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Electric Power Systems Research 111 (2014) 185–193

Contents lists available at ScienceDirect

Electric Power Systems Research

j o ur na l ho mepage: www.elsev ier .com/ locate /epsr

mpacts of residential photovoltaic power fluctuation on on-load taphanger operation and a solution using DSTATCOM

uifeng Yan, Brandon Marais, Tapan Kumar Saha ∗

chool of Information Technology and Electrical Engineering, University of Queensland, Brisbane, QLD 4072, Australia

r t i c l e i n f o

rticle history:eceived 19 November 2013eceived in revised form 13 February 2014ccepted 23 February 2014vailable online 16 March 2014

eywords:hotovoltaicV power variabilityoltage regulationap changer transformer

a b s t r a c t

Recently penetration of Photovoltaic (PV) systems in Low Voltage (LV) distribution networks has drasti-cally increased. The stochastic nature of PV output coupled with the characteristic of high R/X ratio of LVdistribution network results in a direct correlation between PV power and voltage fluctuations. Currentlydistribution networks rely heavily on existing On Load Tap Changing (OLTC) transformers to mitigate volt-age fluctuations. However, during the regulation process OLTC transformers can experience excessive tapchanging with high PV penetration, which in turn results in an increased maintenance requirement andshorter lifetime. Without the knowledge of how an increase in PV penetration impacts the operationof an OLTC, a Distribution Network Operator (DNO) cannot effectively coordinate compensation. Thispaper examines the effect of PV penetration levels on OLTC transformers and voltage regulation. Theinvestigation of tap changing frequencies and voltage profiles is done through quasi-static time-series

istribution system simulations using a residential street network and one year real world data obtained from local DNOsand research institutes. Then, a mitigation strategy is developed using a Distribution Static Compen-sator (DSTATCOM) and interaction between OLTC and DSTATCOM is also analyzed. This will enable DNOsto choose an appropriate size of DSTATCOM based on economic and technical requirements of voltageregulation.

© 2014 Elsevier B.V. All rights reserved.

. Introduction

The rapid increase in grid tied Photovoltaic (PV) systemsnstalled in the low voltage (LV) distribution network over the lastve years has resulted in significant power and voltage regulation

ssues [1–8]. With PV penetration levels on a rise due to vari-us government subsidies and incentives [9], distribution networkperators (DNOs) are now facing with an ever increasing complex-ty associated with the regulation of both power and voltage for LVistribution networks.

Integration of Distributed Generation (DG) into an LV distribu-ion network affects the voltage profile, which has been studied

n [1–5,10,11]. Ari and Baghzouz found that a PV penetration ofreater than 15% can cause significant power swing issues. At a PVenetration of 20%, the occurrence of tap changes was found to

∗ Corresponding author at: School of Information Technology and Electrical Engi-eering, University of Queensland, St. Lucia, QLD 4072, Australia.el.: +61 7 33653962; fax: +61 733654999.

E-mail addresses: ruifeng@itee.uq.edu.au (R. Yan),randon.marais@uqconnect.edu.au (B. Marais), saha@itee.uq.edu.au,ksaha@ieee.org (T.K. Saha).

ttp://dx.doi.org/10.1016/j.epsr.2014.02.020378-7796/© 2014 Elsevier B.V. All rights reserved.

be four times with that of no PV penetration [1]. Garrett and Jeter[12] suspected that higher penetrations of PV will cause problemswith voltage regulation as well as put an extra stress on voltageregulating equipment, in particular to OLTC transformers.

Reactive power support has been investigated as a form of com-pensation to mitigate the effects associated with an increased levelof DG penetration [2–4,10,13]. Firstly it was found that reactivepower is a lot less effective on distribution networks with a highR/X ratio [2]. Reactive power is useful to alleviate the associatedvoltage fluctuations; however, the addition of reactive power com-pensation was found to increase the frequency of tap changes inthe distribution network [2,4,10] as well as increase the probabil-ity of tap changing saturation [4]. Consequently, OLTC transformerswhich have been traditionally used to counteract voltage fluctu-ations in distribution systems may encounter more frequent tapchanges.

In the literature, the extent of the impact of various PV pen-etration levels on the occurrence of tap changes has not yet beenthoroughly studied using real world network data over an adequate

period of time. Most research demonstrated the quantity of extratap changes with recorded PV output and load consumption of afew days [1–3,12]. Moreover, source voltages in these simulationswere usually held constant [1,5]. Further, very little is known about

186 R. Yan et al. / Electric Power Systems Research 111 (2014) 185–193

studie

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2

s1iovu[

2

Obctv3f

Fig. 1. Overview of the

he interaction between OLTC and flexible reactive power com-ensator, such as Distribution Static Compensator (DSTATCOM). Allhese factors limit the accuracy of simulation results.

