International Journal of Innovative Technology and Exploring Engineering (IJITEE)

ISSN: 2278-3075 (Online), Volume-9 Issue-10, August 2020

Evaluation of Distributed Generation Impact on

Reliability of a Distribution System using
DIgSILENT PowerFactory
Ravishankar B S, Vijayendra V K, K. T. Veeramanju

Abstract: As an effective supplement to the centralized fossil About 65-70% of the losses occurring in the power
fuel based traditional generation, Distributed Generation (DG) system can be attributed to distribution system losses [30].
has become an effective alternative choice and has been rapidly In order to reduce these losses, DGs integrated to the
increasing since past few years due to growing demand for distribution system will be a good option. DGs may be based
electricity and the new policies of governing bodies for usage of on renewable energy or non-renewable energy technologies.
green energy. In overall power system, distribution systems are
However, with the increased environmental concerns,
more vulnerable to faults and reliability aspects of such systems
becomes an important issue. With higher penetration of DG into
renewable energy based DGs are gaining more importance.
the distribution network, it will be necessary to study the impact of Renewable energy based DGs have many techno-economical
such generation on the various aspects of distribution system. and environmental advantages. Due to increased customers
Thus, increase in rate of penetration DGs into the distribution demand for reliable and quality power supply, evaluation of
system on one side and increased faults in distribution network on the impact of DG integration to improve performance of the
another side, will make the study of impact of DG integration on system, especially reliability and reduction of losses is
distribution system reliability an interesting topic of research. The gaining more importance in the present distribution system
present work focuses on evaluation of impacts of integration of operating scenario. Improvement in reliability and reduction
such DGs on reliability of local distribution network, typically in
in losses can be achieved only by optimal selection,
an urban scenario By using the simulation method using
DIgSILENT PowerFactory software, the impacts of integration of
placement and sizing of DGs. This will in turn have added
DG in terms of enhancement in distribution system reliability benefit of improved voltage profile, better power quality,
indices and reduction in system losses for different scenarios are optimum system loadability, enhanced system security. This
studied and presented in this paper. Based on the simulation will also lead to reduced capital investments, repair and
results obtained and after analysis of the distribution system, maintenance costs, fuel cost for conventional units and
overall results are summarized by focusing on the installation of operational costs. Renewable energy based DGs will have
suitable capacity of DG and the location of DG which are advantage of no-emissions, free availability and so on. With
important factors affecting the system losses and system reliability increase in DG, the integration of such DGs into the
indices.
distribution networks has to be taken care and it is necessary
Keywords: Distributed Generation (DG), RBTS, Simulation, to study the impacts of DG integration in terms of reliability
DIgSILENT PowerFactory. Radial distribution system. and system losses. Otherwise, if DGs are not properly
installed at proper locations, it may lead various problems
I. INTRODUCTION viz. increased losses, protection co-ordination problem,
power quality issues. This problem of optimal selection,
T he Distribution systems which were passive in nature sizing and siting of DGs has been dealt with in literature
using several techniques. Analytical techniques are suitable
earlier with uni-directional power flows are transforming into
for small systems and not performing well for complex
active distribution systems with bidirectional power flows in
systems. Various meta-heuristic techniques are developed for
the present scenario due to gradual increase in integration of
large and complex system which provides good results. Many
small-scale DGs [1]. Integration of DG into the distribution
simulation techniques are adopted by using different power
system results in increased system availability and improved
system simulation software which also provides good output
reliability of the system. Also, there is possibility of increased
indicators to arrive at suitable conclusions based on the
system complexity and problem of increased losses due to
simulation results. Simulation studies are carried out using
improper placement, sizing of DGs in distribution networks.
Neplan software in [1], [24], [26] using ETAP in [3], [8],
Revised Manuscript Received on August 30, 2020. [12], [16], [17], [18], [19], [21] DigSILENT PowerFactory in
* Correspondence Author [7], [14], [25], [28]. [29], using MiPower in [6],[15], using
Mr. Ravishankar B. S., Assistant Professor, Department of Electrical & DISREL in [30] and using MATLAB in other works. Real
Electronics Engineering, JSS Science & Technology University, Mysuru, time feeder data has been considered in [4], [13], [14], [17],
Karnataka, India. E-mail: ravishankarbs@sjce.ac.in.
Mr. Vijayendra V K, PG-Scholar, Department of Electrical & [24], [27] for case studies. Along with the objective of
Electronics Engineering, JSS Science & Technology University, Mysuru, improvement of reliability of the system, reduction in system
Karnataka, India. E-mail: vijayendravk@gmail.com. loss and improvement in voltage profile has been considered
Dr. K T Veeramanju, Professor, Department of Electrical & Electronics as the objective in [2], [3], [4], [6], [8], [9], [10], [11], [15],
Engineering, JSS Science & Technology University, Mysuru, Karnataka,
India. E-mail: veeramanju.kalyan@gmail.com. [20], [25]. Concept of DSM has been considered in [7], [22].
Solar PV has been considered
© The Authors. Published by Blue Eyes Intelligence Engineering and as choice for DG in most of
Sciences Publication (BEIESP). This is an open access article under the CC the literature.
BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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DOI: 10.35940/ijitee.J7586.0891020
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Evaluation of Distributed Generation Impact on Reliability of a Distribution System using DIgSILENT PowerFactory

