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Power loss minimisation of rural feeder of Jaipur city by renewable-based DG technologies.

1. Introduction

The operation and control of distribution systems have become more complex due to variation of load on feeders. Electrical power distribution systems generally work in radial configuration. Due to high R/X ratio, radial distribution systems (RDSs) cause a huge voltage drop and considerable power losses. As per Indian scenario, distribution losses constitute a significant part of the system losses (around 21%). Nowadays Distributed Generation (DG) technologies are widely used to minimise power losses in RDS. In DG technology, the small generating units (1 kW-50 MW) are connected near the load side. DG units came into picture from last two decades due to the development in DG technologies and deregulation of electricity market in addition to other factors like economical and regulatory changes in distribution system. DG can utilise the power of both renewable and non-renewable energy sources. Sources like wind, solar, geothermal, small hydro and biomass and cogeneration come in the category of renewable energy, while reciprocating engines, fuel cell, gas turbines and micro-turbines are the part of non-renewable energy sources. Optimal DG Allocation (OPDG) can enhance the system performance with the point of view of voltage stability, minimal system losses and flows, better power quality and improved reliability of power supply. The problem of DG allocation is to find the optimal location and optimum size of DG units to be installed into existing distribution networks that can satisfy all the operating constraints of electrical network, constraints of operation of DG and constraints of cost. Various researchers applied different approaches to solve the DG allocation problem. Levitin (2000) presented a solution by combining genetic algorithm and fast energy loss method. The solution was using fast energy losses that based on the daily load curve calculates the losses and does not require to compute load flow to evaluate the annual energy losses. Kim et al. (2002) adopted hybridised method to determine optimal location of DGs along with their capacities in distribution networks. The authors combined the Genetic algorithm with theory of fuzzy set. Gandomkar, Vakilian and Ehsan (2005) suggested a method that works as a new hybridised algorithm for deciding the optimal DG site and size in medium voltage systems. The GA was correlated to simulated annealing metaheuristic methods and employed for DG allocation. Acharya, Mahat and Mithulananthan (2006) presented an analytical method to calculate the optimal capacity of DG. A direct equation derived from the sensitivity factor equation calculates the optimal size of DG corresponding with each network bus. Kamalinia (2007) proposed a solution for the problem of optimal DG placement developed by using a technique of MADM (multi-attribute decision-making) and genetic algorithm. To determine the optimal capacity and location of DG units, authors used analytic hierarchy process along with data envelopment analysis as the technique of MADM. Le et al. (2007) established a deterministic methodology that was based on the SQP algorithm for determining the optimal location and size of DG in distribution network systems. Abbagana, Bakare and Mustapha (2010)derived a methodology based on the technique of differential evolution to calculate the size and location of DG in distribution network while meeting all the constraints of optimality. The authors presented decision-making techniques to find the solution for OPDG. Sedighi, Igderi and Parastar (2010) evaluated the optimal location and capacity of single and multiple DGs by adopting particle swarm optimization (PSO) method. Kansal, Kumar and Tyagi (2013) has considered type-I, II and III DGs for allocation and applied PSO technique to solve the problem. Nawaz et al. (2016a) presented sensitivity analysis technique and tested it on 33 bus system at different loading condition. Rajkumar Viral (2015) proposed an analytical approach to determine the best position and size of DG units in balanced distribution system to reduce real power strategies has been developed by Gupta, Saxena and Soni (2015). Optimal placement Nawaz et al. (2016b) proposed a new analytical technique to solve DG allocation problem in RDS. Ghaffarzadeh and Sadeghi (2016) applied biogeography-based optimisation (BBO) technique for reduction of active and reactive power loss, reduction of purchased energy from transmission line and improvement of voltage profile. Khodabakhshian and Andishgar (2016) presented intersect mutation differential evolution (IMDE) to determine location and size ofDGs and capacitors in distribution networks simultaneously.

The various types of DG units are (S. Devi et. al 2014)

Type-I: Generate active power (ex. PV module).

Type-II: Generate reactive power (ex. capacitors).

Type-III: Generate both active and reactive power (ex. synchronous generator).

Type-IV: Generate active power but consume reactive power (ex. induction generators used in wind farms).

