Distributed GenerationA Novel Approach for Power Quality Improvement in Distributed Generation
A Novel Approach for Power Quality Improvement in Distributed Generationseema appa
 
Online voltage stability margin assessment
Online voltage stability margin assessmentOnline voltage stability margin assessment
Online voltage stability margin assessmentNaganathan G Sesaiyan
 
A Study of Load Flow Analysis Using Particle Swarm Optimization
A Study of Load Flow Analysis Using Particle Swarm OptimizationA Study of Load Flow Analysis Using Particle Swarm Optimization
A Study of Load Flow Analysis Using Particle Swarm OptimizationIJERA Editor
 
Influence of Static VAR Compensator for Undervoltage Load Shedding to Avoid V...
Influence of Static VAR Compensator for Undervoltage Load Shedding to Avoid V...Influence of Static VAR Compensator for Undervoltage Load Shedding to Avoid V...
Influence of Static VAR Compensator for Undervoltage Load Shedding to Avoid V...IJAPEJOURNAL
 
Enhancement of Voltage Stability on IEEE 14 Bus Systems Using Static Var Comp...
Enhancement of Voltage Stability on IEEE 14 Bus Systems Using Static Var Comp...Enhancement of Voltage Stability on IEEE 14 Bus Systems Using Static Var Comp...
Enhancement of Voltage Stability on IEEE 14 Bus Systems Using Static Var Comp...paperpublications3
 
IRJET- Load Flow Analysis of IEEE 14 Bus Systems in Matlab by using Fast Deco...
IRJET- Load Flow Analysis of IEEE 14 Bus Systems in Matlab by using Fast Deco...IRJET- Load Flow Analysis of IEEE 14 Bus Systems in Matlab by using Fast Deco...
IRJET- Load Flow Analysis of IEEE 14 Bus Systems in Matlab by using Fast Deco...IRJET Journal
 
IRJET- Assessment of Voltage Stability in a Power System Network and its Impr...
IRJET- Assessment of Voltage Stability in a Power System Network and its Impr...IRJET- Assessment of Voltage Stability in a Power System Network and its Impr...
IRJET- Assessment of Voltage Stability in a Power System Network and its Impr...IRJET Journal
 
Voltage Stability Investigation of the Nigeria 330KV Interconnected Grid Syst...
Voltage Stability Investigation of the Nigeria 330KV Interconnected Grid Syst...Voltage Stability Investigation of the Nigeria 330KV Interconnected Grid Syst...
Voltage Stability Investigation of the Nigeria 330KV Interconnected Grid Syst...Onyebuchi nosiri
 
Power Factor Improvement in Distribution System using DSTATCOM Based on Unit ...
Power Factor Improvement in Distribution System using DSTATCOM Based on Unit ...Power Factor Improvement in Distribution System using DSTATCOM Based on Unit ...
Power Factor Improvement in Distribution System using DSTATCOM Based on Unit ...RSIS International
 
Voltage Stability Improvement by Reactive Power Rescheduling Incorporating P...
Voltage Stability Improvement by Reactive Power Rescheduling  Incorporating P...Voltage Stability Improvement by Reactive Power Rescheduling  Incorporating P...
Voltage Stability Improvement by Reactive Power Rescheduling Incorporating P...IJMER
 
Three Phase Load Flow Analysis on Four Bus System
Three Phase Load Flow Analysis on Four Bus SystemThree Phase Load Flow Analysis on Four Bus System
Three Phase Load Flow Analysis on Four Bus Systempaperpublications3
 
Advance Technology in Application of Four Leg Inverters to UPQC
Advance Technology in Application of Four Leg Inverters to UPQCAdvance Technology in Application of Four Leg Inverters to UPQC
Advance Technology in Application of Four Leg Inverters to UPQCIJPEDS-IAES
 

Similar to K010418290 (20)

Selective localization of capacitor banks considering stability aspects in po...
Selective localization of capacitor banks considering stability aspects in po...Selective localization of capacitor banks considering stability aspects in po...
Selective localization of capacitor banks considering stability aspects in po...
 
