**Open Access**-
**Authors :**Aditya Prasad Padhy , Manisha Bhatt -
**Paper ID :**IJERTV9IS070036 -
**Volume & Issue :**Volume 09, Issue 07 (July 2020) -
**Published (First Online):**10-07-2020 -
**ISSN (Online) :**2278-0181 -
**Publisher Name :**IJERT -
**License:**This work is licensed under a Creative Commons Attribution 4.0 International License

#### Optimal Allocation and Size Selection of Dispersed Generation in Radial Distribution System

Aditya Prasad Padhy1

Department of Electrical Engineering Kalinga University,

Raipur, Chhattisgarh, India

Manisha Bhatt2

Department of Electrical Engineering Kalinga University,

Raipur, chhattisgarh, India

AbstractThis paper contributes an analytical technique for the allocation and size selection of dispersed generations (DGs) in radial distributed system (DS)). The proposed technique is computationally expeditious as compared to other existing techniques. The prime objective of this method is to improve voltage profile at each node and reduce total active power loss in 33- bus radial distribution system (RDS). Voltage stability indicator (VSI) is used to find heavily loaded bus in the system. After finding the heavily loaded bus, it is set as optimal location for placement of DG. At this optimal location, the size of DG is determined by using continuous increment of step size (CISS) technique. The effectiveness of the proposed technique is validated from simulated results, by comparing voltage profile, branch current and power losses with the presence and absence of DG.

Keywords: Radial distribution system, dispersed generation, optimal allocation, voltage stability indicator, continous increment of step size.

INTRODUCTION

In recent era, Distribution system (DS) is added as an integral part of power distribution system [1]. The indispensible growth of power demand has increased the role and importance of DS. To encounter the load demand effectively, several changes occur in DS resulting in establishment of complex distribution structure. One of the most important changes in DS structure is invasion of renewable energy in the system. These invasions are known as dispersed generations (DGs). The involvement of DGs in the system affect DS such as: minimization of power loss, improvement of node voltage, and reliability [2]. Thus, DS in accordance with DG is the most prominent part of research domain.

Most of the DS structures are radial in nature in which power flows in a single way from the distribution substation to the consumer [3]. Radial distribution system (RDS) has high R / X ratio, radial structure, and unbalance conditions of load where R and X are the resistance and reactance of line respectively. High R / X ratio leads to high power loss and more voltage drops. In RDS nodes, sudden voltage drops occurs under critical loading conditions. In transmission system, load flow by traditional methodologies has serious

substituted by the available methods for load flow of distribution system as backward forward [4] and direct approach methods [5]. These methods have the advantages of quick convergence and less computation time.

In conventional system, renewable energy invasion has increased in earlier years due to environmental concerns. The conventional generation resources such as thermal, hydro, nuclear, etc. are being penetrated by small-scale generations like photovoltaic (PV), wind, and fuel cell. Although these DGs have very less capacity (Range: 1 KW to 50MW ) compared to other conventional resources, availability of these resources minimize power loss, improves voltage profile [6]. Therefore, DGs are required for optimal sizing and proper location.

Many researchers have found proper solution of optimal sizing and location issues of DGs in DS. Genetic algorithm (GA) is implemented to solve the metaheurstic optimization problem for location and size selection of DG [7]. The technique used in [8] minimizes the fitness function using GA for power loss minimization. In general, constant power models are considered in the DS. But in [9], different load models i.e. residential, commercial and industrial are carried out in RDS while optimally allocating and sizing DGs using GA. A hybridized GA and simulated annealing (SA) algorithm is implemented to compute optimal location of DG in [10]. A mixed GA-particle swarm optimization (GA-PSO) algorithm is mentioned in [11] to find out the optimal location and sizing of DG. In [12, 13], binary PSO and fuzzy embedded GA techniques are proposed for optimal DS planning in presence of DGs. The problem of optimal DS planning with DGs in [14] is treated by means of multi- objective PSO (MOPSO). A MOPSO approach is employed to deal with problem considering different load models in [15]. Artificial bee colony (ABC) algorithm is employed to determine the optimal allocation, size and power factor in order to minimize active power loss [16]. Bacterial foraging algorithm (BFA) is implemented to find the optimal size of DG [17]. In [18], backtracking search algorithm (BSA) is used to assign DGs in DS. An immune algorithm (IA) is formulated to solve the optimal DG planning problem in smart grid [19]. Modified teaching-learning based algorithm

convergence problems due to the high

R / X ratio of the

(MTLBA) is proposed in [20] to compute the optimal

RDS. For proper RDS planning, an efficient load flow technique is required. Hence, these methodologies are

allocation and size of the DG units in RDS.

