This document is a thesis proposal by S. Kaveripriya on optimally allocating distributed energy resources (DERs) in a distribution system considering electric vehicles (EVs). The objectives are to minimize power losses. The methodology uses loss sensitivity factor and grasshopper optimization algorithm to determine optimal DER locations and sizes throughout the day for different EV charging patterns. Various charging patterns are analyzed to find the best approach for minimizing power losses. The results show smart charging EVs along with optimally placed DERs further reduces power losses compared to other cases.

1. NAME : KAVERIPRIYA. S
APPLICATION NO:
e4783c21edcf11e98f81cdb80e4aff2f
10/30/2019 1

2. OPTIMAL ALLOCATION OF DERs IN
DISTRIBUTION SYSTEM IN PRESENCE OF
ELECTRIC VEHICLES
by
S. Kaveripriya
(120047007)
II- M. Tech Power system
PROJECT GUIDE
Dr. Velamuri Suresh
AP/III
School of Electrical and Electronics Engineering
Sastra Deemed to be University
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3. Objective
 Optimal Allocation of DERs in Distribution System
in Presence of Electric Vehicles has been implemented
to
• Minimize power losses
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4. Abstract
• In this project the impact of these electric vehicles on distribution
system performance is studied and a new methodology for
reducing the power loss is implemented.
• This method uses a combined Loss Sensitivity factor and
Grasshopper optimization algorithm to determine the optimal
location and size of Distributed Generation throughout the day.
• Various charging patterns for electric vehicles are analysed and
best possible approach for minimizing the power loss is presented.
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5. Literature Review
TITLE AUTHOR NAME
AND YEAR
INFERENCE
Simultaneous Allocation of
Distributed Generators and
Shunt Capacitors in a
Distribution System
Suresh Kumar Sudabattula,
Kowsalya Muniswamy,
Velamuri Suresh. ecti
transactions on electrical
eng., electronics, and
communications 2019
Identifying the optimal
location and capacity of
DGs and SCs .
To reduce power loss and
improvement in voltage
profile
Grasshopper Optimization
Algorithm to solve
Reconfiguration and DG
placement problem
Mehran sanjabi Asai,
Mojtaba abanch. “ IEEE 4th
international conference on
knowledge based
engineering and innovation
2017.
Determines the optimal
location and size of DGs in
distribution systems to
reduce the active power
loss.
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6. Problem Formulation
Objective Functions:
• The power loss minimization objective is
(1)
Where
(2)
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24
1
min ( )L
i
P i


24
2
( )
1
L
i i i
i
P I R

 

7. Power balance constraint:
• Power balance equation is represented as
(3)
Where PL, Pev, PD are the power loss, power consumed by electric
vehicles and load demand for the ith hour respectively.
Battery storage capacity constraint
• The State of Charge (SOC) of the EV at hour is
(4)
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2
1
4 42
1
[ (( ) ) ( ) ( )]L V DG E
i i
P i P Pi i iP

   
min max
iSOC SOC SOC 

8. Charging/discharging power constraints:
• The charging and discharging limits of EVs should be within the
range of power limits.
(4)
(5)
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max
, , ,
max
, , ,
ch i t ch i
disch i t disch i
p p
p p



9. Loss Sensitivity Factor
• Vulnerable buses for the placement of DGs are identified.
• Active power loss in the Kth line is expressed as
(6)
• Where, Peff[b] is the Total effective active power supplied
beyond the bus b. Now, the LSF can be obtained as
(7)
• The LSF can be calculated for every buses and arrange it in
descending order.
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2 2
2
( [ ] [ ]) [ ])
[ ]
( [ ])
eff eff
lineloss
P b Q b R k
P b
V b


2
(2* [ ])* [ ])[ ]
( [ ])
efflineloss
eff
Q b R kp b
p V b




10. Grasshopper Optimization Algorithm
(GOA)
• To find out the optimal sizes of DGs in DS for each hour
• Update c using the equation
(8)
(9)
(10)
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max min
max
max
( )
C C
C t C t
t

 
max
ij ijs s
1
2 2)
1
2
(
Nb
i i i i
i
ploss
i
K r P Q
f
V





max
i iv v

11. Flow Chart
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12. Electric vehicle design
Model : Chevy volt
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Specifications Ratings
Energy consumed 18.5 KWh
Miles(Km) 53 miles(85)
Soc min & max 0.2 & 0.9
Charging time for one full charge 4 hrs
Distance travelled per day 60km
Charge consumed per km 0.1523kwh
Charge consumed per day 9.138kwh
Usage time 8:00 am to 9:00 am & 4:00 pm to
5:00pm
Charging time (after vehicle returns
home)
3hours

13. Charging and discharging time of
EV
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14. Results
Considering three cases:
• Base case
• With DGs and without EVs
• With DGs and EVs
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15. Load Profile In Base Case
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• Power loss in base case is 210.9983 kW

16. Comparison of power loss and DG size obtained using
GOA
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Method FPA[3] PSO[5] GOA
Base case
PL(kW)
210.99 210.9 210.9983
DG size kW
(location)
936.5(12)
1050(30)
1414(33)
863(16)
925(11)
1200(32)
787.6104(13)
506.514(24)
978.314(31)
PL with
DG(kW)
87.4 103.3 73.8009
% PL reduction 58.55 50.99 65.022

17. With DGs
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18. With DGs and EV
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• Using Dumb charging

19. Smart charging -> charging allows when it has low
demand value
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If PAR<1 Charging
If PAR>1 Charging
not
allowed

20. 10/30/2019 20
• Smart charging

21. • Power loss in Dumb charging & Smart charging
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DUMB TYPE(kW) SMART TYPE(kW)
1251.7723 1248.802

22. 10/30/2019 22
• PL in Dumb & smart type

23. Conclusion
• The proposed method was tested by IEEE 33 bus system.
• EVs are charged using dumb and smart charging methods before
DG placement. The observed result for each case is shown.
• From the comparison point of view, it is obvious that the power
loss is very less in EVs and DGs case in smart charging type.
• Finally, it can be concluded that the optimal allocation of DGs and
EVs reduces the power loss proficiently.
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24. REFERENCES
[1]. Suresh kumar sudabattula, kowsalya M, Velamuri S, “ optimal allocation of
Renewable distributed generators and capacitors in distribution system using
dragonfly algorithm”, International conference on intelligent circuits and
systems 2018.
[2]. Kowsalya M, Sureshkumar Sudabattula. “Distributed Energy Resources
Allocation using Flower Pollination Algorithm in Radial Distribution Systems”.
Renewable Energy Integration with Mini/Microgrid, 2016.
[3]. Moradi MH, Abedini M. “ A combination of genetic and particle swarm
optimization for optimal DG location and sizing in distribution system”. Int J
Electric Power Energy System 2012.
[4]. Velamuri Suresh, Suresh Kumar Sudabattula, Kowsalya Muniswamy.
“Simultaneous Allocation of Distributed Generators and Shunt Capacitors in a
Distribution System”. ecti transactions on electrical eng., electronics, and
comunications 2019
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25. [5]. Sudabattula, Suresh Kumar. "Optimal Allocation of Multiple Distributed
Generators And Shunt Capacitors In Distribution System Using Flower
Pollination Algorithm." IEEE International Conference on Environment and
Electrical Engineering 2019.
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26. THANK YOU
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