Ad03401640171
Ad03401640171Ad03401640171
Ad03401640171
 
Ann based voltage stability margin assessment
Ann based voltage stability margin assessmentAnn based voltage stability margin assessment
Ann based voltage stability margin assessment
 
G046033742
G046033742G046033742
G046033742
 
International Journal of Engineering Research and Development (IJERD)
International Journal of Engineering Research and Development (IJERD)International Journal of Engineering Research and Development (IJERD)
International Journal of Engineering Research and Development (IJERD)
 
A Novel Approach for Power Quality Improvement in Distributed Generation
A Novel Approach for Power Quality Improvement in Distributed GenerationA Novel Approach for Power Quality Improvement in Distributed Generation
A Novel Approach for Power Quality Improvement in Distributed Generation
 
Eh25815821
Eh25815821Eh25815821
Eh25815821
 
Online voltage stability margin assessment
Online voltage stability margin assessmentOnline voltage stability margin assessment
Online voltage stability margin assessment
 
A Study of Load Flow Analysis Using Particle Swarm Optimization
A Study of Load Flow Analysis Using Particle Swarm OptimizationA Study of Load Flow Analysis Using Particle Swarm Optimization
A Study of Load Flow Analysis Using Particle Swarm Optimization
 
Influence of Static VAR Compensator for Undervoltage Load Shedding to Avoid V...
Influence of Static VAR Compensator for Undervoltage Load Shedding to Avoid V...Influence of Static VAR Compensator for Undervoltage Load Shedding to Avoid V...
Influence of Static VAR Compensator for Undervoltage Load Shedding to Avoid V...
 
Enhancement of Voltage Stability on IEEE 14 Bus Systems Using Static Var Comp...
Enhancement of Voltage Stability on IEEE 14 Bus Systems Using Static Var Comp...Enhancement of Voltage Stability on IEEE 14 Bus Systems Using Static Var Comp...
Enhancement of Voltage Stability on IEEE 14 Bus Systems Using Static Var Comp...
 
IRJET- Load Flow Analysis of IEEE 14 Bus Systems in Matlab by using Fast Deco...
IRJET- Load Flow Analysis of IEEE 14 Bus Systems in Matlab by using Fast Deco...IRJET- Load Flow Analysis of IEEE 14 Bus Systems in Matlab by using Fast Deco...
IRJET- Load Flow Analysis of IEEE 14 Bus Systems in Matlab by using Fast Deco...
 
IRJET- Assessment of Voltage Stability in a Power System Network and its Impr...
IRJET- Assessment of Voltage Stability in a Power System Network and its Impr...IRJET- Assessment of Voltage Stability in a Power System Network and its Impr...
IRJET- Assessment of Voltage Stability in a Power System Network and its Impr...
 
Eo35798805
Eo35798805Eo35798805
Eo35798805
 
Voltage Stability Investigation of the Nigeria 330KV Interconnected Grid Syst...
Voltage Stability Investigation of the Nigeria 330KV Interconnected Grid Syst...Voltage Stability Investigation of the Nigeria 330KV Interconnected Grid Syst...
Voltage Stability Investigation of the Nigeria 330KV Interconnected Grid Syst...
 
G1101045767
G1101045767G1101045767
G1101045767
 
Power Factor Improvement in Distribution System using DSTATCOM Based on Unit ...
Power Factor Improvement in Distribution System using DSTATCOM Based on Unit ...Power Factor Improvement in Distribution System using DSTATCOM Based on Unit ...
Power Factor Improvement in Distribution System using DSTATCOM Based on Unit ...
 
Voltage Stability Improvement by Reactive Power Rescheduling Incorporating P...
Voltage Stability Improvement by Reactive Power Rescheduling  Incorporating P...Voltage Stability Improvement by Reactive Power Rescheduling  Incorporating P...
Voltage Stability Improvement by Reactive Power Rescheduling Incorporating P...
 
