POTENTIAL TECHNICAL IMPACTS OF ROOFTOP SOLAR GENERATION … · Rooftop Solar Power Generation Project (RRP SRI 50373-002) POTENTIAL TECHNICAL IMPACTS OF ROOFTOP SOLAR GENERATION ON

Rooftop Solar Power Generation Project (RRP SRI 50373-002)

POTENTIAL TECHNICAL IMPACTS OF ROOFTOP SOLAR GENERATION ON LOW VOLTAGE DISTRIBUTION NETWORKS

A. Introduction 1. Sri Lanka experienced a rapid growth in installed rooftop solar photovoltaic capacity with the introduction of the net-metering scheme in 2008. The growth further increased with the introduction of the two new schemes (net accounting and net plus) in September 2016. Net-metered customers generally sized their rooftop solar photovoltaic capacity such that the electricity generation matches with their monthly electricity consumption. Electricity utilities, Ceylon Electricity Board (CEB) and Lanka Electricity Company Limited (LECO), observed a limited amount of net exports to the grid on each monthly billing date. Since customers will be paid for the exported electricity in the newly introduced net accounting and net plus schemes, they are now free to over-size their rooftop solar photovoltaic capacity up to their contract demand to generate more electricity than what they consume within a month. The government has set a target of 200 megawatts (MW) of solar power generation by 2020 and 1,000 MW by 2025. These policy targets are expected to cause an increase in the rooftop solar photovoltaic penetration in the grid. 2. Widespread connection of solar photovoltaic may have three types of technical impacts on a country’s electric power system: (a) the intermittent nature of solar photovoltaic power generation requires increased spinning reserve at generation level, which in turn would require additional investment and operating costs; (b) the inability of solar photovoltaic to support in system frequency management makes a power system with solar photovoltaic less stable than otherwise; and (c) a high penetration of solar photovoltaic capacity have impacts on the medium and low voltage distribution network by way of voltage changes, line or transformer overloading, or power quality issues. 3. The key technical impacts of solar photovoltaic at the grid level, by way of impacts on the spinning reserve requirements and frequency stability, are not covered in this study. 4. This study is to analyze and quantify the impacts of solar photovoltaic power generation on the low voltage distribution network. The study covered impacts on (i) distribution transformer loading level, (ii) distribution feeder loading level, (iii) distribution feeder voltage level, (iv) distribution losses, and (v) harmonic level. The study examined the present status as well as impacts at future solar photovoltaic penetration levels. This supplementary appendix elaborates the methodology and the results of the study. B. Methodology 5. Upon request by the study team, LECO and CEB provided network and customer data for two distribution schemes within their distribution areas. Based on the information received, two case studies were developed. From here onwards, case studies of LECO and CEB distribution schemes are referred as Case Study 1 and Case Study 2, respectively. This section explains the methodology followed in the study, which is summarized in Annex 1. Each study covers a local area served by a distribution transformer, over a network of radial distribution feeders (lines) operating at 400 volts (three phase) or 230 volts (single phase).

http://www.adb.org/Documents/RRPs/?id=50373-002-3

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1. Selection of Case Studies

6. Case Study 1 represents a highly loaded transformer serving a distribution network with a relatively high penetration of rooftop solar photovoltaic capacity, whereas Case Study 2 represents a lightly loaded transformer serving a network with a low penetration of rooftop solar photovoltaic capacity. Table 1 summarizes the details of the two case studies. Schematic diagrams of Case Studies 1 and 2 are given in Annex 2 and Annex 3, respectively.

Table 1: Summary of the Two Case Studies Case Study 1 Case Study 2

Location Sri Jayewardenepura Kotte (Western Province)

Ampara (Eastern Province)

Distribution licensee LECO CEB Region 2 Transformer capacity 250 kVA 160 kVA Present maximum demand as a % of transformer capacity

69% 23%

Number of customers served 336 320 Number of customers with rooftop solar photovoltaic generators

24 2

Number of outgoing LV feeders from the transformer

3 3

CEB = Ceylon Electricity Board, kVA = kilovolt amperes, LECO = Lanka Electricity Company Limited, LV = low voltage. Source: Ceylon Electricity Board and Lanka Electricity Company Limited.

