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1096 IEEE SYSTEMS JOURNAL, VOL. 8, NO. 4, DECEMBER 2014

Voltage Variation on Distribution Networks WithDistributed Generation: Worst Case Scenario

M. A. Mahmud, Member, IEEE, M. J. Hossain, Senior Member, IEEE, and H. R. Pota

AbstractThis paper presents an analytical approach to estab-lish a relationship between the voltage variation and distributedgeneration (DG) integration for the planning and operation ofdistribution networks with DG. The proposed approach is mainlybased on the derivation of a voltage variation formula for distri-bution networks with DG and the consideration of the worst casescenario, which establishes a relationship between the amount ofvoltage variation and maximum permissible DG. Some recommen-dations are presented based on the worst case voltage variationformula and DG integration to counteract the voltage variationeffect. The relationship between the connection cost and voltagelevel is also presented in this paper. The feasibility of the proposedapproach is validated by comparing the voltage profile obtainedfrom the derived formula to that with the existing power systemsimulation software.

Index TermsDistributed generation (DG), distributionsystems, voltage variation, worst case scenario.

I. INTRODUCTION

T RADITIONALLY, distribution networks are passive net-works where the flow of both real and reactive poweris from a higher to a lower voltage level. The integration ofa small- and medium-sized generation into distribution net-works is increasing as these types of generating units offer anumber of technical, environmental, and economical benefitsfor the utilities along with consumers due to their locationnear to customers [1][3]. Beside these benefits, the integrationof distributed generation (DG) units significantly changes thebehavior of the distribution network operation, e.g., passivedistribution networks with a unidirectional power flow areconverted into active distribution networks with a bidirectionalpower flow. From the technical point of view, these changeshave negative impacts along with positive impacts to bothdistribution network service providers (DNSPs) and customers.

To provide the maximum benefit and alleviate the limit ongeneration capacity, an active network management (ANM) ofdistribution networks or other novel approaches are needed tobe considered, which allow the connection of more DG unitsinto the existing distribution network [4]. An ANM in the form

Manuscript received September 30, 2011; revised June 12, 2012 and July 29,2012; accepted October 7, 2012. Date of publication June 12, 2013; date ofcurrent version November 20, 2014.

M. A. Mahmud is with the Future Grid Research Centre, Department of Elec-trical and Electronic Engineering, The University of Melbourne, Melbourne,Vic. 3010, Australia (e-mail: [email protected]).

M. J. Hossain is with Griffith School of Engineering, Griffith University,Gold Coast, Qld. 4222, Australia (e-mail: [email protected]).

H. R. Pota is with the School of Engineering and Information Technology,The University of New South Wales at the Australian Defence Force Academy,Canberra, A.C.T. 2600, Australia (e-mail: [email protected]).

Digital Object Identifier 10.1109/JSYST.2013.2265176

of centralized control is introduced in [5] to increase the DGconnection capacity. A centralized distribution managementsystem controller, similar to that used in transmission networks,is presented in [6] and [7] to maximize the DG penetration usinga wide-area voltage control and reactive power managementapproach where state estimations are employed to assess thevoltage level. However, the centralized approaches presentedin [5] and [7] require significant investment in sensors andcommunication assets, which make their application difficult toincrease the DG penetration.

There are several alternative approaches, which include toensure the maximum DG capacity with minimal voltage im-pacts in the distribution network. A distributed voltage con-trol approach is introduced in [8] to limit the voltage risein distribution feeders by considering continuously distributedloads and generation. Some other distributed active manage-ment approaches are presented in [9][11] to accommodatemore DG units by controlling the power factor rather than thevoltage control to counteract the effect of the DG integration.However, these approaches are similar to fit-and-forget mannerthat accommodate the full DG capacity without encounteringany voltage or thermal issues [12].