Three Phase Load Flow Analysis on Four Bus System
Three Phase Load Flow Analysis on Four Bus SystemThree Phase Load Flow Analysis on Four Bus System
Three Phase Load Flow Analysis on Four Bus System
 
Advance Technology in Application of Four Leg Inverters to UPQC
Advance Technology in Application of Four Leg Inverters to UPQCAdvance Technology in Application of Four Leg Inverters to UPQC
Advance Technology in Application of Four Leg Inverters to UPQC
 

More from IOSR Journals (20)

A011140104
A011140104A011140104
A011140104
 
M0111397100
M0111397100M0111397100
M0111397100
 
L011138596
L011138596L011138596
L011138596
 
K011138084
K011138084K011138084
K011138084
 
J011137479
J011137479J011137479
J011137479
 
I011136673
I011136673I011136673
I011136673
 
G011134454
G011134454G011134454
G011134454
 
H011135565
H011135565H011135565
H011135565
 
F011134043
F011134043F011134043
F011134043
 
E011133639
E011133639E011133639
E011133639
 
D011132635
D011132635D011132635
D011132635
 
C011131925
C011131925C011131925
C011131925
 
B011130918
B011130918B011130918
B011130918
 
A011130108
A011130108A011130108
A011130108
 
I011125160
I011125160I011125160
I011125160
 
H011124050
H011124050H011124050
H011124050
 
G011123539
G011123539G011123539
G011123539
 
F011123134
F011123134F011123134
F011123134
 
E011122530
E011122530E011122530
E011122530
 
D011121524
D011121524D011121524
D011121524
 

Recently uploaded

MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MIND CTI
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdfSandro Moreira
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontologyjohnbeverley2021
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxRustici Software
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...DianaGray10
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfOrbitshub
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingEdi Saputra
 
API Governance and Monetization - The evolution of API governance
API Governance and Monetization -  The evolution of API governanceAPI Governance and Monetization -  The evolution of API governance
API Governance and Monetization - The evolution of API governanceWSO2
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAndrey Devyatkin
 
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Zilliz
 
Stronger Together: Developing an Organizational Strategy for Accessible Desig...
Stronger Together: Developing an Organizational Strategy for Accessible Desig...Stronger Together: Developing an Organizational Strategy for Accessible Desig...
Stronger Together: Developing an Organizational Strategy for Accessible Desig...caitlingebhard1
 
Quantum Leap in Next-Generation Computing
Quantum Leap in Next-Generation ComputingQuantum Leap in Next-Generation Computing
Quantum Leap in Next-Generation ComputingWSO2
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Victor Rentea
 
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodJuan lago vázquez
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusZilliz
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Victor Rentea
 
How to Check CNIC Information Online with Pakdata cf
How to Check CNIC Information Online with Pakdata cfHow to Check CNIC Information Online with Pakdata cf
How to Check CNIC Information Online with Pakdata cfdanishmna97
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
Navigating Identity and Access Management in the Modern Enterprise
Navigating Identity and Access Management in the Modern EnterpriseNavigating Identity and Access Management in the Modern Enterprise
Navigating Identity and Access Management in the Modern EnterpriseWSO2
 
WSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2
 

Recently uploaded (20)

MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontology
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
API Governance and Monetization - The evolution of API governance
API Governance and Monetization -  The evolution of API governanceAPI Governance and Monetization -  The evolution of API governance
API Governance and Monetization - The evolution of API governance
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)
 
Stronger Together: Developing an Organizational Strategy for Accessible Desig...
Stronger Together: Developing an Organizational Strategy for Accessible Desig...Stronger Together: Developing an Organizational Strategy for Accessible Desig...
Stronger Together: Developing an Organizational Strategy for Accessible Desig...
 
Quantum Leap in Next-Generation Computing
Quantum Leap in Next-Generation ComputingQuantum Leap in Next-Generation Computing
Quantum Leap in Next-Generation Computing
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
 
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
 
How to Check CNIC Information Online with Pakdata cf
How to Check CNIC Information Online with Pakdata cfHow to Check CNIC Information Online with Pakdata cf
How to Check CNIC Information Online with Pakdata cf
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Navigating Identity and Access Management in the Modern Enterprise
Navigating Identity and Access Management in the Modern EnterpriseNavigating Identity and Access Management in the Modern Enterprise
Navigating Identity and Access Management in the Modern Enterprise
 
WSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering Developers
 

K010418290

  • 1. IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-ISSN: 2278-1676,p-ISSN: 2320-3331, Volume 10, Issue 4 Ver. I (July – Aug. 2015), PP 82-90 www.iosrjournals.org DOI: 10.9790/1676-10418290 www.iosrjournals.org 82 | Page Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive Participation Index Antamil, Ardiaty Arief and Indar Chaerah Gunadin Department of Electrical Engineering, UniversitasHasanuddin, Indonesia Abstract: This study proposed new method of improving voltage profile utilizing addition of inversed reduced Jacobian matrix elements vertically with the aim of determining location of reactive power compensation installation.This method is tested using actual network in Indonesia. In this analysis, enhancement of power system stability includes of voltage improvement and increase in stability index. By using this proposed method several buses appear as an ideal place for installation of capacitors. The results are also compared to different configuration to validate and demonstrate the effectiveness of the method. Keywords – voltage profile, voltage stability, voltage collapse, modal analysis, steady-state analysis, reactive power compensations, reactive participation index. I. INTRODUCTION Power system stability has been considered as a main requisitefor a safe and trustworthy process in a power system for over ninety years[1-3]. Voltage stability is a common problem that occurs anywhere in the world.Nowadays, electrical systems are thoroughly stressed and running at the stability limit with smaller capacity and margin [4] hence may cause congestion problems [5, 6]. This occurs due to the small and large disturbances that affect the stability of operation.In addition, increasein active and reactive power also contributes to the decrease in the voltage. Voltage dropdue to uncontrolled reactive power can lead the system to collapse. As the system are getting stressed,it is necessary for an evaluation of the weak point where potential instability occurs, so that preventive action can be taken earlier and to avoid cascading failures. As it is well known, that voltage problem has resilient relation with reactive power injections. To find out the weak points in a system, there are several algorithms in the growing literature. One of the advanced method developed is Modal Analysis by [7]. In this technique,relationship between voltage (V) and reactive power (Q) is used to exploit the most contributed bus to system instability.The system is voltage stable, if the injection of reactive power increases and at the same time voltage magnitude also increases. The system is voltage unstable if at the same time reactive power increased and the voltage magnitude decreases[7, 8]. To overcome the voltage drop as described above, it is required compensation equipment to maintain the voltage magnitude remains at the desired level. There are many type of reactive compensation devices, such as: capacitor banks, static Var compensator (SVC) or static compensator (STATCOM). These reactive compensation devices have imperative function in improving voltage stability. Capacitor banks is one of the foremost and commonly used reactive compensators equipment. Capacitors have a very important role in the power system network because apart from being usedas reactive power compensation device, it can help to increase active power delivery and reduce transmission losses[9-15], therefore overall it can improve voltage profile of the system. However, installation of capacitor banks should be at the right buses so it can perform effectively. Various methods have been developed for placement of capacitor. References [16, 17] create Loss Sensitivity Factor to find capacitor placement location. Artificial bee colony algorithm is applied for capacitor allocation in [18]. Paper [19] designs two-stage approach using fuzzy logic and bat algorithm to determine location and size of capacitor. Authors in[20] propose opposition based differential evolution algorithm for reconfiguration and capacitor placement. However, these works only focus on the network losses reduction. In [21], fast decoupled method was employed to determine size for capacitor, but this work only assesses the voltage improvement, not the network losses. Nonetheless, the appropriate location and size of capacitor can reduce both network losses as well as enhance voltage stability. It is essential to develop an effective method that able to confirm both voltage stability of the system and location to improve the stability.This study enhances modal analysis technique for the effective placement of capacitor banks. Modal analysis is an analytic solutions approach that can give information about the voltage stability in a complex power system. In this work, the element of inversed reduced Jacobian matrix is added vertically to compute Reactive Participation Index (RPI). RPI informs about participation of a specific bus in improving voltage magnitude at critical buses based on its reactive power injection. The bus with the biggest RPI has the biggest influence in enhancing voltage profile after injected reactive power hence it is chosen as the