2. System Modelling

7. Modeling was carried out, starting from high voltage terminals of the distribution transformer up to customer metering points including solar photovoltaic generators, using a load flow analysis software.

a. Feeder Modelling

8. Both case studies consist of three feeders each. A summary of feeder details is given in Table 2.

Table 2: Summary of Feeder Data Case Study 1 Case Study 2

Conductor type 3 phase ABC 3 phase AAC Cross Section Type 1: 3×70 mm2 + 54 mm2

Type 2: 3×50 mm2 + 54.6 mm2 3×60 mm2 + 60 mm2

DC Resistance (ohm/km) Type 1: Phase: 0.443, Neutral: 0.63 Type 2: Phase: 0.641, Neutral: 0.63

Phase: 0.523, Neutral: 0.523

Phase conductor current carrying capacity

Type 1: 213 A Type 2: 168 A

263 A

Inductance Type 1: 0.26 mH/km Type 2: 0.27 mH/km

0.93 mH/km

Conductor material Aluminum Aluminum Single phase service connection cable

Al/PVC 16 mm2 Al/PVC 16 mm2

Three phase service connection

3×25 mm2 + 54.6 mm2 ABC 3×25 mm2 + 54.6 mm2 ABC

Length of main feeder Length of main feeder

Feeder 1 511 m 1,009 m Feeder 2 389 m 425 m Feeder 3 607 m 635 m

A = ampere, AAC = all aluminum conductor, ABC = aerial bundled cable, AI = aluminum, DC = direct current, km = kilometer, m = meter, mH = millihenry, mm2 = square millimeter, PVC = polyvinyl chloride. Source: Ceylon Electricity Board and Lanka Electricity Company Limited.

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b. Transformer Modelling

9. Technical specifications of transformers in the case study are given in Table 3.

Table 3: Summary of Transformer Technical Specifications Case Study 1 Case Study 2

Capacity (kVA) 250 160 Vector group DYn11 DYn11 No load loss (W) 670 500 Load loss (W) 3,295 2,575

DYn = delta star neutral connection, kVA = kilovolt ampere, W = watts. Source: Ceylon Electricity Board and Lanka Electricity Company Limited.

c. Customer Modelling

10. Location, tariff category, and tariff group were considered when modelling customers. The number of customers are given in Table 4. Customer distribution in terms of tariff category and blocks (for household customers) is given in Annex 4.

Table 4: Customers in each feeder Case Study 1 Case Study 2

Number of customers in Feeder 1 154 128 Number of customers in Feeder 2 77 30 Number of customers in Feeder 3 105 162 Total number of customers 336 320

Source: Ceylon Electricity Board and Lanka Electricity Company Limited.

11. The electricity consumption in April 2017 and the average monthly electricity consumption of each customer were available for Case Study 1 and Case Study 2, respectively.The most suitable load profile for each customer was selected from a set of load profiles, considering the tariff category and monthly electricity consumption. A sample set of daily load profiles for each tariff group in the domestic tariff category are shown in Figure 1.


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Note: One representative daily load profile is shown for one household in each consumption block. The

consumption blocks are aligned with the blocks of Sri Lanka’s increasing block-tariffs.

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d. Solar Photovoltaic Systems Modelling 12. To study the variation of rooftop solar photovoltaic electricity generation with time of the day, power output of solar photovoltaic systems was calculated using measured Global Horizontal Irradiance (GHI) profile, obtained from the solar irradiance measuring station in Kilinochchi.1 Power generation is proportional to the GHI. Daily power generation curves for 1.0 kilowatt peak (kWp), 1.5 kWp and 2.5 kWp rooftop solar photovoltaic systems are shown in Figure 2.

13. It is important to note that the rated direct current (dc) power capacity of the solar photovoltaic system will not be injected even when the solar irradiance is maximum due to the mismatch between standard test conditions and normal operating conditions. For example, a 2.5 kWp system will inject only 1.63 kW at 12:00 noon. Even though the maximum power will not be injected, the monthly electricity generation will be equal to the design value. This mismatch can be avoided if the dc capacity of the system is increased to be more than the alternating current (ac) capacity of the inverter. Typically used dc to ac design ratio is 1:2. However, this is not practiced by solar photovoltaic suppliers in Sri Lanka. Therefore, dc to ac ratio of 1 was used in modelling solar photovoltaic systems.