In this paper, a new approach has been presented for optimal DGs allocation in RDS. Type-I (PV module) and type-II (capacitors) are used for placement. The aim of this paper is to minimise distribution power loss and also to motivate the customers for installing rooftop solar PV module. A new mathematical expression is formulated that is called PVSC (power voltage sensitivity constant). The constant determine size and location of any type of DGs at the same time. Up to 50% penetration level ofDG units (PV module) is also taken into consideration, so that less size of DG units produce maximum loss reduction. The proposed method is tested on standard IEEE 69 bus and 130 bus real distribution system of Jamwa Ramgarh village, Jaipur city. The obtained results of standard test system are compared with other approaches and found superior. The results of real distribution system are appreciated by Rajasthan State Electricity Board (namely as JVVNL), Jaipur.

2. Problem formulation

DGs (PV module and capacitors) are generally used to minimise real and reactive power loss of the distribution systems. In this paper, real power losses are minimised by allocating multiple DG units of optimal size. Figure 1 shows the line diagram of two bus system. The DG unit is connected at bus j.

The real power loss of above system for n bus is calculated by using (El-Fergany 2015)

(1)[P.sub.Loss] = [n.summation over (i=1)][n.summation over (j=1)]R[|[V.sub.i]|.sup.2] + [|[V.sub.j]|.sup.2] - 2|[V.sub.i]||[V.sub.j]|cos [[delta].sub.ij]/|[Z.sub.2]| (1)

A new mathematical formulation has been proposed in this paper in order to solve the problem of allocation of DG units. The PVSC is anticipated to determine the size and location of DG units.

Min. (f1) = min. (PVSC) (2)

where

[P.sub.realloss]: base case real power loss.

[P.sub.dgloss]:activepower loss afterDGplacementat ith bus.

Now, the objective function of the problem is to

Min. (f1) = min (PVSC) (3)

The Prealloss of any system will be fixed. For optimal placement of DG units, the value of [P.sub.dgloss] should be minimum. Hence, the value of PVSC should be minimum. The operating constraints of the problem are

(a) Equality constraints: The arithmetical summation of all incoming and outgoing powers together with power losses for distribution system and power generated by DG units should be equal to0.

(b) Inequality constraints:

1. The injected power by each DG units is restricted by its maximum and minimum limits as

[P.sup.min.sub.DGj] [less than or equal to] [P.sub.DGj] [less than or equal to] [P.sup.max.sub.DGj]

[Q.sup.min.sub.DGj] [less than or equal to] [Q.sub.DGj] [less than or equal to] [Q.sup.max.sub.DGj]

2.Bus voltage limits (as per Indian standard [+ or -]5% margin) 0.95pu [less than or equal to] [V.sub.i], [less than or equal to] 1.05pu

3.The feeder should not go beyond the thermal limit of the line.

where

R: Line resistance between bus i and j;

X: Line reactance between bus i and j;

Z: Line impedance;

[V.sub.i]. Magnitude of voltage at bus i;

[V.sub.j]: Magnitude of voltage at bus j;

[V.sub.min]: Minimum bus voltage

[[delta].sub.i]:Angle of voltage at bus i;

[[delta].sub.j] Angle of voltage at bus j;

P and Q: Active and reactive power flow from bus i to j.

3.Proposed approach

A new approach has been proposed in this paper to solve optimal DG placement problem. Other optimisation techniques have large number of iterations, so the computational time is large. But, in this proposed technique, the processing time is less. In most of the techniques, the candidate bus is determined by sensitivity analysis and size is determined by other optimisation methods. But, the proposed technique gives size and location both at same time. The proposed method for optimal placement of DG units is based on a new mathematical formulation i.e. PVSC.

To obtain the optimal location and size of DG units, PVSC value at each bus for specified DG size is calculated. The bus, which has least PVSC value, will be the candidate bus for allocation and the corresponding DG's size will be the optimal size.

Computational process for proposed analytical technique is explained below:

Step 1: Run the load flow programme and calculate value of [P.sub.realloss].

Step 2: Start with 5% DG penetration level of total system load and run load flow programme.

Step 3: Compute [P.sub.dgloss] of the system and 'PVSC' values for each bus using Equation 2.