  • 2. Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive DOI: 10.9790/1676-10418290 www.iosrjournals.org 83 | Page location of capacitor banks placement. This method is simple but accurate and do not need complicated computational processes. This paper consist of five parts. Part 1 is introduction, Part 2 isthe breakdown of modal analysis approach and development of participation factor, Part 3describes method proposed, Part 4 informs about the South Sulawesi interconnected system in Indonesia as the case study, Part 5 presentsresearch data, results analysis, and validation,Part 6 is the final conclusion and closing of this research. II. BREAKDOWN OF MODAL ANALYSIS APPROACH TO COMPUTE REACTIVE PARTICIPATION INDEX (RPI) To evaluate the system stability, it often requires extensive and in-depth examination of the condition of the system. Therefore linearized steady state analysis is used to see the problems that exist on the voltage and reactive power. ∆P ∆Q = JPθ JPV JQθ JQV ∆Q ∆V (1) Where : P = Incremental change in bus real power Q = Incremental change in bus reactive power injection  = Incremental change in bus voltage angle V = Incremental change in bus voltage magnitude The stability of the power system is influenced by P & Q factors. However, for voltage stability analysis purpose, it is necessary to note relationship between V and Q. For that purpose P is considered constant at all node, hence change of active power is considered 0 (zero), hence, 0 ∆Q = JPθ JPV JQθ JQV ∆θ ∆V Then obtained, ∆Q = JQV − JQθJPθ −1 JPθ ∆V (2) Then, ∆Q = JR ∆V ∆V = JR −1 ∆Q (3) Where, JR = JQV − JQθJPθ −1 JPθ JR is the reduced Jacobian matrix. This matrix make a discern between P,Q and V so it is easier to perform voltage stability analysis.This approach computationally efficient rather than performing full Jacobian matrix. This JR demonstrate direct relationship between reactive power injection and voltage magnitude for each buses. Each buses which most contributed to the voltage instability can be obtained by extracting reactive participation index from JR -1 . To see voltage changes on each buses, equation 3 is formed in matrix, hence, ∆V1 ∆V2 ⋮ ∆Vm = ℘11 ℘12 ⋯ ℘1n ℘21 ⋮ ℘22 ⋯ ⋮ ⋱ ℘2n ⋮ ℘m1 ℘m2 ⋯ ℘mn −1 ∆Q1 ∆Q2 ⋮ ∆Qm (4) To obtain the best location among weak buses then elements of inversed JR are summed up vertically. The highest reactive participation index is ideal for capacitor placement. Every voltage changes in each buses depend on multiplication between elements of inversed JR and Q. Reactive participation index (RPI) can be used to determine which buses is the most ideal for capacitor placement, which is formulated as,
  • 3. Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive DOI: 10.9790/1676-10418290 www.iosrjournals.org 84 | Page ℘11 ℘12 ⋯ ℘1n ℘21 ⋮ ℘22 ⋯ ⋮ ⋱ ℘2n ⋮ ℘m 1 ℘m 2 ⋯ ℘mn RPI 1 RPI 2 ⋯ RPI n + (5) Eigenvalue of reduced Jacobianmatrix is used to portray how close the system to instability. As the system becomes more stressed, eigenvalue will become smaller.The smaller the eigenvalue is, the closer the system to instability. When minimum eigenvalue is equal to zero, then system is collapse since it undergoes infinite changes for reactive power changes. The formula for eigenvalue is as follow:  = Eigen [JR] (6) III. PROPOSED METHOD FOR FINDING IDEAL BUSES Figure 1 shows the flowchart of the proposed method. To perform this research new method is developed using new technique of finding ideal buses for capacitor placement as described in Part II. Figure 1. Flowchart of reactive participation index method for placement of capacitors Figure 1 shows process of improving voltage profile of the system. When all of the area of the system is 0.95<V<1.05 pu, then the process is stop. Stability of system is measure by extracting eigenvalue. IV. THE TEST SYSTEM: THE SOUTH SULAWESI SYSTEM IN INDONESIA The proposed method is simulated at a real large power system in Indonesia, the South Sulawesi System. This section