A comprehensive time dependent model that closely represents residential street, which incorporates real world network data asell as a duration that takes into account seasonal differences, is

rucial for the validity of this research. Hence, this paper utilizesearlong recorded data obtained from real world sources, whoseimelines are aligned for quasi-static time-series simulations [14].hus, the effects of differing PV penetration levels on OLTC trans-ormer tap operation frequency as well as voltage regulation cane examined with a high level of accuracy. The results of these

nvestigations provide clear indication of an increasing need onaintenance of OLTC transformers and an extended demand on

oltage regulation. If these requirements cannot be easily fulfilledhen DNOs have to limit the maximum desired PV penetration levelnder current network conditions. However, this is far from idealince it hinders future development of renewable energy systems.hus potential solutions are investigated in this paper. First, thenteraction between tap changers and DSTATCOM is examined andhen a strategy of DSTATCOM selection is developed which pro-ides valuable information to DNOs for dealing with PV poweructuations as the PV penetration level is rapidly increasing in LVistribution networks.

. Simulation system

In order to acquire results with a high degree of accuracy theimulation utilized real world data over the yearlong period fromst July 2011 to 30th June 2012. The use of the recorded data is vital

n maintaining the integrity of results as the variable propertiesf PV output power, residential load consumption and upstreamoltage change drastically through seasonal differences. All datased was obtained from local DNOs [15,16] and a research institute17,18] in Queensland, Australia.

.1. The residential network

For the purpose of investigating the PV integration effects onLTC transformer tap changes and voltage regulation at a distri-ution level, a model of a single street containing 60 houses wasonstructed (Fig. 1). The network is assumed to be a balanced

hree phase network with 20 houses connected to each phase. Theoltage of the upstream network is first stepped down through a3 kV/11 kV transformer and after 500 m it is further transformedor the end-user to a level of 415 V. The first house (House 1) is

d residential network.

located 100 m from the 10.5 kV/405 V transformer and the houseacross the street (House 2) is a further 15 m away. Such allocationscontinue downstream with a distance of 25 m apart for each of thetwo houses.

According to local DNOs – Energex and Ergon Energy [15,16]MOON conductor (AAC 7/4.75) is widely used in Queensland,Australia for the LV distribution networks at 11 kV and 415 V levels.Based on their manuals, it has an R/X ratio of approximately 0.85(R = 0.2840 �/km and X = 0.3327 �/km) [15], which is much higherthan that in transmission networks. This makes real power fluctu-ation comparably effective as reactive power fluctuation to voltagevariation.

It needs to be noted that in reality there will be several othersimilar 415 V feeders connected throughout the 500 m 11 kV line.However, only one such feeder has been considered in this study.This is because of the smoothing effect on PV power variations asso-ciated with cloud coverage [19]. Over a large area, as clouds shadeone region they have a tendency to un-shade another. Only in rarecircumstances can it be found that all regions are covered by cloudsat the same time, thus the overall power fluctuation observed froman upstream position becomes much smoother than an individualregion. Therefore, only one region is considered in this paper toexamine the effects of PV power fluctuations.

2.2. PV data

The PV data used was obtained from the University of Queens-land’s (UQ) 1.22 MWp PV system over a yearlong period withinstantaneous power recorded every minute [18]. All power log-ging systems at the three different PV sites are synchronized forthe validity of recording PV power fluctuations. The objective ofthis paper is to utilize the recorded UQ PV data to extract PV powerfluctuations, which can be used to represent PV power variabilityin residential feeders for evaluating impacts on tap changes andvoltage regulations. The UQ network was built to be extremelystrong and normally has a 12.5 MW base load (22 MW peak load)in which PV penetration accounts for only 10% or less, so there willnot be any concerns on PV power fluctuation related issues. But,many residential feeders have much weaker networks with higherPV penetration levels, which can potentially cause serious voltageproblems during cloud induced PV power fluctuations. However,no existing recorded data is available for any residential areas.