There is significant ongoing research interest for evaluatingthe DG capacity with a wide range of methods, objectives, andconstraints within two broad approaches. The first approachis to accommodate DG units with distributed and prespecifiedcapacities at the best locations by using evolutionary computa-tions such as genetic algorithms (GAs) [13], [14] and the parti-cle swarm optimization (PSO) [15], which are able to handle thedistributed formulations. However, the distributed formulationof the DG capacity will not provide a truly optimal solution.Moreover, the use of multiple capacities extends the searchspace significantly. The other approach requires the networklocations of interest to be prespecified with algorithms guidingthe DG capacity growth within network constraints. In this case,these methods are not capable of solving the continuous func-tions of the capacity. To solve these continuous functions, linearprogramming [16], gradient search [17], or optimal power flow(OPF) [18][23] methods are employed. A major drawbackof this approach is that the perceived optimal solution maycontain a number of sites with very small available capacitieswhen a large number of locations are searched. Moreover, therequirement of prespecifying locations is another major issuewith this approach as this involves a significant effort beyondthe feasibility of manual searches even for a small distributionnetwork. To overcome some of these limitations, a hybridmethod (the combination of GA and OPF) is presented in [24]where the GA is used to search a large range of combinations

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MAHMUD et al.: VOLTAGE VARIATION ON DISTRIBUTION NETWORKS WITH DG: WORST CASE SCENARIO 1097

of locations and an OPF is used to define the available capacityfor each combination. However, this method also requires thenumber of DG units to be prespecified. Another hybrid method(the combination of PSO and OPF) is introduced in [25] todo the same task as presented in [24] and obtain a betterperformance, but this method also suffers from the limitationof prespecifying DG units.

The majority of the optimization techniques are complexand involve more mathematical computations. Moreover, thesetechniques have the problem of long convergence time, prema-ture convergence, and no performance guarantee. To overcomethese difficulties, analytical approaches can be adopted to en-hance the power quality of distribution feeders in terms of thenode voltage profile improvement, which, in turn, reduces thepower loss. Various analytical methods have been presented in[26][30] for the placement of optimal DG units in distributionnetworks. Most of the analytical approaches as presented in[26][30] are mainly based on the network sensitivity approach.

From the existing literature on the DG planning and opera-tion, it can be summarized that the main purpose of integratingDG units is to deliver a portion of real and/or reactive powerinto the network to enhance the voltage profile of distributionnetworks along with the reduction in distribution losses andinvestment costs. However, most of the approaches are mainlybased on the consideration of real power available from the DGunit although the consideration of reactive power available fromthe DG unit has gained attraction in some recent investigations[11], [29][31]. The reactive power from DG units can helpimprove the voltage profile and reduce the energy loss. The lackof attention to the reactive power capability exhibited by DGunits at the planning stage may lead to the potential increasein investment costs and improper allocation of DG units. Itis of vital importance that the reactive capability limit of DGunits is accounted in distribution system planning and operationproblems to quantify the associated benefits.

The worst case scenario of a system is very important forthe planning and operation as it captures all unusual conditionsof the system. In distribution networks planning and operation,the worst case scenario is essential to demonstrate the relation-ship between the voltage variation and DG connected to thedistribution network and to ensure that distribution networksand customers will not be adversely affected. The aim of thispaper is to establish a relationship between the voltage variationand DG integration in a distribution network by considering theworst case scenario and to provide some solutions to the voltagevariation and connection costs. Finally, simulation results arepresented for the justification of the proposed approach.

II. VOLTAGE VARIATION IN CONVENTIONALDISTRIBUTION NETWORK

Since distribution networks have high resistance to reactanceratio, as compared to transmission networks, the percentagevoltage drop in distribution networks is more than that intransmission networks. To get an understanding of the voltagedrop in distribution networks, the amount of the voltage dropis first calculated for a two-bus distribution system, as shownin Fig. 1.

Fig. 1. Conventional two-bus distribution system.

In Fig. 1, DS and OLTC stand for the distribution substationand on-load tap-changer, respectively; VS is the sending-endvoltage; VR is the receiving-end voltage; P and Q are thereal and reactive power flowing through the distribution line,respectively; and PL and QL are the real and reactive powerof the load, respectively. The voltage at the sending end can bewritten as [32]

VS = VR +P jQ

V S(R+ jX)

= VR +RP +XQ

V S+ j

XP RQV S

.

Therefore, the voltage drop between the sending and receiv-ing ends can be written as

V = VS VR = RP +XQV S

+ jXP RQ

V S.