Although numerous techniques are available for optimal location and sizing of DG, but traditional techniques are still a current interest. Thus, this article presented a voltage

Total power loss

tb

PTL PL , 1

1

(7)

stability indicator (VSI) which indicates the heavily loaded bus. This bus signifies the optimal location of DG placement. After proper allocation of DG, the size of DG is found out by continuous increment of step size (CISS) technique. CISS technique is applied to monitor active and reactive power loss in the IEEE-33bus system.

The paper is organized as follows: In section 2, presents load flow equations and power loss computation for 33 bus RDS. Proposed methodology for optimal allocation and size selection of DG are explained in Section 3, Section 4 discusses the 33 bus test system and simulation results. Finally, conclusion is outlined in section 5.

PROBLEM FORMULATION

A. Radial distribution load flow

In [5] author proposed a simplified and efficient technique

where, tb represents total number of buses.

PROPOSED METHODOLOGY

In distribution system, the node voltage plays a important role to maintain good voltage regulation. Ideally, voltage regulation should be nearly equal to zero, but due to line resistance and reactance there are slight drop in voltage in different nodes of the RDS. To improve voltage profile and reduce line losses, different DGs are used at different power factor [21] according to the requirement as shown in table

Voltage stability node indicator for dg placement

To identify the most sensitive or heavily loaded bus in the system, voltage stability node indicator (VSNI) is used.

From figure 1 branch current is given by

2 P 1 2 Q 1 2

for radial distribution system (RDS). A simplified RDS

I

V 1 2

(8)

shown in Fig. 1.

The equivalent load current injection, corresponding to power injection equations

Active and reactive power loss of the branch between two

I P 1 jQ 1 V 1 *

1, 2,3, .

(1)

nodes is computed by using following equation

For the branch connecting buses 1 to 4, the branch currents

P 2 Q 2

calculated using KCL as

G1 I2 I3 I4

P r

L

L

1 1

V 1 2

()

G2 I3 I4

G3 I4

Branch injection Matrix (BIM) becomes

G1 1 1 1 I2

G2 0 1 1 I3

(2)

(3)

Types of DG

Power factor (P.F)

Power injection ability

Examples

A

P.FDG=0

Only reactive power

Synchronous compensator

B

P.FDG=1

Only active power

Photovoltaic system

C

0<P.FDG<1

Both Active and reactive power

Synchronous generator

D

0<P.FDG<1

Active power and consuming reactive power

Wind turbine

Types of DG

Power factor (P.F)

Power injection ability

Examples

A

P.FDG=0

Only reactive power

Synchronous compensator

B

P.FDG=1

Only active power

Photovoltaic system

C

0<P.FDG<1

Both Active and reactive power

Synchronous generator

D

0<P.FDG<1

Active power and consuming reactive power

Wind turbine

TABLE-1 DG SCENARIO

G3

0 0 1 I4

Bus 1 Bus 2 Bus 3 Bus 4

V1 V2

V3 V4

Substation

G1 G2 G3

P + jQ

P3 + jQ3

P4 + jQ4

2 2

PLoad2 + jQLoad2 PLoad3 + jQLoad3 PLoad4 + jQLoad4

Fig. 1. Single line diagram of radial distribution system

P 1 2 Q 1 2

L

L

In general form,

P x

V 1 2

(10)

G BIMI

Node voltages at different buses calculated by using KVL

V 1 V G Z , 1

(4)

(5)

From the above (9) and (10) the developed VSNI is given by

Power loss in between the buses and 1 is calculated as

2

4 P 1

2 Q 1 2

PL , 1 I * R

(6)

VSNI 1

(11)

The total power loss of the RDS is computed by the summation of all the branch losses, which is represented by

V 1 2

From (11) it can be cleared that 0 VSNI 1 . Further, when the value of the VSNI approaches to 1.0, the system will become its unstable. Similarly, the values away from zero indicates improved stability of the system.