gives a brief review on the case study system. South Sulawesi is located in the center of Indonesia and it is an interconnected system comprises of many different power generations which are associated by transmission lines of 150 kV, 70 kV and 30 kV. This system has unique attribute where the main cost-effective power generation centers are located in the northern part of the system, whereas the predominant load center is located in the southern part. Figure 2 shows the interconnected system of South Sulawesi. The total power generations in the northern part of the system is around 559 MW with details as follow [22] :  Bakaru hydro power plant (PLTA Bakaru) 127.7 MW  Suppa diesel power plant (PLTD Suppa) 62.2 MW  Sengkang steam and gas power plant (PLTGU Sengkang) 320 MW  Barru steam power plant (PLTU Barru) 50 MW Whereas total generation in the southern part is 444 MW from:  Tello power plants (gas, steam and diesel) 169 MW  BiliBili hydro power plant 20 MW  Sewatama diesel power plant 15 MW Start End Data Power Flow Voltage Stability Limit Stability Level New Reactive Participation Index Setup Compensation Device Yes No
  • 4. Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive DOI: 10.9790/1676-10418290 www.iosrjournals.org 85 | Page  Jeneponto steam power plant 240 MW with total load of the system is around 860 MW. Figure 2. The South Sulawesi interconnected power system, Indonesia [23] V. RESULTS AND ANALYSIS The simulation uses data from the Indonesian state electricity company (PT. PLN) as of 11 November 2014). Figure 3 shows initial voltage profile condition of the system. There are several under voltage stability buses which potentially lead the system to voltage collapse. Table 1 below shows the unstable buses with their voltages. Figure 3. Voltage profile of Sulsel system at peakload [23] 0.9 0.92 0.94 0.96 0.98 1 1.02 1.04 1.06 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 VoltageMagnitude(pu) Bus Voltate Stability Limit Lower Limit 0.95 pu Upper Limit 1.05 pu
  • 5. Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive DOI: 10.9790/1676-10418290 www.iosrjournals.org 86 | Page Table 1. Under voltage buses Buses /Substations Voltage Magnitude (pu) 12/Pangkep(150) 0.934 13/Bosowa 0.925 14/Kima 0.931 17/Mandai 0.935 18/Daya 0.933 19/Tello(150) 0.932 20/Tello(70) 0.932 21/Tallo Lama(150) 0.932 26/Tallo Lama(70) 0.94 27/TanjungBunga 0.937 28/Panakkukang 0.931 In order to find ideal buses for capacitor banks then the reactive participation index (RPI) at all load buses are calculated. At the first iteration, bus 14 (Kima) has the highest RPI, hence this bus is selected as the location for reactive power injection. For the first time, the injection is 10 MVar and this is repeated until the highest value of RPI changes to other bus. For optimal size of capacitors found for bus 14 (Kima) is 80 MVar. Then at the next process, bus 13 (Bosowa) has the biggest RPI, and chosen as location for the second reactive power injection. The optimal size for capacitors at this bus is 50 MVar. Figure 4 shows the RPI value for every steps in determining location for reactive power injection, which is concluded in Table 2. There are totally of 210 MVar reactive compensation injections needed to bring the system back to the stability limit. Figure 5 shows the voltage profile of the system before and after capacitor banks placement. All voltage at all buses are between the stability limit. Network losses around 24.251 MW and reactive losses 29.869 MW. Figure 4. Reactive Participation Index of each load buses Table 2. Buses, Size and Number of Capacitor based on proposed method Bus No. Substations Injected MVar 13 Bosowa 50 14 Kima 80 17 Mandai 60 20 Tello 20 Total 210 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 ReactiveParticipationIndex Bus 1st Iteration 2nd Iteration 3rd Iteration 4th Iteration
  • 6. Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive DOI: 10.9790/1676-10418290 www.iosrjournals.org 87 | Page Figure 5. Voltage profile shows an improvement after capacitor installation Figure 6 and 7 show the increase of eigenvalue for every iterations and comparison of eigenvalue before and after reactive power injection, respectively. As can be seen in Figure 6, there is an improvement in stability in every iteration. Eigenvalue increases from 1.7379 to 1.753. Eigenvalue at initial state 1.7096 and potentially increase to 1.753 if 210 MVar of capacitor banks are injected to the system. This informs that the system is more stable after the injection of reactive power. Figure 6. Increase eigenvalue in each iteration Figure 7. Eigenvalue of initial and proposed capacitor installation 0.9 0.92 0.94 0.96 0.98 1 1.02 1.04 1.06 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 VoltageMagnitude(pu) Bus Limit (0.95<V1.05 pu)