Since the phase difference between the sending-end voltageand the receiving-end voltage is very small, the voltage drop isapproximately equal to the real part of the drop [33], and if thesending-end bus is considered as the reference bus, the angleof this voltage is 0, i.e., V S = |VS | = VS . Therefore, the aboveequation can be approximated as

V RP +XQVS

. (1)

If the sending-end voltage of the system is considered as thebase voltage, in per unit, VS can be considered as one and (1)can be written as follows:

V RP +XQ. (2)

The amount of voltage variation in a large distribution net-work can be also determined by using a similar approach. InFig. 2, an n-bus system is considered. The voltage drop betweenthe ith and jth buses can be written as

Vij RijPij +XijQijVi

, i, j = 1, 2, 3, . . . , n, i = j(3)

where Vij is the variation of voltage between the ith and jthbuses, Rij is the resistance between the ith and jth buses, Xijis the reactance between the ith and jth buses, Vi is the voltageat the ith bus, and Pij and Qij are the active and reactive powerflowing from the ith to the jth bus, respectively.

The derivation of voltage variation formula for distributionnetworks with DG based on the derived voltage variation for-mula as aforementioned is presented in the following section.


Fig. 2. Conventional n-bus large distribution system.

Fig. 3. Two-bus distribution system with DG.

III. VOLTAGE VARIATION IN DISTRIBUTIONNETWORK WITH DG

When generators are connected to the distribution system,the power flow and the voltage profile are affected. In order toexport power, a generator is likely to operate at a higher voltage,as compared to other nodes where it is supplying power. In thiscase, receiving-end voltage VR will be

VR VS +RP +XQ (4)as the direction of the power flow is reversed. Thus, the voltageat the point of connection of the generator will rise above thesending-end voltage, which can be clarified through Fig. 3.

In Fig. 3, a distributed energy resource (DER) is connectedwhere the voltage is VGEN; PG and QG are active and reactivepower generated by the DG, respectively; PL and QL are theactive and reactive power of the load, respectively; and QC isreactive power of the shunt compensator. This DER with loadsand compensators is connected to the distribution system via anoverhead distribution line with impedance R+ jX and throughan OLTC. The voltage variation along the distribution network,as shown in Fig. 3, can be written as follows:

V = VGEN VS RP +XQVGEN

(5)

where P = (PG PL), and Q = (QC QL QG). IfVGEN is considered as base voltage and expressed in terms ofper unit, then (5) can be written as

V = VGEN VS R(PG PL) +X(QC QL QG).(6)

DERs always export active power (+PG) and may exportor import reactive power (QG), whereas the load consumesboth active PL and reactive QL power and the compen-sators may supply or absorb only reactive power QC . Thereactive power capability of DERs depends on the nature ofDERs connected to distribution networks. The present trend isto integrate synchronous machine-based combined heat power

Fig. 4. n-bus large distribution system with DG.

(CHP) generators, induction machine-based wind generators,and voltage source inverter-based photovoltaic (PV) generatorsinto distribution networks, which have different reactive powercapabilities. For example, if there is a synchronous machine-based CHP unit within distribution systems, it can providereactive power to the system as it possesses the capabilityof controlling reactive power output by adjusting the fieldexcitation. However, if a wind generator is connected to thedistribution network as DG, it is essential to provide somereactive power to the system to maintain the voltage stabilityas its induction generator requires a source of reactive power tooperate. Again, if a PV generator is connected to the system, itcannot provide any reactive power as it needs to operate at unitypower factor in order to deliver maximum power into the grid.

The voltage variation in large distribution networks withDG can be obtained in a similar way to that in conventionaldistribution networks as discussed before. If we integrate a DGunit at the jth bus, as presented in Fig. 4, the voltage variationVji at the point of the DG connection, i.e., at the jth bus of aradial distribution feeder, can be written as

Vji Rij(PGj PLj) +Xij(QGj QLj)Vj

(7)

where PGj is the active power supplied by the DG unit con-nected to the jth bus, QGj is the reactive power of the DG unitconnected to the jth bus, and PLj and QLj are the active andreactive power of the load connected to the jth bus, respectively.Now, if a shunt compensator with reactive power QCj is con-nected at the jth bus, (7) can be written as

Vji Rij(PGj PLj) +Xij(QGj QCj QLj)Vj

. (8)

In per unit, (8) can be written as

Vji Rij(PGj PLj) +Xij(QGj QCj QLj).