1 A modern solar irradiation measuring station was installed under ADB. 2011. Technical Assistance to the Democratic Socialist Republic of Sri Lanka for Preparing the Clean Energy and Network Efficiency Improvement Project. Manila (TA 7837-SRI, Part 2: Wind and Solar Resource Assessment) in the Northern Province of Sri Lanka.

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Figure 2: Daily Power generation Curves of Solar PV Systems

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Note: Average daily solar irradiance in March was considered in this study, as Sri Lanka receives the maximum solar irradiance in March. Source: Solar irradiance measuring station in Kilinochchi.

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e. Harmonic Modelling 14. A code of practice for grid connected photovoltaic power system standards are being finalized by the Sri Lanka Sustainable Energy Authority in association with Sri Lanka Standards Institution (SLSI). This standard refers the IEC 61727:2004 standard, which specifies the harmonic current limits. These current limits were used as the source emission levels in this study. It was assumed that harmonic orders of individual inverters are equal to maximum allowable limit in the standard. The inverter output harmonic current limits are given in Table 5.

Table 5: Odd and Even Harmonic Limits in the Standard

Odd Harmonics Current Limits

Odd harmonic order number Limits for each individual odd harmonic based on

percentage of fundamental 3, 5, 7 & 9 4.0% 11,13 & 15 2.0% 17, 19 & 21 1.5% 23, 25, 27, 29, 31 & 33 0.6%

Even Harmonic Current Limits

Even harmonic order number Limits for each individual even harmonic based on

percentage of fundamental 2, 4, 6 & 8 1.0% 10 – 32 0.5%

Source: Asian Development Bank estimate.

3. Assumptions

15. Modelling of the two case studies was carried out based on the following assumptions: (i) for Case Study 1 information about the phase, from which each customer is supplied, was not available, and therefore, single phase customers were distributed among the three phases in such a way that the three phases are balanced; and (ii) power factor of all loads and solar photovoltaic systems were assumed to be 0.95 lagging and unity, respectively.

4. Solar Photovoltaic Capacity Penetration Scenarios 16. To analyse the impacts of different solar photovoltaic capacity penetration levels, six scenarios were modelled in Case Study 1. Customers in Case Study 1 belong to high electricity consumption groups and the potential of installing solar photovoltaic systems by them is high. Therefore, two scenarios were developed to analyse the impact of installing solar photovoltaic systems by the potential customers. The fifth scenario was modelled to analyse the impact of installing a solar photovoltaic system with a higher capacity in the existing network while keeping the capacities of existing solar photovoltaic systems unchanged. Scenario 6 assumes that all customers consuming more than 120 kilowatt (kWh) per month will install net-metered solar photovoltaic systems. 2 Table 6 summarizes the study scenarios of Case Study 1, while details of solar photovoltaic systems in each scenario are given in Annex 5.

2 Demand analysis conducted as part of this study reveals that at an 8% interest rate, installing a net-metered or net-accounting solar photovoltaic system is viable for customers whose monthly electricity consumption exceeds 120 kWh.

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Table 6: Scenarios Analysed in Case Study 1

Scenario Description

Number of Solar Photovoltaic

Systems Cumulative Capacity of Solar Photovoltaic Systems (kW)

1 Without solar photovoltaic systems 0 0 2 Present network 24 108 3 Solar photovoltaic capacity is equal to

50% of the transformer capacity 27 128

4 Solar photovoltaic capacity is equal to 75% of the transformer capacity

38 189

5 One 42 kWp solar photovoltaic system added to the present network

25 150

6 All customers whose monthly electricity consumption is more than 120 kWh install net-metered solar photovoltaic systems

220 567

kWh = kilowatt hour, kWp = kilowatt peak. Source: Asian Development Bank estimates.

17. Customers in Case Study 2 belong to low electricity consumption groups and it is unlikely that they will install solar photovoltaic systems at the prevailing solar photovoltaic system costs. Therefore, when defining study scenarios, in place of a gradual increase in solar photovoltaic capacity penetration, addition of one high capacity solar photovoltaic system was considered. Impacts can vary with the location of the solar photovoltaic system. Therefore, three scenarios were modelled to assess the changes in impacts when the Point of Connection (PoC) of the high capacity solar photovoltaic system varies along the feeder. Table 7 summarizes the scenarios in Case Study 2.