  • 7. Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive DOI: 10.9790/1676-10418290 www.iosrjournals.org 88 | Page To evaluatethe robustness of proposed method above, this results are compared using 3 different configurations. 1st configuration using same capacity of capacitor but divided by 4 evenly at all buses with high RPI which is as shown below, Table 3. Placement and size of MVar injection for 1st configuration Bus No. Injected Mvar Bus 13 52.5 Bus 14 52.5 Bus 17 52.5 Bus 20 52.5 Total 210 Figure 8 shows the voltage profile of the system after the injection of capacitors based on Table 3. Eventhough with the same total injection of 210 MVar, but there are still several buses with under voltage condition. Buses 21, 27 and 28 are still under stability limit (<0.95 pu) and minimum eigenvalue is achieved only 1.7453. This configuration generate losses of active power around 24.756 MW and reactive power 30.827 MVar. This means dividing the MVar injection into 4 equal size is no better than the proposed method which is present lower nework losses Figure 8. Voltage profile of 1st configuration 2nd configuration using same size of capacitor, but total 210 MVar are injected at one single bus. In this configuration, the simulations are done by injecting 210 MVar at each of these buses: 13, 14, 17, and 20 separetely, and test is performed one by one. Figure 9 shows voltage profile of the system if 210 MVar capacitor installed. None of the voltage profile based on these placement meet voltage stability required for the system. Table 4 presents the eigenvalue and network losses of 2nd configuration. The lowest losses can be achieved in this configuration is installation at bus 14 but still higher than proposed method. Figure 9. Voltage profile 2nd configuration. 0.9 0.95 1 1.05 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 VoltageMagnitude(pu) Bus Voltage Stability Limit Pu Upper limit 0.9 0.92 0.94 0.96 0.98 1 1.02 1.04 1.06 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 VoltageMagnitude(pu) Bus 14 Bus 13 Bus 17 Bus 20 Bus
  • 8. Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive DOI: 10.9790/1676-10418290 www.iosrjournals.org 89 | Page Table 4. Eigenvalue and network losses 2nd configuration Bus No. Eigenvalue Network Losses MW MVar 14 1.7791 24.366 34.009 13 1.7562 24.869 34.967 17 1.7193 31.417 47.117 20 1.7184 28.876 41.766 3rd Configuration using buses with small RPI of the proposed method and using the same size of capacitors. Bus 1, 4, 6 and 9 are chosen, since they have small RPI. Each of them are injected 52.5 MVar. Figure 10 shows the voltage profile of the South Sulawesi system after the injection of capacitors based on 3rd configuration. As can be seen, misplacement of capacitor injection can also increase voltage higher than 1.05 pu, which cause over voltages. Improper placement of these capacitor can lead system out of voltage stability limit which degrade system quality. Eigenvalue obtained is 1.7099. Losses of active power and reactive power are 23.021 MW and 32.687 MVar, respectively. This configuration generate higher reactive power losses and lower stability than proposed method. Figure 10. Voltage profile of 3rd configuration VI. CONCLUSIONS Conclusions that can be taken from this research are: 1. Based on simulation results, before capacitors installation at peak load, some areas are under voltage and this condition potentially interfere system stability. These bus are buses 12 13, 14, 17, 18, 19, 20, 21, 26, 27 and 28. 4 Based on proposed method bus 14, 13, 17 and 20 are the best buses for reactive power injection. 2. By using reactive participation index, it is successfully choose the right buses for capacitors placement to improve voltage profile compared to 3 other configurations. 3. Method used in this paper demonstrates its strength to overcome problem in voltage stability. By using the method, voltage profile improved with minimum injection of capacitor in size and number. Voltage profile is align in 0.95<V<1.05 pu. REFERENCES [1] A. Arief, "Under Voltage Load Shedding Using Trajectory Sensitivity Analysis Considering Dynamic Loads," Universal Journal of Electrical and Electronic Engineering, vol. 2, No. 3, pp. 118 - 123, DOI: 10.13189/ujeee.2014.020304, 2014. [2] A. Arief, et al., "Under voltage load shedding in power systems with wind turbine-driven doubly fed induction generators," Electric Power Systems Research, vol. 96, pp. 91-100, DOI: 10.1016/j.epsr.2012.10.013, 2013. [3] Z. Y. Dong and P. Zhang, Emerging Techniques in Power System Analysis: Springer, 2009. [4] A. Arief, et al., "Under voltage load shedding incorporating bus participation factor," in 2010 Conference Proceedings IPEC, 2010, pp. 561-566. 0.9 0.92 0.94 0.96 0.98 1 1.02 1.04 1.06 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 VoltageMagnitude(pu) Bus Voltage Stability Limit Pu Upper Limit