Step 4: Now vary DG penetration in small step and compute [P.sub.dgloss].

Step 5: Stop the programme as bus number is changed.

Step 6: Store the size of DGs which gives least amount of [P.sub.dgloss].

Step 7: The bus, which has least 'PVSC' value, will be the optimal position of DG unit.

Step 8: Repeat Steps 4-7to find more location of DGs.

4.Test results

The proposed method has been tested on standard IEEE 69 bus distribution system (Savier and Das 2007) and 130 bus real distribution system of Jamw Ramgarh area of Jaipur city. Proposed method has been implemented using MATLAB software.

4.1. IEEE 69 bus system

The standard IEEE 69 bus distribution system, as shown in Figure 2, has 12.66 kV and 100 MVA base values. The total system load is 3.802 MW and 2.694 MVAr [15]. The base case real power loss of 69 bus system is 225 kW and minimum bus voltage is 0.9092 pu.

Following cases are considered here:

Case I: Allocation of only DG units.

Case II: Allocation of only capacitors.

Case III: Simultaneous placement of DGs and capacitors.

4.2.Case I: allocation of only DG (solar PV module) units

The proposed analytical method is applied on 69 bus standard test system. The first three buses are selected for DG allocation. Maximum 50% DG penetration is used here. The Table 1 shows the obtained results for 69 bus system after applying the proposed method. The optimal size and location of DGs are determined as 290 kW (bus no. 21), 940 kW (61) and 560 kW (64). The real power loss is reduced to 77.52 kW from 225 kW after DG allocation. The minimum bus voltage is also enhanced to 0.970 pu from 0.909 pu.

4.3.Case II: allocation of only capacitors

The proposed technique is also applied to determine optimal location and size of capacitor units. The results are shown in Table 2. The optimal size and location of shunt capacitors are found as 690 kVAr (61), 240 kVAr (21) and 360 kVAr (64). The real power loss (without compensation) is 225 kW and reduced to 149.22 kW after installation of capacitor of total size 1290 kVAr. The minimum bus voltage is also improved to 0.929 pu.

4.4.Case III: simultaneous placement of DGs and capacitors

The results for simultaneous placement of DGs and capacitor bank are presented in Table 3. The real power loss is reduced to 13.5 kW from 225 kW. The size of DG (PV module) and shunt capacitor units are 1790 kW and 1290 kVAr, respectively. This yield to percentage loss reduction of 94% and the minimum bus voltage is also improved to 0.986 pu from 0.9092 pu. The reactive power loss is also reduced to 90%.

The result of case-III is compared with the result of PSO (Satish Kansal, Kumar, and Tyagi 2013), IMDE (Khodabakhshian and Andishgar 2016) and BBO (Ghaffarzadeh and Sadeghi 2016) techniques in Table 4. It is observed that proposed approach gives maximum loss reduction at lesser DG and capacitor size than other techniques.

The comparison of bus voltage profile is presented in Figure 3. In the comparison, four cases are considered i.e. base case, after DG allocation only, after capacitor allocation only and after simultaneous allocation of DG and capacitor.

4.5.Jamwaramgarh 130 - bus real distribution system, Jaipur

The system under consideration is of 11 kV rural feeders, Rampura village, emanating from Jaipur Discom 33/11 kV Jamwaramgarh substation. The system has 130 buses as shown in Figure 4. The system peak load is 1875 kW and 1415 kVAr. The area has mainly agricultural load (mainly submersible water pump of rating 1-10 hp). The average load of the area in day time is about 80% (1500 kW and 1132 kVAr) of peak load. In the evening, the load is reduced to 20-25% of the peak load. The bus no. 1 is swing bus and number ofload buses are 100. The real power loss of the system is 335 kW and minimum bus voltage is 0.825 pu at peak load. At average load level, the real power loss is 198 kW and minimum bus voltage is 0.8657 pu. In this analysis, the energy theft is not considered. The Jamwa Ramgarh area is located near Jaipur city (capital of Rajasthan state). So, the energy theft of this area is negligible. At present scenario, no compensation device is connected at the load side in the area.