Fortunately, the UQ PV system has yearlong measured data andit is spread out across the campus over an approximate geographi-cal area of 700 m × 100 m (Fig. 2). This area is definitely larger thanmost 415 V residential feeders with 60 houses shown in Fig. 1;

R. Yan et al. / Electric Power Systems Research 111 (2014) 185–193 187

Fig. 2. Aerial view of UQ 1.22 MWp system [18].

hwitUdsiUsiP

tsspan

Mon 00 :00 Tues 00:00 Wed 00:00 Thur 00:00 Fri 00:00 Sat 00:00 Sun 00 :00 Mon 00 :00200

400

600

800

1000

1200

1400

1600

1800

2000

Days of Week

Load

Pow

er C

onsu

mpt

ion

(Wat

ts)

Fig. 4. Load data examples for one house from 16th to 22nd April 2012 [15,16].

of 3 kWp, 50% PV penetration for Phase A with 20 houses means

owever, if the PV power system at UQ can be greatly affectedithin 1 min due to cloud coverage, so too will the PV systems

n a smaller residential area. This is a pivotal reason behind whyhe UQ PV system was chosen for this analysis. In order to adaptQ’s large scale PV system data to a residential system, the UQ PVata was normalized and scaled to represent residential rooftop PVystems in the simulation. It should be noted that due to differentllumination angles existing in residential PV units in reality, theQ PV system with a more uniform illumination angle may have

lightly less power variation. This may be taken into considerationf a very precise result is required and data from individual rooftopV is available.

In accordance with the current practice of residential PV sys-ems [15,16], unity power factor control was implemented in theimulation. Fig. 3 demonstrates a sample of data showing theeasonal differences in PV power generation. Over a one yeareriod, there have been only three incidents that PV power vari-tions (�PPV = PPV-present − PPV - 1min before) reached over 67.5% and

o occurrences of over 75% was found.

Fri 00:00 Sat 00:00 Sun 00:00 Mon 00:00 Tues 00:00 Wed 00:00 Thur 00:00 Fri 00:000

200

400

600

800

1000

1200

1400

1600

Days of Week

PV

Out

put P

ower

(Wat

ts)

S

1

1

2

2

3

PV

Out

put P

ower

(Wat

ts)

(a) Winter: 1st– 7th July 2011

Fig. 3. Single 3 kWp PV syste

2.3. Load data

Load data was obtained from the real power measurement of an11 kV/415 V transformer in a typical residential area [15,16]. Realpower was recorded in half hour intervals over a one year period. Aweek worth of load data is illustrated in Fig. 4. Typical load patternswere observed – the morning/evening peak during weekdays anddaytime peak for weekends.

Due to the data logging practice of the power utilities it is impos-sible to acquire 1 min load data for individual houses. Therefore,the recorded data is normalized and scaled to represent the loadprofile of each house and collectively they show a correct load pat-tern at the 11 kV/415 V transformer. The power factor of the loadis held constant at 0.9 lagging, which is typical in Queensland’s LVnetworks [15–17].

In this study, the average nominal load of each household isassumed to be 3 kW based on the loading diversity and transformerrating (with consideration of necessary margin for temperatureeffect on thermal overload). Consequently, PV penetration level inthis paper can be defined as the percentage of total PV power ratingto total nominal load. When considering a PV system with a rating

that 10 households have installed such 3 kWp PV unit.

un 00:00 Mon 00:00 Tues 00:00 Wed 00:00 Thur 00:00 Fri 00:00 Sat 00:00 Sun 00:000

500

000

500

000

500

000

Days of Week

(b) Summer: 1st– 7th January 2012

m output power [18].

188 R. Yan et al. / Electric Power Systems Research 111 (2014) 185–193

2

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PV Power Outp ut and Load

Pow

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0.981

1.02LDC Refere nce Voltage Calculated

(p.u

.)

-3-2-101

OLTC1 Tap Position

Sta

tus

0 3 6 9 12 15 18 21 00.9

11.1

Voltage Profile for Beg inning and End of Line

Hours (24 hour forma t)

(p.u

.)

End Beginn ing

PVLoad

0 3 6 9 12 15 18 21 00.9

1

1.1Voltag e Profile for Beginning, Middle and End of Line

Hours (24 hour format)

(p.u

.)

Beg inn ing (Blue)

Middle ( Red ) End ( Black)

0123

PV Power Output

Pow

er(k

W)

0.9

1

1.10% PV Penetration

Ven

d (p.u

.)

0.9

1

1.150% PV Penetration

Ven

d (p.u

.)

1

1.1

Ven

d (p.u

.)

90% PV Penetration

Fig. 5. Line drop compensation (LDC) diagram.

.4. Line drop compensation

In order to replicate the common method employed by DNO’s ofegulating voltage at the bulk load point, the feedback method usedor controlling the OLTC is line drop compensation (LDC) [2,4,20],hich is shown in Fig. 5.