  • 9. Allocation of Reactive Power Compensation Devices to Improve Voltage Profile Using Reactive DOI: 10.9790/1676-10418290 www.iosrjournals.org 90 | Page [5] M. Bachtiar Nappu, et al., "Transmission management for congested power system: A review of concepts, technical challenges and development of a new methodology," Renewable and Sustainable Energy Reviews, vol. 38, pp. 572- 580, DOI:10.1016/j.rser.2014.05.089, 2014. [6] M. B. Nappu, et al., "Market power implication on congested power system: A case study of financial withheld strategy," International Journal of Electrical Power & Energy Systems, vol. 47, pp. 408-415, 2013. [7] B. Gao, et al., "Voltage stability evaluation using modal analysis," IEEE Transactions on Power Systems, vol. 7, pp. 1529-1542, 1992. [8] C. Sharma and M. G. Ganness, "Determination of Power System Voltage Stability Using Modal Analysis," in International Conference on Power Engineering, Energy and Electrical Drives, POWERENG, 2007, pp. 381-387. [9] S. Devi and M. Geethanjali, "Optimal location and sizing of Distribution Static Synchronous Series Compensator using Particle Swarm Optimization," International Journal of Electrical Power & Energy Systems, vol. 62, pp. 646- 653, 2014. [10] A. A. El-Fergany, "Involvement of cost savings and voltage stability indices in optimal capacitor allocation in radial distribution networks using artificial bee colony algorithm," International Journal of Electrical Power & Energy Systems, vol. 62, pp. 608-616, 2014. [11] I. K. Kiran and J. Laxmi.A, "Shunt Versus Series Compensation in the Improvement of Power System Performance," IndianJournals.com, vol. Volume 2, No 1, 2010. [12] C.-S. Lee, et al., "Capacitor placement of distribution systems using particle swarm optimization approaches," International Journal of Electrical Power & Energy Systems, vol. 64, pp. 839-851, 2015. [13] A. Zeinalzadeh, et al., "Optimal multi objective placement and sizing of multiple DGs and shunt capacitor banks simultaneously considering load uncertainty via MOPSO approach," International Journal of Electrical Power & Energy Systems, vol. 67, pp. 336-349, 2015. [14] V. U. Reddy, et al., "Capacitor placement for loss reduction in radial distribution network: a two stage approach," Journal of Electrical Engineering, vol. 12, No. 2, pp. 114-119, 2012. [15] O. P. Mahela, et al., "Optimal Capacitor Placement Techniques in Transmission and Distribution Networks to Reduce Line Losses and Voltage Stability Enhancement: A Review," IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE), vol. 3, no. 4, pp. 1-8, 2012. [16] A. Elsheikh, et al., "Optimal capacitor placement and sizing in radial electric power systems," Alexandria Engineering Journal, vol. 53, pp. 809-816, 2014. [17] K. R. Devabalaji, et al., "Optimal location and sizing of capacitor placement in radial distribution system using Bacterial Foraging Optimization Algorithm," International Journal of Electrical Power & Energy Systems, vol. 71, pp. 383-390, 2015. [18] A. A. El-Fergany and A. Y. Abdelaziz, "Capacitor placement for net saving maximization and system stability enhancement in distribution networks using artificial bee colony-based approach," International Journal of Electrical Power & Energy Systems, vol. 54, pp. 235-243, 2014. [19] V. U. Reddy and A. Manoj, "Optimal Capacitor Placement for Loss Reduction in Distribution Systems Using Bat Algorithm," IOSR Journal of Engineering, vol. 2, No. 10, pp. 23-27, 2012. [20] R. MuthuKumar and K. Thanushkodi, "Capacitor Placement and Reconfiguration of Distribution System with Hybrid Fuzzy-Opposition based Differential Evolution Algorithm," IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE), vol. 6, no. 4, pp. 64-69, 2013. [21] M. R. Amin and R. B. Roy, "Determination of Volume of Capacitor Bank for Static VAR Compensator," International Journal of Electrical and Computer Engineering (IJECE), vol. 4, No. 4, August 2014, pp. 512-519, 2014. [22] Mudakir, "Database Sistem Simulasi 2015," AP2B PT. PLN (Persero) Wilayah VIII, Sulselbar2014. [23] P. PLN(Persero), Rencana Usaha Penyediaan Tenaga Listrik PT PLN (Persero) 2013 - 2022, 2013-2022.