4.6.Case I: allocation of only DG units

The proposed approach has been applied on 130 bus real distribution system to find out optimal site and size of DG (PV Module) units. First five buses are selected for allocation of DG units. The level of DG penetration is also fixed to 50% of total real power load of the system. The results, before and after DG allocation, are shown in Table 5.

At average load, the five location and size of PV set are 180 kW (bus no.106), 90 kW (bus no. 115), 120 kW (bus no. 119), 140 kW (bus no. 122), 220 kW (bus no. 128). Now, the real power loss is reduced to 87.2 kW from 198 kW and minimum bus voltage is also enhanced to 0.93 pu from 0.865 pu.

4.7.Case II: allocation of only capacitors

The optimal size and position of shunt capacitor units for 130 bus system at average load level are calculated by proposed technique. Similarly, first five candidate buses are selected for placement of capacitor units. The results are shown in Table 6.

The optimal location and size of shunt capacitors are determined as 290 kVAr (bus no. 53), 140 kVAr (77), 140 kVAr(114), 150 kVAr (120) and 210 kVAr (126). After placing of 930 kVAr of shunt capacitor bank, the real power is reduced to 125.57 kW and minimum bus voltage is enhanced to 0.908 pu.

4.8.Case III: simultaneous placement of DGs (solar PV module) and capacitors

The results for simultaneous placement of DGs and capacitors of 130 bus real distribution systems at three different load levels i.e. heavy, nominal and light load are shown in Table 7. The Figure 5 shows the single line diagram of 130 bus system after simultaneous placement of DGs and capacitors.

From Table 7, it is observed that after DG and capacitor allocation, the percentage real and reactive power loss reduction ofthe real system are 83.5% and 83%, respectively. The minimum bus voltage is also improved to 0.96 pu from 0.8657 pu.

The comparison of bus voltage profile at average load level is presented in Figure 6.Inthe comparison, four cases are considered i.e. base case, after DG allocation only, after capacitor allocation only and after simultaneous allocation of DG and capacitor.

It is observed from Figure 6 that after simultaneous placement of DGs and capacitors at all loading conditions, the voltage profile of each bus laid down under specified limit of Indian standard.

5. Conclusion

In this paper, a new approach has been proposed in order to minimise active power loss of RDS by maintaining several operating conditions. The objective has been achieved by allocation of DG units (type-I and II). A new mathematical formulation, PVSC, has been proposed for determining candidate bus location and size. The level of DG penetration is also considered in a range of 0-50% of total system load. To examine the performance of the proposed approach, it has been tested on two different distribution systems i.e. standard IEEE 69 bus distribution systems and 130 bus real distribution system of Jamwaramgarh area of Jaipur city. On the standard distribution system, the results are compared with the latest optimisation techniques. The results obtained show that the proposed approach gives maximum percentage loss reduction on lesser size of DGs. The method is also examined on real distribution system of Jamwaramgarh area of Jaipur city (India). After DG and shunt capacitor allocation, the percentage real and reactive power loss reduction (at average load) are 83.5% and 83%, respectively, and minimum bus voltage is also improved to 0.96 pu from 0.865 pu. The customers or distribution companies are motivated to set up a rooftop solar photovoltaic system after reviewing the results of real distribution system. The obtained results of real distribution system are also verified by 'State Electricity Board (JVVNL)', Jaipur, India.

Disclosure Statement

No potential conflict of interest was reported by the authors.

References

Abbagana, M., G. A. Bakare, and I. Mustapha. 2010. "Optimal Placement and Sizing of a Distributed Generator in a Power Distribution System Using Differential Evolution" Proceedings of the 1st International Technology, Education and Environment Conference African Society for Scientific Research (ASSR).

Acharya, N., P. Mahat, and N. Mithulananthan. 2006. "An Analytical Approach for DG Allocation in Primary Distribution Network." International Journal of Electrical Power & Energy Systems 28 (10): 669-678. doi:10.1016/j.ijepes.2006.02.013.

Devi, S., and M. Geethanjali. 2014. "Application of Modified Bacterial Foraging Optimization Algorithm for Optimal Placement and Sizing of Distributed Generation." Expert Systems with Applications 41: 2772-2781. doi:10.1016/j.eswa.2013.10.010.