Energy storage has been considered in [1], micro hydro in and energy oriented reliability indices are required in
[13], Diesel generator in [26] and wind in [7], [9], [12], [13], addition to basic indices. These system oriented indices,
[15], [18], [22], [26]. namely System Average Interruption Frequency Index
This present work addresses to assess the reliability of (SAIFI), System Average Interruption Duration Index
distribution system in presence of DGs for RBTS test (SAIDI), Customer Average Interruption Duration Index
distribution system and practical system of 11kV feeders (CAIDI), Average System Availability Index (ASAI),
emanating from 66/11 kV Hebbal sub-station coming under Average System Unavailability Index (ASUI) considered in
Karnataka Power Transmission Corporation Limited the present work are represented by (4)-(8) and energy
(KPTCL), Mysuru and distribution feeders coming under the oriented indices namely Average System Interruption
jurisdiction of Chamundeshwari Electricity Supply Company
Frequency Index (ASIFI), Average System Interruption
(CESC), Mysuru. Both test system and practical system
Duration Index (ASIDI) and Energy Not Supplied (ENS) are
feeders are modeled using DIgSILENT PowerFactory.
represented by the (9)-(11).
Failure rates are taken as per the test system values.
Reliability indices of the test system and practical system are Sum of no. of cust interrutpions  i Ni
SAIFI = = f/Ca…... (4)
determined for different cases of DG integration. Simulation
results are summarized by focusing on the installation of Total no. of cust served  Ni
suitable capacity of DGs and the location of DGs which are
Sum of cust interrutpion duration  U i Ni
important factors affecting the system losses and system SAIDI = = h/Ca.. (5)
reliability indices Total no. of cust served  Ni
This paper has been organized into IV sections. This
introduction section is followed by section-II which provides Sum of cust interrutpion duration  U i Ni
CAIDI = = hrs….……..
overview of Reliability analysis of a distribution system; Sum of no. of cust interrutpions  i Ni
section-III provides the problem formulation for DG
integration, section-IV provides both test system and (6)
practical system data, simulation and analysis for difference Customer hours of available service  Ni x8760 −  Ui Ni
ASAI = = .. (7)
cases, section-V deals with results and discussion and Customer hours demanded  Ni x8760
section-VI provides conclusions based on case study results.
ASUI = 1-ASAI………………………………………… (8)
II. RELIABILITY ANALYSIS OF A DISTRIBUTION Sum of connectedkVA of load interrupted
SYSTEM ASIFI = …….….. (9)
TotalonnectedkVA served
This work mainly concentrates on radial distribution Sum of connectedkVA durationsof load interrupted
system. IEEE standard 1366 provides a set of indices for ASIDI = (10)
determining reliability of power distribution system. Data TotalonnectedkVA served
related to reliability for set of power system components, ENS =  La xUi ………..……………………………. (11)
load points and customers are statistically interpreted using
reliability indices. These indices are classified into load point Where, λi is the failure rate of the components i =
indices and system indices [18]. 1,2,3……N Where Ni is the number of customers at the load
point i = 1,2,3…….N. Ui is the annual unavailability at the
A. Basic load point reliability indices load point i = 1,2,3…….N.
Average failure rate (λs), average outage time (rs) and Total energy demand in the period of interest
average annual unavailability (Us) are the basic elementary La =
indices called load point indices [5]. These indices denote the Period of interest
average values. Average failure rate provide information
regarding the number of failures happening at load point for III. PROBLEM FORMULATION
the specific time interval. Average failure time interval at the With higher penetration of DGs, distribution system are
load point is expressed by average outage time. Average becoming similar to transmission systems where load and
supply outage at the load point for a period of one year is generation node points are mixed and reliability of such
termed as average annual outage time. systems are becoming important. Evaluation of the DG
Depending on failure rates for each system components, integration impact on reliability of distribution system is
repair times and feeder configurations, these basic indices are important from both utility and consumer point of view.
expressed using the following equations: This present paper addresses to evaluate the reliability of
 s =  i f/yr ………….…..(1) distribution system in presence of DGs by simulation method
U s =  i  i hrs/yr…………(2)
using DIgSILENT PowerFactory. RBTS test distribution
system and practical system pertaining to Hebbal sub-station

s =
Us
=
  i i
hrs….….(3)
is modeled using DIgSILENT PowerFactory. Reliability
indices of the test system are determined for different cases of
s i DG integration.
Where, λi and ri are the failure rate and the average repair
time of component-i, and Ui is the annual unavailability at the
load point i.
B. System reliability indices
For complete understanding of the system, system oriented