Where VLC denotes the calculated LDC reference voltage, Vreg ishe voltage measurement of the transformer secondary winding,line represents the current measured after transformer and Rcomp

nd Xcomp are estimated compensation impedance.According to local utilities practice [15,16], the targeted regula-

ion point is generally in the middle of the feeder and the commonLTC setup in Fig. 1 is that OLTC1 is set in an automatic mode with5 taps [Auto (11) – 11 taps in total including the mid-point, Tap] and 1.25% voltage regulation per tap and OLTC2 operates in aanual mode with ±3 taps and 2.5% voltage regulation per tap.owever, for some feeders, OLTC2 is in automatic mode [Auto (7)

7 taps in total including the mid-point, Tap 0]. In this paper, inrder to explore PV integration effects on tap changes and voltageegulations, different OLTC settings and combinations were investi-ated. These scenarios have been summarized in Table 1. Moreover,t an LV level to avoid the hunting effect, automatic tap changersenerally have longer delays for changing tap positions. Based onhe practice of local DNOs [15,16], this delay is normally around0–120 s at an LV distribution level.

. Simulation results

The simulation was carried out using quasi-static time-seriesethod in MatLab/Simulink [21] with the recorded data of PV out-

ut, loads and upstream voltage profiles aligning with respect toime for a yearlong period. In this way, time-dependent variablese.g. load and PV) are appropriately considered and many realis-ic combinations of these variables can be examined. However,t should be noted that the simulation did not take into accounthe cloud coverage directions and the individual load behaviors,ecause such data is not currently available. Instead, the study hasssumed an average variation of each PV and load along the feedero approximate the overall effect on feeder voltages.

For each scenario in Table 1, the network illustrated in Fig. 1s simulated with 10 different PV penetration levels for a year-ong period (0%–90%). Consequently, a vast amount of simulationesults were obtained. It is not practicable to present all results withimited space, therefore only a small fraction of results are demon-trated in this section as an example to show how an OLTC changests tap positions as well as how PV power variability affects voltageegulation. Scenario S1-1 with a 30% PV penetration level is chosenor demonstrating the effects (Fig. 6).

Fig. 6 depicts the network status on 11th December 2011. Therst two profiles on the first graph present load and PV power gen-ration for a single household. The second and third graphs show

he required tap changes of OLTC1 while regulating the mid feederoint voltage estimated by LDC. For example, at 9 am the calcu-

ated LDC reference voltage dropped out of the lower band whichesulted in OLTC1 changing its tap setting and bringing the voltage

Fig. 6. Scenario S1-1 with 30% PV from 11th December 2011.

back into bounds. The last graph compares the voltage profilesbetween the beginning, the middle and the end of the 415 V feeder.It can be noted that the voltage difference was larger during theevening peak but it reduced during daytime when load consump-tion was low and PV generation was high. It is also worth notingthat the voltage profile for the middle of the line is much closer tothat of the end of the line. Because the first half of the line under-takes nearly all loading current of the feeder, which causes muchmore voltage drop than that of the middle-to-end section.

Fig. 7 shows how PV power fluctuations induce resultant fluctu-ations in network voltages. As can be seen in this three-day periodthe voltage at the end of the line was more significantly affected byhigher PV penetration and there were more serious voltage vari-ations and voltage limit (±6% based on the practice in Australia[15,16]) violations as the level of PV penetration increased.

0 12 0 12 0 12 00.9

Duration (hours): 11th - 13th December 2011

Fig. 7. Scenario S1-1 with 0%, 50% and 90% PV from 11th to 13th December 2011.

R. Yan et al. / Electric Power Systems Research 111 (2014) 185–193 189

Table 1Summary of simulated scenarios.

Scenarios Sub scenarios OLTC1 (33 kV/11 kV) OLTC2 (11 kV/415 V)

Tap changer (total taps) Vreg/tap or tap position Tap changer (total taps) Vreg/tap or tap position

Scenario 1 S1-1 Auto (11) 1.25% Manual 0 tapS1-2 Auto (7) 2.5% Manual 0 tap

tap

tap25%

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Scenario 2 S2-1 Manual 0

S2-2 Manual 0

Scenario 3 S3 Auto (11) 1.

. Summary and analysis of simulation results

A detailed analysis of the time series results has been presentedn the last section to give a comprehensive understanding of theystem operation. However, it is neither an efficient nor effectiveeans of recapping simulation results and concluding findings. In

his section, tap position changes and voltage violation occurrencesre summarized using tables to clearly compare operational per-ormances between different scenarios. Then if required, results ofables 2 and 3 can easily be extracted. For example, Fig. 8 shows taphange trend with an increase in PV penetration levels (0%–90%) forcenario S2-1. These results are analyzed as follows.