El-Fergany, A. 2015. "Study Impact of Various Load Models on DG Placement and Sizingusing Backtracking Search Algorithm." Applied Soft Computing 30: 803-811. doi:10.1016/j.asoc.2015.02.028.

Gandomkar, M., M. Vakilian, and M. Ehsan. 2005. "Optimal Distributed Generation Allocation in Distribution Network Using Hereford Ranch Algorithm," Electrical Machines and Systems, 2005. ICEMS 2005. Proceedings of the Eighth International Conference on, vol.2, pp.916-918.

Ghaffarzadeh, N., and H. Sadeghi. 2016. "New Efficient BBO Based Method for Simultaneous Placement of Inverter-Based DG Units and Capacitors considering Harmonic Limits." Electrical Power and Energy Systems 80: 37-45. doi:10.1016/j.ijepes.2016.01.030.

Gupta, S., A. Saxena, and B. P. Soni. 2015. "Optimal Placement Strategy of Distributed Generators Based on Radial Basis Function Neural Network in Distribution Networks." Procedia Computer Science 57: 249-257. doi:10.1016/j.procs.2015.07.478.

Kamalinia, S. 2007. "A Combination of MADM and Genetic Algorithm for Optimal DG Allocation in Power Systems", Universities Power Engineering Conference, 2007. UPEC 2007. 42nd International, Sept.

Kansal, S., V. Kumar, and B. Tyagi. 2013. "Optimal Placement of Different Type of DG Sources in

Distribution Networks." Electrical Power and Energy Systems 53: 752-760. doi:10.1016/j.ijepes.2013.05.040.

Khodabakhshian, A., and M. H. Andishgar. 2016. "Simultaneous Placement and Sizing of DGs and Shunt Capacitors in Distribution Systems by Using IMDE Algorithm." Electrical Power and Energy Systems 82: 599-607. doi:10.1016/j.ijepes.2016.04.002.

Kim, K.-H., Y.-J. Lee, S.-B. Rhee, S.-K. Lee, and S.-K. You. 2002. "Dispersed Generator Placement Using fuzzy-GA in Distribution Systems," Power Engineering Society Summer Meeting, 2002 IEEE, vol.3, pp.1148-1153.

Le, A. D. T., M. A. Kashem, M. Negnevitsky, and G. Ledwich. 2007. "Optimal Distributed Generation Parameters for Reducing Losses with Economic Consideration," Power Engineering Society General Meeting, 2007. IEEE, pp.1, 8, June 24-28.

Levitin, G. 2000. "Optimal Capacitor Allocation in Distribution Systems Using a Genetic Algorithm and a Fast Energy Loss Computation Technique." IEEE Transaction on Power Delivery15: 2. doi:10.1109/61.852995.

Nawaz, S., M. Imran, A. Sharma, and A. Jain. 2016a. "Optimal Feeder Reconfiguration and DG Placement in Distribution Network." International Journal of Applied Engineering Research 11 (7): 4878-4885.

Nawaz, S., A. K. Bansal, and M. P. Sharma. 2016b. "Optimal Allocation of Multiple DGs and Capacitor Banks in Distribution Network." European Journal of Scientific Research 142 (2): 153-162. ISSN 1450-216X/1450-202X.

Rajkumar Viral, D. K. K. 2015. "An Analytical Approach for Sizing and Siting of DGs in Balanced Radial Distribution Networks for Loss Minimization." Electrical Power and Energy Systems 67: 191 -201. doi:10.1016/j.ijepes.2014.11.017.

Savier, J. S., and D. Das. 2007. "Impact of Network Reconfiguration on Loss Allocation of Radial Distribution Systems." IEEE Transactions Power Delaware 2 (4): 2473-2480. doi:10.1109/TPWRD.2007.905370.

Sedighi, M., A. Igderi, and A. Parastar. 2010. "Sitting and Sizing of Distributed Generation in Distribution Network to Improve of Several Parameters by PSO Algorithm," Presented at IPEC, 2010 Conference Proceedings.