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DOI: 10.35940/ijitee.J7586.0891020
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382 and Sciences Publication
 International Journal of Innovative Technology and Exploring Engineering (IJITEE)
ISSN: 2278-3075 (Online), Volume-9 Issue-10, August 2020

The cases considered are: i) Without DGs (Base Case), ii) points and loads are shown lumped at 415V level. For
With one DG (Synchronous / PV) to determine optimal size, industrial bulk consumers, loads are shown lumped at 11kV
iii) With two DGs (PV / Synchronous DG) to determine level itself. Overall system peak load is 20MW and average
optimal size, iv) DGs at different distance from the source to load is 12.29MW with total of 1908 customers at 22 load
determine optimal location. points Feeder-wise peak and average loads considered for
The objective in all the case studies above is to reduce the RBTS is show in the table-I. The defined average load is
system losses and to improve the reliability indices of the based on the fact that this will be value at the load point due to
given system. The impacts of DG integration on reliability diversity factor between customers and normal load
variations throughout the day and through the year [35].
are analyzed through simulation method using DIgSILENT
Power Factory software. The system losses and the reliability Table- I: Feeder-wise data for RBTS Bus2 system
indices obtained from the above case studies are used to Line Avg No. of
Feeder Load Peak load
illustrate the impact of DG integration and in improving the No.
length
Points (in MW)
load (in customer
reliability of the distribution system. Step by step in km MW) s
methodology adopted for the carrying out the work is: i) F1 2.85 LP1-7 5.934 3.645 652
Modeling of RBTS test distribution system and practical F2 2.35 LP8-9 3.5 2.15 2
Hebbal system using DIgSILENT PowerFactory software, ii) F3 2.9 LP10-15 5.046 3.106 632
Determination of the real power loss in the system without F4 2.9 LP16-22 5.521 3.39 622
DG integration, iii) Determination of the reliability indices Total 22 20.001 12.291 1908
of the test system using reliability analysis tool without DG
integration, iv) Carrying out case studies with one DG and
two DGs and determine the power losses and reliability Line lengths, transformer capacities, load data are considered
indices, v) Carrying out case studies by placing the DGs at as per the RBTS data in [35]. The reliability data considered
different distances from the source to determine the optimal for 33kV and 11kV system components are shown in the
location, vi) Carrying out case studies to determine optimal table-II.
size of the DG for individual feeders of test system.vii) Table- II: Reliability relate data for 33kV and 11kV
comparison of results for test and practical system. Flow system components
chart showing the proposed methodology is shown in the 33/11 kV Transformers
fig.1. Active Failure Rate in f/yr.km 0.015
Start
Repair time in hrs 15
Modeling of test system using 11 / 0.433 kV Distribution transformer
DIgSILENT PowerFactory
Active Failure Rate in f/yr.km
0.015
Load flow using modified NR method
without considering DG integration Repair time in hrs 200
11 kV lines
Ploss (without DG) = P(Gen) – P(Load)
Active Failure Rate in f/yr.km 0.065
Determine the reliability Indices (SAIDI, SAIFI, ASAI, ASUI, Repair time in hrs 5
ENS, ASIFI & ASIDI) using Reliability analysis tool

The line parameters and transformer parameters

Determine the DG location using load flow
& reliability analysis results considered are shown in the table-III and table-IV
Optimal sizing of single DG using load flow
respectively.
and losses.
Table- III: Line parameters for 11 kV OH lines
Load flow analysis after DG integration
Ploss (with DG) = P(Gen) – P(Load)
Conductor type Coyote Rabbit
Determine the reliability Indices with DG integration using
Reliability analysis tool
Rated Voltage (in kV) 11 11