1) Within a major scenario – sub-scenario comparison(a) S1-1 and S1-2

Both S1-1 and S1-2 scenarios feature an automatic tapchanger at the 33 kV/11 kV transformer (OLTC1). The resultsshow that tap changes were almost not affected by PV pen-etration levels. This was due to the small current variations(less than 15 A on the 11 kV side) induced by PV power vari-ations. It was not significant enough to cause the estimatedvoltage of the LDC to pass outside of the bands. Meanwhile,

on the 415 V side over/under voltage occurrences drasti-cally increased with PV penetration. Compared with S1-1,S1-2 has a larger voltage regulation per tap (less sensitive)

able 2ummary of tap changes in different scenarios.

Sub scenarios S1-1 S1-2 S2-1 S2-2 S3

OLTC1 OLTC2

0% 1266 429 2752 469 1270 87510% 1266 429 2940 549 1268 89320% 1266 429 3180 693 1268 93730% 1266 429 3556 877 1268 105140% 1270 429 4292 1013 1268 124350% 1270 429 5078 1137 1268 138360% 1268 431 5962 1313 1270 152370% 1268 431 6540 1621 1272 165180% 1268 431 6822 2071 1270 189190% 1268 433 7002 2467 1270 2169

able 3ummary of over/under-voltage occurrences at the end of the feeder.

Sub scenarios S1-1 S1-2 S2-1 S2-2 S3

0% 453a 684 2 2 610% 453 684 8 2 620% 453 701 8 8 630% 453 880 8 8 640% 525 1813 8 8 750% 605 5016 8 8 760% 1409 12,570 8 8 770% 2465 23,185 8 8 880% 13,462 38,038 8 8 1290% 22,760 52,887 8 9 23

Over/under-voltage occurrence is counted every 30 s. This is duration based ratherhan event based.

Auto (11) 1.25%Auto (7) 2.5%Auto (7) 2.5%

and a broader band, so it comes as no surprise that S1-2experienced less tap changes per annum, which resulted inmore voltage violation occurrences.

(b) S2-1 and S2-2With the automatic tap changer (OLTC2) located closer to

loads and PV systems voltage regulation saw a tremendousimprovement. Again, due to the less sensitive tap settingsin S2-2 less tap changes were observed. Moreover, it isworth noting that in Fig. 8 the occurrences of tap changesincreased at a higher rate after 30% PV penetration andslowed down when PV penetration reached 60%. This isanalyzed as follows:• When PV penetration is very low the majority of PV

power fluctuations are not significant enough to causetap changes. Only occasionally when the estimated LDCvoltage is drifted to a level close to the band limits a rel-atively small �PPV will push the LDC voltage outside theboundaries resulting in more tap changes. Otherwise, theextra tap changes can only be caused by substantial �PPV,which does not often occur according to the statistics.

• When PV penetration is very high, theoretically evensmall �PPV can greatly affect the LDC reference voltageleading to additional tap changes, so the tap changingoccurrences should increase in a more rapid pace. How-ever, higher PV penetration levels mean an even widervoltage regulation range. When this range exceeds theregulatory capability of the OLTC, tap position will bemore prone to saturation and therefore lose the abilityto regulate voltage. Therefore, the increase of tap changesslowed down. Further, it can be noted that the saturationdoes not necessarily lead to more voltage violations at theend of the feeder as shown in Table 3. This is due to the factthat when the LDC reference voltage is out of the bound,it only indicates the line voltage profile at the mid-point

deviates from the desired target. However, there may stillbe plenty of headroom from the network voltage limits.

(2) Between major scenarios – major scenario comparison(a) S1 and S2

0 10 20 30 40 50 60 70 80 902000

3000

4000

5000

6000

7000

8000

PV Penetration Le vel (%)

Occ

urre

nces

Fig. 8. Tap changes in Scenario S2-1 with different PV penetration levels.

190 R. Yan et al. / Electric Power Systems Research 111 (2014) 185–193

TCOM

Fig. 9. DSTA

If only considering voltage regulation due to PV powerfluctuations automatic tap changers should be placed closeto loads and PV systems. However, it should be noted thatthis alteration can result in more tap changes which willincrease maintenance costs and shorten OLTC lifetime.

(b) S1, S2 and S3In reality, there will be more similar 415 V feeders

connected to the same 11 kV feeder. In order to reg-ulate 11 kV voltage due to load and upstream voltage

0.95

1End of Li

V (p

u)

-5

0

5OLTC T

Sta

tus

Fri Sat Sun Mo n

-50

0React ive Power Sup

Da

kVA

R

01.02.0

PV Power

Ppv

(kW

)

Fri Sat Sun Mo n-50

0Rea ctive Power Sup

D

Qst

at (k

Var

)

Fri Sat Sun Mon-3-2-101

Overall Ppv : Sloa d (blue) a

T

Rat

io

PV O utp ut Power

Fig. 10. Scenario S2-1 (50% PV) with DSTATCOM (non-restrained):

structure.