Table 7: Scenarios Analysed in Case Study 2

Scenario Description Number of Solar

Photovoltaic Systems

Cumulative Capacity of Solar Photovoltaic

Systems (kWp)

1 Without any solar photovoltaic systems 0 0 2 Present network 2 7 3 One 42 kWp solar photovoltaic system

at a location closer to the transformer 3 49

4 One 42 kWp solar photovoltaic system in the middle of a feeder

3 49

5 42 kWp solar photovoltaic system at the end of a feeder

3 49

kWp = kilowatt peak. Source: Asian Development Bank estimates.

C. Results 18. This section presents the simulation results of Case Study 1 and Case Study 2.

1. Results of Case Study 1 19. Six studies were carried out under Case Study 1.

a. Distribution Transformer Loading Level 20. Distribution transformer loading levels in 15-minute intervals were calculated for a 24-hour period for each scenario, as shown in Figure 3.

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21. All load profiles plotted in Figure 3 are simulated results. Since the actual profile of power generation from the rooftop solar photovoltaic systems is not available for all scenarios, profiles were assumed to be similar over the period of 6:00 p.m. to 6:30 a.m. Scenario 1 profile represents the cumulative load profile including system power losses. Day peak load due to connected loads is 49% of the transformer rated capacity. As connected solar photovoltaic capacity grows, day-time loading of the transformer decreases. In Scenario 4, power flow from the low voltage distribution network backwards to the medium voltage network was observed, and that increases the transformer loading slightly more than in Scenario 3, during periods when reverse power flow occurs. In Scenario 6, transformer loading level exceeded its rated capacity for a very short period. However, there is a probability for transformer loading level to even exceed 100% if load is reduced from the assumed levels and large reverse power flows were observed under such conditions.

b. Feeder Loading Level 22. Observed maximum feeder loading levels during daytime, as a percentage of conductor rated current carrying capacity, are given in Table 8. Maximum line loading in Scenario 1 (without solar photovoltaic systems) was observed at 11:30 a.m. when power demand is relatively high. When solar photovoltaic capacity penetration increases loading level at 11:30 a.m. decreases. For Scenarios 2 to 4, maximum line loading level was observed at 4.30 p.m. when solar photovoltaic power generation is low. In Scenario 6, 75.3% line loading was observed at

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Figure 3: Calculated Transformer Loading Levels of Case Study 1

Scenario 1 (Without Solar)

Scenario 2 (Present Network)

Scenario 3 (Solar PV Capacity = 50% Trasnsformer Capacity)

Scenario 4 (Solar PV Capacity = 75% Trasnsformer Capacity)

Scenario 5 (Single 42 kW Solar PV System)

Scenario 6 (All customers above 120 kWh/month)

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11:45 a.m. due to reverse power flow. Night time peak line loading level is 48.2%, and it occurs at 8:15 p.m. In a distribution scheme with high electricity consuming customers, the problem of feeder overloading will be more significant in the night time (due to load growth) compared with the day time (due to solar photovoltaic generation), unless the solar photovoltaic capacity penetration level is extremely high.

Table 8: Calculated Maximum Line Loading Levels, Case Study 1

Maximum Line Loading % Time of occurrence

Scenario 1 37.2% 11:30 a.m. Scenario 2 29.4% 4:30 p.m. Scenario 3 28.5% 4:30 p.m. Scenario 4 23.9% 4:30 p.m. Scenario 5 29.4% 4:30 p.m. Scenario 6 75.3% 11:45 a.m.


c. Feeder Voltage Levels

23. Voltage reduces along the feeder when moving from the transformer towards the remote end of the feeder due to conductor impedance. When solar photovoltaic systems are connected, voltage along the feeder can increase or decrease depending on connected loads, solar photovoltaic capacity and PoC of solar photovoltaic systems. It is observed that the highest voltage rise occurs at 11:00 a.m. in all scenarios, and Figure 4 shows the voltage profile of Phase B of Feeder 3 where maximum voltage rise was observed. In Scenario 6, there is a solar photovoltaic system at the end of the feeder which increases the voltage up to end of the feeder. Distribution Code of Sri Lanka allows ±6% voltage regulation in the low voltage feeders. In Case Study 1, violation of this condition was observed only in Scenario 6.