Ploss (with DG) <= No

Rated Current (in A) 386 183
Ploss (with out DG)
Resistance (Ω/km) 0.248 0.616
Yes Reactance (Ω/km) 0.337 0.366
No RI (with DG) <=
RI(without DG)
Table- IV: Transformer parameters for RBTS
Yes
End Parameters Value
Rated Power 2 MVA
Fig. 1.Flow chart showing the proposed methodology. Rated Voltage 11/0.433kV
Vector group Dyn11
% impedance 6%
IV. SYSTEM DATA AND ANALYSIS
B. Hebbal practical system data
A. RBTS system data The practical system identified for study is 66/11 kV
RBTS bus2 system is considered in this work. RBTS Hebbal Sub-station (SS) coming under the jurisdiction of
KPTCL, Mysuru.
Bus2 system consists of 4 numbers of 11 kV feeders (F1-F4)
with a total of 22 load points with voltage level of 11 kV.
11/0.415kV distribution transformers are modeled for
residential, commercial and Government installation load

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DOI: 10.35940/ijitee.J7586.0891020
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383 and Sciences Publication
Evaluation of Distributed Generation Impact on Reliability of a Distribution System using DIgSILENT PowerFactory

The 66/11 kV Hebbal SS is fed from 66 kV transmission condition, DG is connected to distribution network with a
line emanating from upstream 220 kV Hootagally Receiving circuit breaker iii) It is assumed that, the operation of the
Station (RS). The upstream network has been modeled as breaker is 100% reliable and it operates in case of any fault in
grid for analysis purpose Modeling and Simulation 3 Nos. of the system and isolates the faulty portion so that power
11 kV Feeders viz. F1-HPCL, F2-Hebbal and F4-Birla which supply is available for the other customers of the healthy
connected to 11kV Bank-1 at 66/11 kV Hebbal SS has been portion of the system, iv) Either a synchronous DG (for 1-DG
considered for practical system study. 11kV Bank-1 and studies) or PV-DG with synchronous-DG (for 2-DG studies)
above 11 kV feeders are connected to 66/11 kV, 12.5 MVA is considered for case studies.
Transformer-1 at the SS.Line lengths, transformer capacities, The RBTS system and Hebbal feeder-1 system modeled
load data are considered as per the actual field data collected. using the DIgSILENT PowerFactory is as shown in the fig.2
The line parameters are as per table-3 and transformer and fig.3 respectively.
parameters considered are as per table-V.
Table- V: Transformer parameters for Hebbal
System
Parameters Values

Rated Power (in kVA) 63 100 250 500

Rated Voltage 11/0.433kV
Vector group Dyn11 Dyn11 Dyn11 Dyn11

% impedance 4.5% 4.9% 5% 6%

The reliability data considered for 66kV and 11kV system

components are shown in the table-VI.
Table- VI: Reliability data for 66kV and 11kV system
components of Hebbal system
66/11 kV Transformers

Active Failure Rate in f/yr.km 0.015

Repair time in hrs 15

11 / 0.433 kV Distribution transformer

Active Failure Rate in f/yr.km 0.015

Repair time in hrs 200

11 kV lines
Active Failure Rate in f/yr.km 0.065
Repair time in hrs 5

Few assumptions are made for modeling the system and

to carry out the load flow studies and reliability studies using Fig. 2.RBTS Bus2 system modeled using PowerFactory.
DIgSILENT PowerFactory. Assumptions for load flow
studies are i) Network above 33kV voltage for RBTS and 66
kV for practical system is represented by grid, ii) Modeling is
limited and truncated at 415V level, iii) DTCs (Distribution
Transformers Centers) i.e. 11/0.415kV transformers are
modeled and all the loads are assumed to be lumped at
distribution transformer LV (Low Voltage) side i.e., at 415V
level, iv) Residential, commercial and government
installation loads are metered on the LV side and the
transformer belongs to utility and hence included in the
analysis. The bulk user loads are metered on the HV (High
Voltage) side and the transformer belongs to customer and
hence not considered for analysis, v) Loads are placed on 11
kV bus itself for small users, vi) All the 11kV lines are
assumed to be overhead with Coyote conductor for trunk
lines and Rabbit conductor for spur lines, vii) Modified
Newton-Raphson method is used for carrying out load flow
which provides acceptable results for distribution systems.
Assumptions for reliability studies are i) The feeder operation
is considered to be radial mode with normally open
sectionalizers if provided, ii) This work focuses on DG as a
source rather than technology and is considere that DG is
used with its full capacity. In order to isolate the DG in fault

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 International Journal of Innovative Technology and Exploring Engineering (IJITEE)
ISSN: 2278-3075 (Online), Volume-9 Issue-10, August 2020

D. Analysis with single DG

Only Feeder-1 is considered for study with all other
feeders being out of service. Load flow analysis and
reliability evaluation has been carried out for base case i.e.
without any DGs connected to the feeder and for different
scenarios with DGs connected. In the base case, only the
system components on feeder-1 are considered without any
DGs. The system losses and reliability indices for RBTS
feeder-1 base-case are presented in table-VII.
Table- VII: Base case loss & reliability indices for
RBTS feeder-1
Parameters Base case (No DG)