These voltage variation formulas can be used to determinethe relationship between the voltage variation and DG inte-gration, which may suggest possible solutions to mitigate thevoltage variation. In this paper, the worst case scenario of thedistribution network is considered to investigate the relationshipbetween the voltage variation and DG integration, which isnot considered in [32]. The worst case scenario of distributionnetworks with DG is discussed in the following section.


IV. ESTIMATION OF VOLTAGE VARIATION ANDDG CAPACITY USING WORST CASE SCENARIO

DERs are connected to the distribution system due to thetechnological innovations and changes in the economic andregulatory environment, as well as to meet the increased loaddemand. From (6), we can write

PG VGEN VS +RPL X(QC QL QG)R

(9)

and for a large distribution network

PGj Vj Vi +RijPLj Xij(QCj QLj QGj)Rij

.

From (9), it is clear that the level of DG connected to thedistribution system depends on the voltage at the primary DS,the voltage level of the receiving end, the size of the conductorsand the distance from the primary DS, the load demand on thesystem, and the other generation on the system.

DNSPs should consider the worst case operating scenariosto demonstrate the relationship between the voltage variationand the amount of DG integration so that their networks andcustomers will not be adversely affected. Generally, these worstcase scenarios are:

1) minimum load maximum generation;2) maximum load minimum generation;3) maximum load maximum generation.Since the aim of this paper is to find out the maximum

amount of DG units that can be integrated into the distributionnetwork under the worst condition, the minimum load max-imum generation scenario is considered in this paper as theworst case scenario. Under the considered worst case scenario

PL = 0 QL = 0 PG = PGmax.

Now, for the sake of simplicity, if we consider that the systemis operating at unity power factor, QG and QC will be zero.In this case, the worst case voltage variation for a two-busdistribution network can be obtained from (6) and written inthe following form:

Vworst = VGENmax VS RPGmax. (10)For a large system, the worst case voltage variation is

Vworstji = Vjmax Vi RijPGjmax.From (10), it is clear that the voltage variation depends on theresistance of the distribution line and the power supplied byDERs. If the resistance of the distribution line is constant, thenwe can write

Vworst PGmax (11)and that for a large system is

Vworstji PGjmax.Therefore, the voltage variation in the distribution network withDG is directly proportional to the amount of active power

supplied by DERs. Since there is a linear relationship betweenthe voltage variation and the amount of active power suppliedby DERs, the voltage variation is more onerous when there isno demand on the system as the generation is exported backto the primary distribution system. The voltage variation in thedistribution system also limits the amount of DG units that canbe integrated into the distribution network, and this can be seenin the following equation, which is obtained from (6):

PGmax VGENmax VSR

. (12)

The capacity of the DG unit that can be accommodated in theexisting system is clearly limited by the maximum voltage atthe point of DG connection, which can be written as

PGmax VGENmax VSR

(13)

and for a large distribution system, it can be written as

PGjmax Vjmax ViRij

.

Therefore, from the worst case scenario, it is seen that theresistance of the line, as well as the voltage variation within thesystem, is critical for the DG integration. From the worst casescenario of distribution networks with DG, possible solutions tothe voltage variation due to the integration of the maximum DGunit can be obtained easily, which is presented in the followingsection.

V. MITIGATION OF VOLTAGE VARIATION BASED ONWORST CASE SCENARIO

The integration of DERs may cause an excessive voltagevariation. Traditionally, the DS is equipped with an over- orundervoltage protection relay to protect it. The voltage protec-tion scheme may permanently disconnect DERs, or it may evendisconnect the DS from the main grid, which may cause seriouseconomical damage for customers and DNSPs. The voltagevariation on the DS can be mitigated through the followingapproaches:

1) by using the resistance reduction;2) by regulating primary DS voltage VS ;3) by using the generation curtailment;4) by using the reactive power compensation.