changes an automatic tap changer (OLTC1) is still neededin a 33 kV/11 kV transformer. Moreover, OLTC2 doesexist in some feeders; therefore this is the reason whyscenario 3 (with both OLTCs) is conducted. It required moretap position changes than S1-1, S1-2 and S2-2, but much

fewer than S2-1. Its over/under voltage violation was a lotbetter than S1 and marginally worse than S2. If OLTC2 inS3 were set to 1.25%/tap with 11 taps the total tap changesin S3 should still be much lower than those of S2-1, but its

ne Voltage

ap Status

Tue Wed Thu Fr i

plied by DSTATCOM

ys

pe r House

Tue Wed Thu Fri

plied by DSTATCOM

ays

Tue Wed Thu Fri

nd Qstat : Sload (red) Ratios

ime

(Single PV Unit)

simulation result examples from 10th to 16th February 2012.

stems Research 111 (2014) 185–193 191

5

ftbhr

e1vtS

(

(

(

5

tcwogtatipneotct

vtb

TC

0

1000

2000

3000p

Wat

ts

-60

-40

-20

0Reactive Power Supplied by DSTATCOM

kVA

R

11am 11:39a m12pm 1p m 2pm 3pm

0.9675

0.98

0.99 25

LDC Reference Voltage Calculated

Time

V (p

u)R

atio

11a m 11:39a m 12p m 1pm 2p m

-2

-1

0

1

Overall Ppv : Sload (blue) and Qstat : Sload (red) Ratios

Time

PV Output Power (Single PV Unit)

(a) With DSTATCOM

PV Output Power (Single PV Unit)

0

1000

2000

3000W

atts

2

4

6OLTC Tap Change r Status

Sta

tus

11am 11:39am 12p m 1pm 2p m 3p m0.96

0.98

1

1.02LDC Reference Voltage Calculated

Time

V (p

u)

(b) Without DSTATCOM

R. Yan et al. / Electric Power Sy

voltage regulation should be comparable to S2-1. It can benoted that for 11 kV/415 V transformers with manual tapchangers, modifying or replacing them with automatic tapchangers can be expensive. For example, an additional OLTCat an LV level could cost around 20,000 Australian dollars(AUD) according to vendors in the local area.

. Interaction between OLTC and DSTATCOM

In order to mitigate the problems of excessive tap changes andrequent voltage violations caused by PV power fluctuations, poten-ial solutions should be investigated. A DSTATCOM has been chosenecause it is a proven technology with a reasonable price (Fig. 9). Itas the ability of injecting and absorbing reactive power for voltageegulation.

First, the interaction between DSTATCOM and OLTC needs to bexamined. In this study a DSTATCOM is placed at the bus of house3 according to local DNOs common practice (Fig. 1). The targetoltage for the DSTATCOM was set to 0.98 pu, which in turn keepshe end of the line voltage above standard practice limits. Scenario2-1 with 50% PV penetration is chosen for the following reasons.

1) There are some 11 kV/415 V feeders having the second OLTC(OLTC2), which is corresponding to Scenario S2-1.

2) According to the local DNOs some feeders have already had aPV penetration level of more than 30%, thus 50% PV penetrationis becoming a concern.

3) The analysis of this case will shed some light on voltage reg-ulation of 11 kV/415 V feeders which do not have OLTC2. Thecombination of OLTC and DSTATCOM may be a promising solu-tion.

.1. Required DSTATCOM size for precise voltage regulation

DSTATCOM size was not restrained in this part in order to findhe required size for a precise voltage regulation at the DSTATCOMonnection point. Simulation results showed that throughout thehole year there have not been any tap position changes of OLTC2

r occurrences of voltage violation at the end of the feeder. Powereneration of the DSTATCOM varied from 52 kVar/phase inductiveo 10.7 kVar/phase capacitive, which gives a ratio of 0.5:0.8667:1.0mong power rating of the PV, the DSTATCOM and the load forhe 50% PV penetration scenario. A fraction of simulation resultss shown in Fig. 10 as an example for demonstrating the systemerformance with DSTATCOM over a yearlong period. It can beoted from the last graph in Fig. 10 that the residential load gen-rally dropped to a low level during the daytime when PV powerutput became significant (a high Ppv to Sload ratio as indicated inhe graph). As a result, DSTATCOM output (inductive) increased toounter the PV effect, but this action was considerably reduced ashe load peaked in the evening.

If the results are compared to 5078 tap changes and eight voltageiolations of S2-1 (50% PV without DSTATCOM) in Tables 2 and 3,his performance is very desirable. It effectively means OLTC2ecomes obsolete with the presence of a 52 kVar/phase DSTATCOM,

able 4omparison of performances with different DSTATCOM sizes.