MW Losses in MW 0.09

SAIFI (1/Ca) 0.13041

SAIDI (h/Ca) 3.577
CAIDI (hrs) 27.429
ASAI 0.999592
ASUI 0.000408
ENS (MWh/a) 13.679
ASIFI (1/a) 0.165572
ASIDI (h/a) 3.752859

Initially, 1-DG with a capacity of 500 kW is placed at the

tail end of the main trunk line. System losses and reliability
indices are determined. Gradually, the capacity of DG is
increased in steps of 500kW such that beyond a certain
capacity of DG, there will be increase in the system losses.
Fig. 3. Hebbal system modeled using PowerFactory The system losses and reliability indices for placing different
capacities of DG at tail end are presented in the table-VIII.
C. Steps for carrying out the analysis
For carrying out case studies for individual feeders, Table- VIII: Loss & Reliability indices for Feeder-1
(With 1-DG at tail end).
following steps are adopted. i) For base case study, the
existing system without any DG interconnections is %age
Parame 1-DG
Base 1-DG on 1-DG on impro
considered, ii) For studying the impact of DG integration on ters \ on F1
case (No F1 F1 vemen
DG (1000
the feeder, case studies are performed with different capacity
DG)
kW)
(2000kW) (2370kW) t w.r.t
capacities of DGs at different locations on the feeder, iii) base
Initially, 1-DG with a capacity of approximately 15% of the Loss in
0.09 0.07 0.06 0.07 33.33
MW
loading is considered and gradually increased in steps 15%, 0.12588
iv) Single DG will be placed at the tail end of the main trunk SAIFI 0.13041 0.125568 0.108754 16.61
3
line initially which will be considered as the tail end case or SAIDI 3.577 3.554 3.553 3.469 3.02
100% of the line length case, v) Initially for lower capacity of 0.99959 0.99959
ASAI 0.999594 0.999604 0.001
DGs, there will be reduction in system losses along with 2 4
0.00040 0.00040
improvement in reliability.vi) Gradually, the capacity of DG ASUI
8 5
0.000405 0.000395 3.04
is increased such that beyond a certain capacity of DG, there ENS 13.679 12.94 12.359 12.186 10.91
will be increase in the system losses. This capacity of the DG ASIFI
0.16557 0.12499
0.093108 0.083636 49.49
is considered to be the optimal capacity for the feeder beyond 2 1
3.75285 3.54995
which there is increase in the system losses, vii) Case studies ASIDI
9 7
3.390541 3.343181 10.92
with different capacities of DGs are repeated for DG
placement at 75%, 50% and 25% of line lengths for each From the above, the following observations are noted.
feeder, viii) Case studies are also repeated with 2-DGs There is improvement in the reliability with placement of
considered at different locations i.e. Both at the tail end, 1-DG at tail end. Losses will decrease to an extent of 33%
1-DG at tail end and 1-DG at 75% line length, 1-DG at tail with placement of DG capacity up to 2370kW. For DG
end and 1-DG at 50% line length, 1-DG at tail end and 1-DG capacity ≥2370kW, there will be increase in system losses.
at 25% line length, 1-DG at 75% line length and 1-DG at 50%
line length, viii) The reliability indices are also determined
for different capacities of DG placement to measure and
quantify the effect on the system performance.

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Evaluation of Distributed Generation Impact on Reliability of a Distribution System using DIgSILENT PowerFactory