A. Mitigation of Voltage Variation by Using theResistance Reduction

If the amount of the DG connected to a distribution system isconstant, from (10), we can write

Vworst R. (14)From (14), it is seen that the worst case voltage variation thatconsiders the maximum DG penetration is directly proportionalto the resistance of the line. Therefore, the voltage variationin distribution networks can be reduced by decreasing the lineresistance. The resistance of a line can be reduced by increasing


the conductor size for which it is essential to change the in-frastructure of the existing distribution network infrastructure,which is very difficult in practice. Therefore, before construct-ing a new distribution system, i.e., for the future planning andoperation of a distribution network, DNSPs should consider thereduced value of the line resistance to make provisions for alarger amount of DG units.

B. Mitigation of Voltage Variation by Using the ReactivePower Compensation

If we consider the worst case scenario with DERs andcompensators are operating at a power factor other than unity,(6) can be rewritten as

Vworst RPGmax +X(QGmax QC). (15)

From (15), it is seen that the voltage variation can be mitigatedby adjusting the reactive power of DERs and compensators.

As previously discussed, a DG unit may export or importpower into or from the grid. When a DG unit exports power,(15) can be written as

Vworst RPGmax +X(+QGmax QC) (16)

and that for large systems

Vworstji RijPGmaxj +Xij(+QGmaxj QCj). (17)

From (16) and (17), it is seen that the second part of the rightside of these equations needs to be negative to mitigate thevoltage rise problem, and in this case, the compensator mustabsorb reactive power that should be greater than the maximumreactive power supplied by the generator. However, if there is avoltage dip within the network, the compensator should supplyreactive power to the system to keep the voltage within thespecified limit.

Again, if a DG unit imports reactive power, (15) can bewritten as

Vworst RPGmax +X(QGmax QC) (18)

and for large systems, it can be written as

Vworstji RijPGmaxj +Xij(QGmaxj QCj). (19)

From (18) and (19), it can be said that if there is a voltage risewithin the system and the reactive power absorbed by DG isnot sufficient, it is essential to absorb more reactive power andthe compensator should absorb reactive power to mitigate thevoltage rise problem. In case of a voltage dip, reactive powerneeds to be supplied from the compensator to compensate thereactive power absorbed by the DG unit.

C. Mitigation of Voltage Variation by Regulating the PrimaryDS Voltage VS

In conventional passive distribution networks, it is a commonpractice for DNSPs to maintain the primary DS voltage above

Fig. 5. Mitigation of voltage variation by regulating primary DS voltage.

the nominal voltage to ensure that the voltage profile of thesystem remains within the specified voltage limit. As we know

Vworst = VGENmax VS .The voltage variation can be mitigated by regulating thesending-end voltage VS , i.e., the primary DS voltage. Thiscan easily be done by using OLTCs connected to distributionnetworks, as shown in Fig. 5, from where it is seen that theprimary voltage can be regulated by using an automatic voltagecontroller. The controller senses the voltage variation betweenthe two buses. If the voltage variation is within the permissiblelimit, the controller does not work, but if the voltage varia-tion exceeds the permissible limit, the controller automaticallyregulates the voltage and thus reduces the voltage variation.However, in a more complex network, the value of this voltageand the corresponding tap position of the OLTC would have tobe optimized.

D. Mitigation of Voltage Variation by Using theGeneration Curtailment

It is important to observe that the probability of the worstcase scenario in distribution networks is generally low, andhence, it may be beneficial to accommodate a larger DER andcurtail it when the voltage at the busbar where it is connectedvaries outside the specified limit. The effect of the generationcurtailment on the voltage variation can be obtained from thefollowing equation:

PGmax PGcur + VGENmax VSR

. (20)

Equation (19) can be rewritten asVworst RPGmax RPGcur. (21)

From (21), it is seen that the voltage rise can be reduced throughthe generation curtailment. The likelihood of the coincidenceof the minimum load with maximum generation will determinethe total annual energy that needs to be curtailed. As the priceof electricity is primarily driven by the load demand and thegeneration curtailment occurs typically during the period of lowload, the value of this energy to be curtailed is relatively low.However, this approach is not suitable when there is a voltagedrop within the system.