Sarfaraz Nawaz and Ankush Tandon

Department of Electrical Engineering, Swami Keshvanand Institute of Technology Management & Gramothan, Jaipur, India

KEYWORDS

Radial Distribution Systems (RDS); real power loss; real distribution systems; PVSC; Distributed Generation (DG); shunt capacitors

ARTICLE HISTORY

Received 16 December 2017

Accepted 3 July 2018

https://doi.org/10.1080/1448837X.2018.1500667
Table 1. Result of 69 bus systems before and after DG allocation.

Case        Item                      Results

Without DG  Power loss (kW)            225
            [V.sub.min] (pu)             0.909
With DG     DG size in kW (bus No.)    290 (21); 940 (61); 560 (64)
            Total DG size in kW       1790
            Power loss (kW)             77.52
            [V.sub.min] (pu)             0.970
            % loss reduction            65.54

Table 2. Results for 69 bus systems after capacitor installation.

Case              Item                        Results

Before capacitor  Power Loss in kW             225
placement         Min. bus voltage (pu)          0.909
After capacitor   Capacitor size in kVAr and   690 (61)
placement         location                     240 (21)
                                               360 (64)
                  Total kVAr                  1290
                  Power loss (kW)              149.22
                  Min. bus voltage               0.929
                  % Loss reduction              33.7%

Table 3. Results of 69 bus systems after simultaneous placement of DGs
and capacitors.

Case                         Item                             Results

Base case                    Real power loss (kW)              225
                             Reactive power loss (kVAr)        102.15
                             Minimum bus voltage (pu)            0.9092
DG and capacitor allocation  Total DG size (kW)               1790
                             Total capacitor size (kVAr)      1290
                             Real power loss (kW)               13.5
                             % Real power loss reduction        94%
                             Reactive power loss                10.4
                             % Reactive power loss reduction    90%
                             Minimum bus voltage (pu)            0.986

Table 4. Comparison of results of 69 bus systems for case-III.

Item                     PSO (Kansal, Kumar,  IMDE (Khodabakhshian
                         and Tyagi 2013)      and Andishgar 2016)

Total DG size in kW      1820                 2217
Total capacitor size in  1300                 1300
kVAr
Total real power loss      23.17                13.83
% Loss reduction           89.70%               93.85%
Min. voltage                0.98                 0.99

Item                         BBO [26] (Ghaffarzadeh  Proposed
                             and Sadeghi 2016)

Total DG size in kW           2326                    1790
Total capacitor size in       2700                    1290
kVAr
Total real power loss           54.90                   13.5
% Loss reduction                75.6%                   94%
Min. voltage                     0.97                    0.986

Table 5. Results of 130 bus real systems after DG allocation only.

Case        Item                     Results

Without DG  Power loss in kW         198
            [V.sub.min] in pu          0.8657
With DG     DG size in kW [bus no.]  180 (106); 90 (115); 120 (119);
                                     140 (122); 220 (128)
            Total DG size in kW      750
            Real power losses in kW   87.2
            Min. bus voltage in pu     0.934
            % Loss reduction          56%

Table 6. Results of 130 Bus Jamwaramgarh Distribution Systems after
Capacitor Allocation only.

Case        Item                          Results

Without DG  Power loss in kW               198
            [V.sub.min] in pu                0.8657
With DG     Capacitor size in kVAr         290 (53); 140 (77); 140
                                          (114); 150 (120); 210 (126)
            [bus no.]
            Total capacitor size in kVAr   930
            Real power losses in kW        125.57
            Min. bus voltage in pu           0.908
            % Loss reduction                36.6%

Table 7. Results of 130 bus real systems after simultaneous allocation
of DG and capacitor.

Case                 Item                             Results

Base case at         Real power loss (kW)             198
average load level
                     Reactive power loss (kVAr)       107.6
                     Minimum bus voltage (pu)           0.8657
Simultaneous         Total DG size (kW)               750
placement of DG and
capacitor
                     Total capacitor size (kVAr)      930
                     Real power loss (kW)              32.63
                     Reactive power loss (kVAr)        18.40
                     Minimum bus voltage (pu)           0.96
                     % Reactive power loss reduction   83%
                     % Real power loss reduction       83.5%
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Author:Nawaz, Sarfaraz; Tandon, Ankush
Publication:Australian Journal of Electrical & Electronics Engineering
Geographic Code:9INDI
Date:Mar 1, 2018
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