DSTATCOM size (per phase) For precise regulation 20 kV

QDSTATCOM (kVar) [−52 10.7]a [–20

OLTC2 tap changes 0 103

Vend (pu) (all) [0.973–0.986] [0.95Vend (pu) (eliminate once a year incident) – –

a Minus means inductive.

Fig. 11. System response to PV power fluctuations from 11 am to 3 pm on 17thFebruary 2012.

so this solution solves the issue of any cost associated with addingOLTC2 for voltage regulation. However, a DSTATCOM of this size(52 kVar × 3 phases) is currently very expensive – around 60,000AUD according to local vendors and power utilities.

DSTATCOM is a reactive power compensation device but PV

ar 10 kVar 5 kVar Baseline 0 kVar

20] [–10 10] [–5 5] 01056 2000 5078

9–0.998] [0.934–1.008] [0.928–1.013] [0.925–1.040][0.950–1.008] [0.954–1.013] [0.959–1.026]

power fluctuations are related to real power. To better analyzethe interactions between DSTATCOM, OLTC and PV power fluc-tuation, firstly an example is illustrated in Fig. 11 to show howthe network with DSTATCOM responds to substantial PV power

192 R. Yan et al. / Electric Power Systems Research 111 (2014) 185–193

Table 5Comparison of implementing DSTATCOM and PV inverter reactive power control.

Aspects DSTATCOM PV inverter reactive power control

Cost • Additional purchase and maintenance cost for power utilities.• Complex cost sharing arrangement for PV and non-PVhouseholds.

• Utilization of PV inverter capability and no extra purchase andmaintenance cost.• Cost for upgrade of PV systems installed before the release of newstandard.

PQ control Without storage:• Q control only• Not related to P

Two possibilities:• P Priority: reduce Q capability• Q Priority: sacrifice P generation

Voltage regulationcoordination

• For single device: no coordination issues.• For multiple devices: coordination is required.

• Different types of inverters: with different time delays, gains and timeconstants in sensors and controllers. Networks may suffer problems fromcontrol hunting and oscillating between inverters.• Coordination may be needed.

Policy (fairness) • Fair for all inverters.tem.

• At the beginning of a feeder, rarely any regulation is required.

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• May not be fair financially for customer without a PV sys

uctuations from 11 am to 3 pm on 17th February 2012. It cane noted that the LDC voltage target was set to 0.98 pu in order toork with DSTATCOM. Originally this voltage reference was 0.99 puithout DSTATCOM for a better voltage regulation.

In Fig. 11(a) it has been observed that PV power considerablyuctuated during the presented 4 h with the maximum variationt 11:39 am of 73.9%/min. However, the calculated LDC refer-nce voltage did not change significantly and it remained withinhe defined limits (0.98 ± 0.0125 pu). Therefore there were no taphanges in OLTC2. In the same scenario without DSTATCOM shownn Fig. 11(b), at 11:39 am the PV power surge was so severe that itaused the calculated LDC voltage to increase by 0.0263 pu which isreater than the range of the LDC band [the third graph of Fig. 11(b)].his means there should definitely be a tap change due to this PVower surge shown in the second graph.

One possible explanation for the insensitive LDC voltage withhe presence of the DSTATCOM can be as follows. The DSTATCOMith enough capacity had the ability of generating the amount of

eactive power required to hold the voltage at house 13 constant at.98 pu. At the same time the LDC voltage target was also aiming at.98 pu in a similar region (house 11 to house 13) and this regula-ion task was accomplished by the DSTATCOM in a much more rapidate. Therefore, the estimated LDC reference voltage magnitudesaried insignificantly shown in the third graph of Fig. 11(a). There-ore it is effectively demonstrated that the OLTC becomes inactivend may be replaced by a huge DSTATCOM.

.2. Smaller DSTATCOM size

As mentioned in the last part, a 150 kVar three-phase DSTAT-OM may be oversized and is very expensive. Moreover, theurpose is to reduce the tap changing frequencies and maintenanceosts of OLTC2 and extend its lifetime rather than removing it fromhe network. Therefore, different sizes of DSTATCOM units werexamined. As shown in Table 4, with the reduction of DSTATCOMapacity the voltage range at the end of the line is becoming widernd the OLTC2 tap changes are getting larger. This tendency willead to a very promising solution.

The results show the following advantages.

1) Tap changes: 2000 tap changes were observed. Comparedwith 5078 tap changes of the baseline case, this is a greatimprovement. Moreover, this number is even smaller than thecase without any PV systems (2752 changes in Table 2). Thisdemonstrates a significant benefit for integrating a very small

DSTATCOM unit to the distribution system.