VI. VOLTAGE LEVEL AND DG CONNECTION COST

From the analysis of the worst case voltage variation, it isseen that the voltage level at the point of the DG connection isvery important as it has a great impact on the overall profitabil-ity of both consumers and DNSPs. If a DG unit is connected to a


TABLE IVOLTAGE LEVEL AND DG CONNECTION COST

higher voltage level, there is less chance of the voltage variationwithin the network close to the customers. However, if a DGunit is connected to the vicinity of the customer, the voltagevariation due to the DG integration may affect the customersappliances. Therefore, the voltage level and the effect of voltagevariation have an inverse relationship.

The connection cost of a device into the existing distributionnetwork is also very important. These costs are determinedbased on the network access charge (NAC). Energy Australiadefines the NAC as a fixed charge (cents/day) applied to eachenergized connection point at which Energy Australias energy/demand is measured or recorded. Energy Australias NACunder different voltage levels and network categories is shownin Table I [34].

In Table I, the voltage levels are categorized as follows: lowvoltage (LV): nominally 240/415 V; high voltage (HV): nomi-nally 5, 6.6, 11, or 22 kV; and subtransmission (ST): nominally33 kV or above. From Table I, it is seen that the NAC is more forthe higher voltage level, which indicates the higher connectioncost. Due to this reason, DNSPs main target is to connect a DGunit into the LV level but this might cause the voltage variationwithin the system. On the other hand, the connection of a DGunit at a higher voltage level has a lower impact on the perfor-mance of the network in terms of the steady-state voltage profileand power quality. These two conflicting objectives need to bebalanced appropriately.

VII. SIMULATION RESULTS

The voltage level at each connection point of the load andgeneration is very important for the quality of the supply.Since there are no internationally agreed rules that define theallowed steady-state voltage range, the maximum permittedvoltage variation on each busbar is defined by some technicalregulations or specific contracts. DNSPs should maintain thevoltage variation in distribution networks within the permissiblelimit fixed by national and international standards to guaranteereliable and economic service to customers. In most cases, theallowable voltage variation along distribution networks is 6%[35] but it may vary depending on rules and regulations ofeach country. In this paper, the allowed voltage variation at thecustomer end is considered as 6% in order to demonstratethe effect of the DG integration into distribution networkswith the derived voltage variation formula. In order to validatethe derived voltage variation formula, the voltage profile of adistribution network is obtained from the derived formula andcompared with that of the existing power system simulationsoftware.

In this paper, a 15-bus Kumamoto, Japanese distributionsystem is considered, which is shown in Fig. 6. The base power

Fig. 6. Fifteen-bus Kumamoto, Japanese distribution system.

Fig. 7. Voltage profile of the 15-bus distribution system without DG: (solidline with star) PSSE; (solid line with circle) derived formula; and (two dottedlines) allowable range of voltage variation.

Fig. 8. Voltage profile of the 15-bus distribution system with DG: (solid linewith star) PSSE; (solid line with circle) derived formula; and (two dotted lines)allowable range of voltage variation.

of this distribution system is 10 MVA and the base voltage is6.6 kV; the total load on the system is 6.301 MW, 0.446 MVAr.The test system data with the distribution of loads in differentnodes can be seen in [36].


The voltage profile of the 15-bus test system is shown inFig. 7 from where it is seen that the voltages at buses 6, 15,and 11 are below the considered specified limit 6% becausethese buses are far away from the main grid supply point. Atthis point, no DERs are connected to the distribution network.The voltage profile obtained from a widely used simulation toolin power industry, called PSSE, is shown by the solid line withstars in Fig. 7. The voltage profile of this test system shouldbe similar or close to that of obtained through PSSE when thederived voltage variation formula will be used. With the derivedvoltage variation formula, the voltage profile of the 15-bus testsystem is also shown in Fig. 7 by the solid line with circles,which is very close that of obtained from PSSE.