Hence optimal DC capacity can be considered as 2370 0.0004

ASUI 0.000405 0.000405 0.000389 4.63
08
kW i.e. around 65% of loading on the feeder. Further, the ENS 13.679 12.947 12.352 12.091 11.61
system losses and reliability indices are determined by 0.1655
ASIFI 0.125383 0.092745 0.078428 52.63
placing different capacities of 1-DG at 75%, 50% and 25% of 72
the line lengths. The bar chart showing percentage loss 3.7528
ASIDI 3.551917 3.388726 3.317139 11.61
59
reduction and percentage improvement in reliability indices
for single DG placed at different locations is shown in the From the above, the following observations are noted: i)
fig.4. When 2 DGs are placed at the tail end, loss reduction is
almost same as that of placing an equal capacity single DG at
tail end. Ii) From loss point of view, combined capacity can
be increased up to 2570kW i.e. 70% of loading when
synchronous DG and PV DG is considered. iii) If both DGs
are synchronous DGs, then the optimal capacity is same as
that of single DG, i.e. 65% of loading. iv) Reliability
improvement in terms of all indices are comparatively much
better than placing an equal capacity single DG.
Further, the system losses and reliability indices are
determined by placing 2-DGs at different locations i.e. 1-DG
at tail end and 1-DG at 75% line length, 1-DG at tail end and
1-DG at 50% line length, 1-DG at 75% line length and 1-DG
Fig. 4. %age loss reduction and %age improvement in at 50% line length, 1-DG at tail end and 1-DG at 25% line
reliability indices for single DG placed at different length. The bar chart showing percentage loss reduction and
locations. percentage improvement in reliability for two DGs placed at
different locations is shown in the fig.5.
Based on the case studies with single DG, following
conclusions are drawn. i) The optimal capacity for maximum
loss reduction would be 2370 kW (i.e about 65-70% of the
loading of the line). Ii) For maximum loss reduction and
reliability improvement, it is optimal to place DG between
75% of line length towards the tail end for lower DG
capacities below optimal, iii) For higher DG capacity, it is
best feasible to place the DG between 50% to 75% of the line
length for better reliability improvement, iv) It is not feasible
to place the DG nearer to the source in view of both higher
losses and poor reliability compared to placing DG away
from the source.
The case studies presented above with single DG for
feeder-1 of RBTS bus2 system are carried out for all the other Fig. 5.%age loss reduction and %age improvement in
RBTS feeders i.e. feeder-2, 3 & 4. Also, the case studies are reliability indices for two DGs placed at different
carried out for all the feeders of practical Hebbal system. locations.

E. Analysis with two DGs Based on the case studies with two DGs, following
conclusions are drawn. i) Reliability will further improve
For carrying out case studies with 2 DGs, initially 2 DGs
(1 synchronous + 1 PV or both synchronous DGs) are placed with 2-DGs when compared to 1-DG placement, ii) For
at the tail end of main trunk line. System losses and reliability maximum loss reduction and reliability improvement, it is
indices are determined. Gradually, the capacity of DG is optimal to place DG between 75% of line length towards the
increased in steps of 500kW such that beyond certain tail end for lower DG capacities below optimal, iii) For
combined DG capacity, there will be increase in the system higher combined DG capacity, it is best feasible to place the
losses. The system losses and reliability indices for placing DGs between 50% to 75% of the line length for better
different capacities of DGs at tail end are presented in the reliability improvement, iv) It is not feasible to place the DGs
table-IX. nearer to the source in view of both higher losses and poor
Table- IX: Loss & Reliability indices for Feeder-1 reliability compared to placing DGs away from the source.
(With 2-DGs at tail end).
Parame %age V. RESULTS AND DISCUSSIONS
Base
ters \ 2DGs 2DGs improv
case 2DGs
DG
(No (500+500)
(1000+10 (1570+10 ement The case studies presented above with two DGs for
capacit 00) 00) w.r.t feeder-1 of RBTS bus2 system are carried out for all the other
DG)
y base
Loss in RBTS feeders i.e. feeder-2, 3 & 4.
0.09 0.07 0.06 0.07 33.33
MW
0.1304 Also, the case studies are
SAIFI 0.125887 0.125564 0.097326 25.37
10
SAIDI 3.577 3.554 3.553 3.412 4.61
carried out for all the feeders
0.9995 of practical Hebbal system.
ASAI 0.999594 0.999594 0.999610 0.002
91

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386 and Sciences Publication
 International Journal of Innovative Technology and Exploring Engineering (IJITEE)
ISSN: 2278-3075 (Online), Volume-9 Issue-10, August 2020