Optimal size selection using Continuous increment of step size (CISS)

Once the optimal location of DG is fixed, then DG size change from 0 to 1 p.u. of the total load. As the DG size increases, total active power is injected to the system increases. This injected power minimizes the total active power loss. A parabolic curve is formed between DG size and total active power loss. This curve indicates, first the losses of the system decreases till it reaches the optimum point. Thereafter, system losses suddenly increases. Thus, step size plays factor while selecting DG size. In present scenario, the step size chosen is 0.1 Mw. For exact DG size, step size must be as small as possible, but the simulation time increases.

Start

Read load and line data

Run Load flow

Compute VSNI for each bus and choose

maximum value

Sub- Station

19 20 21 22

Fix the location of DG at Maximum value of VSNI bus

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Initially set the DG value PDG =PLoad

and rerun the load flow compute PTL

Save(k)th iteration power loss as

PTL (k)th

Save(k)th iteration power loss as

PTL (k)th

Save(k)th iteration power loss as

PTL (k)th

Save(k)th iteration power loss as

PTL (k)th

26 27 28 29 30 31 32 33

23 24 25

Fig. 2. Single line diagram of 33-bus radial distribution system

If No

PTL (k)th < PTL(k+1)th

Yes

Set PDG as optimal size

Stop

Fig. 3. Flow chart for proposed methodology

RESULT AND DISCUSSIONS

The Fig. 3 shows the single line diagram of 33 bus radial distribution system. The detailed methodology of the proposed method is described by flow chart as shown in Fig.

2. The proposed flow chart described in two steps. At First, optimal location of DGs are calculated by using VSNI. The tabulated values of VSIN are shown in table 1. The table 1 indicates the active and reactive power consumed by different buses and their corresponding VSNI values. In next step, the optimal size of the DGs are determined by using continuous increment of step size (CISS) technique with a step size of 0.1Mw.

A. Case A (DG placement at bus no: 25)

In this case DGs are connected at bus no 25. From the Fig. 4 it is noticed that, active power loss of the system increases, when the DG size increases beyond an optimum point.

Bus No

Real Power Demand (Kw)

Reactive power Demand (Kvar)

Voltage Stability Node Indicator (VSI)

1

0

0

0

2

100

60

0.0316

3

90

40

0.0304

4

120

80

0.0361

5

60

30

0.0259

6

60

20

0.0265

7

200

100

0.0501

8

200

100

0.0547

9

60

20

0.0286

10

60

20

0.0290

11

45

30

0.0251

12

60

35

0.0291

13

60

35

0.0319

14

120

80

0.0430

15

60

10

0.0296

16

60

20

0.0300

17

60

20

0.0312

18

90

40

0.0372

19

90

40

0.0367

20

90

40

0.0324

21

90

40

0.0307

22

90

40

0.0313

23

90

50

0.0308

24

420

200

0.0694

25

420

200

0.0704

26

60

25

0.0261

27

60

25

0.0273

28

60

20

0.0280

29

120

70

0.0411

30

200

600

0.0631

31

150

70

0.0473

32

210

100

0.0546

33

60

40

0.0296

Bus No

Real Power Demand (Kw)

Reactive power Demand (Kvar)

Voltage Stability Node Indicator (VSI)

1

0

0

0

2

100

60

0.0316

3

90

40

0.0304

4

120

80

0.0361

5

60

30

0.0259

6

60

20

0.0265

7

200

100

0.0501

8

200

100

0.0547

9

60

20

0.0286

10

60

20

0.0290

11

45

30

0.0251

12

60

35

0.0291

13

60

35

0.0319

14

120

80

0.0430

15

60

10

0.0296

16

60

20

0.0300

17

60

20

0.0312

18

90

40

0.0372

19

90

40

0.0367

20

90

40

0.0324

21

90

40

0.0307

22

90

40

0.0313

23

90

50

0.0308

24

420

200

0.0694

25

420

200

0.0704

26

60

25

0.0261

27

60

25

0.0273

28

60

20

0.0280

29

120

70

0.0411

30

200

600

0.0631

31

150

70

0.0473

32

210

100

0.0546

33

60

40

0.0296

Variation of Active Power Loss with DG size )

Table 2 VSNI table

Active Power loss

Active Power loss

183.5

183

182.5

Ploss in (kw)

Ploss in (kw)

182

181.5

181

180.5

180

179.5

179

0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4

DG size in (Mw)

Fig. 4. Power loss curve with step increment of DG size at bus no. 25

Optimal point is calculated based on values of voltage stability node indicator, which is shown in Table. 2

Line No Vs Line Loss

60

NDG DG

50

Line Loss(Kw)

Line Loss(Kw)

40

30

20

10

B.