Now, if a 6-kW synchronous generator is connected at bus4, a 2-kW PV generator is connected at bus 13, and a 3-kWwind generator is connected at bus 10, the voltage profile ofthe distribution network is shown in Fig. 8. In this case, thereshould be a voltage rise, as compared with the distributionnetwork without DG at buses 4 and 13, as well as their adjacentbuses and a voltage drop at bus 10 and its adjacent buses. Thishappens as the synchronous generator supplies both active andreactive power and the PV generator supplies active power tothe system. Moreover, this portion of the system has enoughreactive power to supply loads. On the other hand, the region atwhich the wind generator is connected is far from the main grid,and the reactive power available in this portion is not sufficientto meet the load demand. Moreover, the wind generator alsoconsumes reactive power, and this is why the voltage at bus 11,which is adjacent to bus 10, falls down outside the specifiedlimit. In Fig. 8, it is shown that the voltage profile obtainedfrom the derived formula is very close to that of obtained fromPSSE when DERs are integrated into the distribution system.

VIII. CONCLUSION

The voltage variation for a small and a large distributionnetwork has been estimated through an analytical approach, andthe derived voltage variation formula is accurate for performingthe analysis as it provides very similar results to that of theexisting power system simulation software. The worst casescenario of the distribution network is considered based on thederived formula in order to build up a relationship between thevoltage variation and maximum DG capacity. The relationshipamong voltage level, voltage variation, and DG connection costis built using an example. The approach presented in this paperis useful for the future planning and operation of distributionnetworks, as well as for the voltage control of the existingdistribution network with DG. Future works will deal with thedetailed analysis of the voltage control with different types ofDG such as CHP, wind generators, and PV.

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M. A. Mahmud (S10M13) received the Bache-lors degree (with honours, first class first position) inelectrical and electronic engineering from RajshahiUniversity of Engineering and Technology (RUET),Rajshahi, Bangladesh, in 2008 and the Ph.D. de-gree (with best thesis award) in electrical engi-neering from The University of New South Wales,Canberra, Australia, in 2012.

He served as a Radio Network Planning Engineerat Huawei Technologies (BD) Ltd. After that, he be-came a Lecturer at Khulna University of Engineering

and Technology, Khulna, Bangladesh, and in the Department of Electricaland Electronic Engineering, RUET. He is currently a Research Fellow atThe University of Melbourne, Melbourne, Australia. His research interests aredynamic stability of power systems, renewable energy integration, smart grids,nonlinear control theory, and electrical machine.

M. J. Hossain (M11SM13) received the B.Sc.and M.Sc.Eng. degrees from Rajshahi Universityof Engineering and Technology (RUET), Rajshahi,Bangladesh, in 2001 and 2005, respectively, and thePh.D. degree from The University of New SouthWales, Canberra, Australia, in 2010, all in electricaland electronic engineering.

He served as a Research Fellow in the School ofInformation Technology and Electrical Engineering,The University of Queensland, Brisbane, Australia.He was also an Assistant Professor and a Lecturer

at RUET for six years. He is currently a Lecturer in Griffith School ofEngineering, Griffith University, Gold Coast, Australia. His research interestsare power systems, renewable energy integration and stabilization, voltagestability, microgrids, robust control, electrical machine, flexible alternatingcurrent transmission system devices, and energy storage systems.

H. R. Pota received the B.E. degree from SardarVallabhbhai Regional College of Engineering andTechnology, Surat, India, in 1979; the M.E. degreefrom the Indian Institute of Science, Bangalore,India, in 1981; and the Ph.D. degree from The Uni-versity of Newcastle, Callaghan, Australia, in 1985,all in electrical engineering.

He is currently an Associate Professor at TheUniversity of New South Wales at the AustralianDefence Force Academy, Canberra, Australia. Hehas held visiting appointments at the University of

Delaware, Newark, DE, USA; Iowa State University, Ames, IA, USA; KansasState University, Manhattan, KS, USA; Old Dominion University, Norfolk, VA,USA; the University of California at San Diego, La Jolla, CA, USA; and theCentre for Artificial Intelligence and Robotics, Bangalore. He has a continuinginterest in the area of power system dynamics and control and modeling andcontrol of mechanical systems such as flexible structures, acoustical systems,and unmanned aerial vehicles.

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