The percentage loss reduction, optimal capacity of DG Table- XI: Comparison of %age loss reduction,
than can be connected, percentage improvement in reliability optimal DG capacity and %age improvement in
in terms of SAIFI, SAIDI, ENS, ASIFI and ASIDI for RBTS reliability for RBTS Bus2 feeders & Hebbal system
bus2 system feeders and Hebbal feeders with single DG are feeders with 2-DGs.
Paramet RBTS Bus2 system Hebbal System
presented in the table-X. ers /
Feeders F1 F3 F4 F2 F1 F2 F4
Table- X: Comparison of %age loss reduction, optimal Optimal 70.0 90.0 60.0
DG capacity and %age improvement in reliability for 72.00 80.00 50.00 77.00
capacity 0 0 0
RBTS Bus2 feeders & Hebbal system feeders with 1-DG. Loss
Paramet 33.3 50.0 60.0
RBTS Bus2 system Hebbal System reductio 37.50 44.44 20.00 66.67
ers / 3 0 0
n
Feeders F1 F3 F4 F2 F1 F2 F4 25.3 62.7 55.5
Optimal SAIFI 29.87 52.81 24.05 79.00
65.0 66.0 74.0 80.0 55.0 50 74 7 6 9
capacity 62.7 16.4
Loss 66. SAIDI 4.61 5.94 10.47 10.65 31.55
33.3 37.5 44.4 50.0 40.0 20 0 7
reduction 6 11.6 65.0 35.0
24. 76. ENS 12.24 14.51 5.41 38.34
SAIFI 16.6 23.4 47.8 57.8 60.7 1 5 8
0 3 52.6 65.0 56.1
10. 30. ASIFI 58.41 60.43 12.59 82.86
SAIDI 3.0 4.6 9.4 57.9 18.0 3 4 5
6 5 11.6 65.0 35.1
5.4 37. ASIDI 12.24 14.51 5.41 38.33
ENS 10.9 11.5 14.1 60.3 32.6 1 4 0
1 7
12. 81.
ASIFI 49.4 55.2 58.8 60.4 52.2
6 5
5.4 37.
ASIDI 10.9 11.5 14.1 60.4 32.6
1 7

The above values are represented in the form of bar chart

as shown in the fig.6.

Fig. 7.Optimal capacity, %age loss reduction and %age

improvement in reliability indices w.r.t base case for
RBTS bus2 feeders (with 2-DGs).
From the above results and comparison, following
conclusions are drawn. i) The optimal capacity of DG
connection with 2-DGs may be increased up to 70-84% of
feeder peak loads, ii) Loss reduction with 2-DG
Fig. 6.Optimal capacity, %age loss reduction and %age interconnection will be less than that of 1-DG case and will
improvement in reliability indices w.r.t base case for be in the range of 33-44% normally, iii) SAIFI improvement
RBTS bus2 feeders (with 1-DG). will be between 25-62%, SAIDI between 4-11%, ENS
between 11-15%. ASIFI between 52-60% and ASIDI
From the above results and comparison, following 11-15%, iv) In case of RBTS feeder-2 and Hebbal feeder-4
conclusions are drawn. i) The optimal capacity of DG being predominantly industrial or bulk consumer feeder,
connection with 1-DG may be increased up to 50%-74% of optimal capacity of DG connected can be between 77-90% of
feeder peak loads. This also coincides with the general 2/3 feeder peak. v) For RBTS feeder-2 and Hebbal feeder-4,
rule. ii) Loss reduction with 1-DG interconnection will be in reliability improvement will be much higher than normal
the range of 20-44% normally, iii) SAIFI improvement will feeders.
be between 16-48%, SAIDI between 3-10%, ENS between The actual value of indices depends on lots of factors such
10-15%. as, location of placing the DGs, length of the feeder, number
ASIFI between 49-60% and ASIDI 10-15%, iv) In case of of customers connected to each load points which is different
RBTS feeder-2 and Hebbal feeder-4 which are for different feeders and network configuration. Hence there
predominantly industrial or bulk consumer feeders, optimal will be variation in the indices for different feeders due to
capacity of DG connected can be between up to 74-80% of above factors.
feeder peak, v) For RBTS feeder-2 and Hebbal feeder-4,
reliability improvement will be much higher than normal
feeders.
Similarly, the percentage loss reduction, optimal capacity
of DG that can be connected, percentage improvement in
reliability in terms of SAIFI, SAIDI, ENS, ASIFI and ASIDI
for RBTS and Hebbal system feeders for two DG case are
presented in the table-XI and the bar chart in the fig.7.

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Evaluation of Distributed Generation Impact on Reliability of a Distribution System using DIgSILENT PowerFactory