Case B (DG placement at bus no 24)

0

0 5 10 15 20 25 30 35

Line No

From the VSNI table, it is clear that bus no 24 is the most critical or weakest bus of the system. This weakest bus identified as the optimal DG allocation point. Further, DG size is computed by using CISS technique.

Fig. 5. Line loss with and without placement of DG at bus no. 25

183

182.5

182

Ploss in (Kw)

Ploss in (Kw)

181.5

181

180.5

180

Variation of Active Power Loss with DG size )

170

165

160

Ploss in (Kw)

Ploss in (Kw)

155

150

145

140

Variation of Active Power Loss with DG size )

Active Power loss

Active Power loss

179.5

179

0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4

DG size in (Mw)

Fig. 6. Power loss curve with step increment of DG size at bus no. 24

135

Active Power loss

Active Power loss

130

125

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2

DG size in (Mw)

Fig. 8. Power loss curve with step increment of DG size at bus no. 30

Line No Vs Line Loss

60

50

NDG 60

DG

50

Line No Vs Line Loss

NDG DG

40

Line Loss(Kw)

Line Loss(Kw)

40

Line Loss(Kw)

Line Loss(Kw)

30

30

20

20

10

10

0

0 5 10 15 20 25 30 35

Line No

0

0 5 10 15 20 25 30 35

Line No

Fig. 7. Line loss with and without placement of DG at bus no. 24 Fig. 9. Line loss with and without placement of DG at bus no. 30

C. Case C (DG placement at bus no: 30)

To examine the efficacy of the proposed technique, it is

Bus No Vs Bus Voltage

1

NDG

applied to 12.66 kV, 3.72 Mw and 2.3 Mvar RDS consisting

0.99

DG at bus 25

DG at bus 24

of 33 buses. Further, after application of load flow the real power losses incurred by the system before placement of DGs is 210 kW. To reduce the total power loss of the system DGs are placed at different locations as shown in Table. 3. The optimal allocation point is computed by using (11). After computing VSIN at all buses, the three locations i.e. bus no 25, 24 and 30 identified as the most critical bus. To determine the optimum size, CISS technique is applied on all the critical buses.

From Fig. 4, 6 and 8, shows the curve between DG size and total power loss. It is basically follow a parabolic curve, first the total loss decreases and then increases. While selecting DG size, appropriate step size should be chosen carefully. DG size should not exceed the optimum value, above optimum value the total active power loss of the system increases. As a result, system operates in poor voltage regulation and efficiency.

DG at bus 30

Bus voltage(P.U)

Bus voltage(P.U)

0.97

0.96

0.95

0.94

0.93

0.92

0.91

0.9

0 5 10 15 20 25 30 35

Bus No

Fig. 10. Comparison of voltage scenarios at different optimal locations.

Table 3 Active power loss scenario after placement of DG at different optimal locations

Active power loss before DG

Active power loss after DG

Optimal Locations (Bus no)

DG size (Mw)

210.7929

179.2400

25

0.920

210.7929

175.3113

24

0.925

210.7929

125.1074

30

1.325

From Fig. 5, 7 and 9 it clear that after placement of DG at optimal locations, the total active power loss reduced in 33- bus radial distribution system. Finally, Fig. 10 shows the comparison of voltage profile at different optimal locations.

CONCLUSION

In this paper, a mixed analytical method is presented on the impact of dispersed generation in RDS. In this method, VSNI and CISS were used to determine the exact location and compute the size of DGs respectively. Proposed method was tested for 33- bus RDS to reduce active power losses and improve voltage profile at each node. The results showed that clearly indicates that case C (allocation of DG at bus no 30) is found to be most appropriate location in minimizing the total active power loss and improving node voltage as compared to the other cases considered.

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