2) Voltage regulation: after eliminating the once per year undervoltage incident, the voltage range at the end of the line wascomfortably within the local DNO’s 6% voltage limits.

• PV systems toward the end of a feeder may be responsible for regulationduring both PV power peak and load peak. Their inverter lifetime could beaffected. A fair policy needs to be designed.

(3) Cost: a 15 kVar (3-phase) DSTATCOM only costs around $8000AUD. Financially this should be a very promising solution.

The reasons for improvement by using DSTATCOM can be ana-lyzed as follows. PV integration tends to cause over-voltage withreverse real power flow, so DSTATCOM is likely to become induc-tive during regulation to bring the voltage down. Therefore, thepower factor seen from the upstream network will decrease, whichwill affect OLTC2 (11 kV/415 V) operation. According to LDC func-tion presented in Fig. 5, this power factor decrease caused by feederreal power consumption drop (due to PV generation) and inductivereactive power increase (due to DSTATCOM compensation) tendsto stabilize the calculated LDC reference voltage and consequentlyreduces OLTC2 tap changes. Since LDC decides tap change basedon line voltage drop the line voltage drop becomes more stableif real power declines and reactive power increases. As a result,the number of tap changes will decrease. This is the reason whyDSTATCOM helps to reduce tap change frequency as shown inTable 4, and larger DSTATCOM can have more impacts on OLTCtap changes.

5.3. Strategy of selecting a solution

The strategy of selecting a solution based on the analysis of thisstudy is summarized as follows:

(1) Specify performance criteria regarding annual tap changinglimits and allowable over/under voltage occurrences.

(2) Conduct Quasi-Static Time-Series study to determine the tech-nical specifications of the potential solutions (e.g. the requiredsize of DSTATCOM):(a) If there is no OLTC2 at the 11 kV/415 V level: solution: an

additional OLTC with DSTATCOM (this is effective and canbe cheaper than the DSTATCOM only solution).

(b) If OLTC2 already exists at the 11 kV/415 V level: solution:DSTATCOM.

(3) Compare the cost of each solution and select an economicalsolution.

It can be noted that currently the battery storage solution ismuch more expensive than the DSTATCOM solution so storage hasnot been considered in this study. Further, it is also important tonote that it is up to the discretion of the DNO to assess and make adecision as to which solution is going to be more financially viable.

5.4. Further discussion

In some countries like Japan and Germany, PV inverter reac-tive power control has recently been required in their standards. A

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omparison between this control scheme and DSTATCOM is sum-arized in Table 5.

. Conclusions

This paper investigates OLTC tap changes and voltage regula-ions issues due to PV power variability in distribution networksy using Quasi-Static Time-Series simulations with yearlong realorld data. Different tap changer configurations and PV penetra-

ion levels are examined to extract the trend of network response.It has been found that currently used common OLTC setup (Sce-

ario 1, OLTC1 only) in the LV networks may not effectively regulateownstream voltages due to PV power fluctuations. However, ifap changers are moved downstream (Scenario 2, OLTC2 only),oltage regulation performance can be considerably improved, butap position changes can be significantly increased. This will reducehe life of tap changers and result in much higher maintenance.f both OLTC1 and OLTC2 are accessible (Scenario 3), the networkoltage performance would also experience a great improvement,hich is comparable to Scenario S2-2. However, if the second OLTC

OLTC2) is not available in a feeder, this downstream OLTC con-guration will involve a cost of modifying an existing manual taphanger or attaching an additional automatic tap changer.

Further investigation of other solutions for mitigating thempacts caused by PV power fluctuations was also conducted. First

big enough DSTATCOM was introduced to S2-1 with 50% PV pene-ration to study the interaction between OLTC2 and DSTATCOM. As

faster regulation device, DSTATCOM demonstrated its ability ofeplacing the OLTC located in close proximity to the residential load.owever, such large DSTATCOM may be overrated and not econom-

cal for the application. Instead, the quasi-static time-series resultshowed that a DSTATCOM as small as 5 kVar/phase can tremen-ously reduce tap changes and improve voltage regulation. For theeeders without OLTC2, the solution of OLTC2/DSTATCOM combi-ation can be cheaper than the DSTATCOM alone solution. Thisrovides an extremely useful solution to the DNOs for networknhancement. Power utilities can follow the strategies proposedn this paper to evaluate the technical and financial viability ofotential solutions and thus make their own decisions for system

mprovement.

cknowledgments

The authors would like to give sincere gratitude to Energex,rgon Energy and UQ Properties & Facilities Division for their sup-orts in this research with the real world data.

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Research 111 (2014) 185–193 193

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