VI. CONCLUSIONS 7. Mohamed Mostafa, Mostafa Elshahed, Mohamed S.Esobki, “The

Impact of Distributed Energy Resources on the Reliability of Smart
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Software. Simulations have been performed for individual SMART-2018, IEEE conference ID: 44078, International conference
on system modeling & advancement in research trends,
feeders of RBTS test system and practical Hebbal system November-2018.
feeders. Based on the study results obtained from simulations 9. J.Senthil kumar, P.Venkatesh, S.Charles Raja, J.Jeslin Drusila
and analysis of the distribution system, overall results are Nesamlar, C.Palanichamy, “Reliability Enhancement of Small and
Medium Distribution System with Renewable Genertions and
summarized by focusing on the installation of suitable Reclosers”, IEEE, 2018.
capacity of DG and the location of DG which are important 10. Vikas Singh Bhadoria, Nidhi Singal Pal, Vivek Shrivastava and Shiva
factors affecting the system losses and system reliability Pujan Jaiswal, “Reliability Improvement of Distribution system by
Optimal Sitting and Sizing of Disperse Generation”, International
indices Journal of Reliability, Quality and Safety Engineering, Vol.2, No.6
Summary of results for individual feeder studies are as (2017) 1740006.
follows, i) the optimal capacity for maximum loss reduction 11. Juan Li, Honglian Zhou, Erbiao Zhou, Jingjie Xue, Zifa Liu and
Xuyang Wang, “Comprehensive Evaluation of Impacts of High
with single DG would be 50-74% of the loading of the line. Penetration of Distributed Generation Integration in Distribution
This is in line with 2/3 rule for the radial feeders. This can be Network, IEEE, 2017.
improved up to 70-84% in case of 2 DGs, ii) Loss reduction 12. Sanaullaha Ahmad, Azzam Ul Asar, Sana Sardar and Babar Noor,
with 2-DG interconnection will be less than that of 1-DG “Impact of Distributed Generation on the Reliability of Local
Distribution System”, International Journal of Advanced Computer
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compared to 1-DG placement, iv). For maximum loss 13. Hadi Suyono, Wiono, Rini Nur Hasanah and Syamsu Dhuba, “Power
reduction and reliability improvement, it is optimal to place Distribution System Reliability Improvement due to Injection of
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DG between 75% of line length towards the tail end for lower 14. A.Ngaopitakkul, C.Jettanasen, “The Effects of Multi-Distributed
DG capacities below optimal, v) For higher DG capacity, loss Generator on Distribution System Reliability”, IEEE, 2017.
reduction is much better in case of placing DG at 50% line 15. M.R.Siddappaji, Dr.K.Thippeswamy, “Reliability Indices Evaluation
and Optimal Placement of Distributed Generation for Loss Reduction
length. Hence, it is best feasible to place the DG between in Distribution System by using Fast Decoupled Method”,
50% to 75% of the line length for better reliability International Conference on Energy, Communication, Data Analytics
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16. K. Prakash, F. R. Islam, K. A. Mamun, A. Lallu and M. Cirrincione,
the source in view of both higher losses and poor reliability “Reliability of Power Distribution Networks With Renewable Energy
compared to placing DGs away from the source. These Sources”, IEEE, 2017.
simulation results will provide the network operators a good 17. Fabian C.Oreke, D.C Idoniboyeobu, “Reliability Assessment of
Electrical Energy Distribution System – A cas study of Port Harcourt
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for interconnections. Simulation results have demonstrated “Analyzing Distributed Generation Impact on the Reliability of
Electric Distribution Network”, International Journal of Advanced
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considering DG placement in the distribution system. The 19. Ulas Eminoglu, Ridvan Uyan, “Reliability Analyses of Electrical
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ACKNOWLEDGMENT 21. V.S.S.Sailaja, Dr.P.V.N.Prasad, “Determination of Optimal
Distributed Generation Size for Losses, Protection Co-Ordination and
The authors thank Dr. M S Shashikala, Professor & Reliability Evaluation Using ETAP”, Biennial International
Head, Department of E&EE, JSS Science & Technology Conference on Power and Energy Systems:Towards Sustainable
University, Mysuru for her valuable inputs and support. Energy (PESTSE), 2016.
22. Maad Al Owaifeer, Mohammad AlMuhaini, “Reliability Analysis of
Distribution Systems with Hybrid Renewable Energy and Demand
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 International Journal of Innovative Technology and Exploring Engineering (IJITEE)
ISSN: 2278-3075 (Online), Volume-9 Issue-10, August 2020

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AUTHORS PROFILE
Mr. Ravishankar B. S. is working as Assistant
Professor in the Department of Electrical &
Electronics Engineering. He obtained his B.E. and
M.Tech. Degrees from Visveswaraiah Technology
University. His research interests are in the field of
Applications in Power Systems, Distributed
generation and reliability of Distribution systems.

Mr.Vijayendra V K is a PG-scholar pursuing M.Tech

in Energy Systems & Management at JSS S&T
University. He obtained his B.E degree from
Visveswaraiah Technology University.

Dr. K. T. Veeramanju is working as Professor in the

Department of Electrical & Electronics Engineering. He
graduated from University of Mysore. He obtained his
M.E. degree from Indian Institute of Science,
Bangalore, and Ph.D. from Kuvempu University. He
has been guiding several graduate, post-graduate and
research candidates.

Retrieval Number: J75860891020/2020©BEIESP

Published By:
DOI: 10.35940/ijitee.J7586.0891020
Blue Eyes Intelligence Engineering
Journal Website: www.ijitee.org
389 and Sciences Publication