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Figure 4: Calculated Voltage Profile (Feeder 3/Phase B) at 11:00a.m.

Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5 Scenario 6

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d. System Losses 24. Distribution transformer loss and low voltage feeder losses were analyzed in this study. Table 9 summarizes the daily system losses in six scenarios.

Table 9: Summary of Calculated Daily System Losses, Case Study 1

External Infeed (kWh)

Transformer Loss Feeder Loss Total LV Loss

kWh % of external

infeed kWh % of input to feeder kWh %

Scenario 1 2,787.1 31.9 1.14% 76.7 2.78% 108.6 3.90% Scenario 2 2,279.2 27.9 1.22% 65.5 2.91% 93.4 4.10% Scenario 3 2,188.9 27.5 1.26% 64.8 3.00% 92.3 4.22% Scenario 4 1,917.2 27.0 1.41% 64.0 3.39% 91.0 4.75% Scenario 5 2,088.7 27.3 1.31% 66.0 3.20% 93.3 4.47% Scenario 6 400.5 39.7 9.91% 121.7 33.73% 161.4 40.30%

kWh = kilowatt hour, LV = low voltage. Note: Loss percentages are given in reference to input to the system.


25. A significant reduction in energy losses in the low voltage network can be observed when moving from Scenario 1 (solar photovoltaic capacity penetration level is 0%) to Scenario 2 (solar photovoltaic capacity penetration level is 43%). Scenarios 3 to 5 do not show significant loss reductions. However, losses as a percentage of external infeed increase due to the fact that relative reduction in energy input is higher than the reduction in losses. This would have commercial implications on distribution licensees, whose loss targets are specified in percentage terms of net input to the respective networks. In Scenario 6, significant increase in losses was observed due to reverse power flow.

e. System Harmonic Level 26. Maximum observed Total Harmonic Distortion (THD) values of the grid voltage are given in Table 10 for all six scenarios. Harmonic injections by loads were not considered in this study. Therefore, actual THD is expected to be greater than the observed values. THD is maximum at 12:00 p.m. when solar photovoltaic power generation is maximum, and it increases when solar photovoltaic capacity penetration increases. The Sri Lanka Distribution Code allows THD of 5% at PoC of solar photovoltaic system. Results indicate that harmonic injections of both loads and solar photovoltaic systems can increase the THD more than the allowed value if inverters are injecting maximum allowed harmonic levels.

Table 10: Calculated Maximum Total Harmonic Distortions, Case Study 1 Total Harmonic Distortion

Phase A Phase B Phase C

Scenario 1 0.00% 0.00% 0.00% Scenario 2 1.51% 0.88% 0.88% Scenario 3 1.78% 1.16% 1.16% Scenario 4 2.60% 1.40% 1.39% Scenario 5 1.87% 1.24% 1.24% Scenario 6 6.20% 4.80% 4.57%


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2. Results of the Case Study 2 27. Five studies were carried out under Case Study 2.

a. Distribution Transformer Loading 28. Variation of the distribution transformer loading levels was obtained for 24 hours in 15-minute intervals for the five scenarios as shown in Figure 5.


29. Since the presently connected solar photovoltaic capacity is only 7 kWp, the difference in transformer loading levels between Scenarios 1 and 2 is low. Scenarios 3, 4 and 5 have the same solar photovoltaic capacity at different locations of the feeder. Therefore, transformer loading level is approximately the same for Scenarios 3, 4 and 5. Even though the distribution transformer is lightly loaded, the increase in transformer loading more than in Scenario 1 was not observed when a solar photovoltaic system with high capacity is connected.

b. Feeder Loading Level 30. The maximum observed feeder loading levels as a percentage of the rated current carrying capacity of the conductor are given in Table 11. Overloading of feeders was not observed in any of the scenarios. In Scenario 3 and 4, maximum loading was observed in the feeder section from transformer low voltage terminal to the first pole. In Scenario 3, the maximum loading was observed in the feeder section closest to the solar photovoltaic system.

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Figure 5: Transformer Loading Levels of Case Study 1

Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5

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Table 11: Calculated Maximum Feeder Loading Level, Case Study 2

Maximum Feeder Loading Time of occurrence

Scenario 3 11.14% 12.00 p.m. Scenario 4 10.89% 12.00 p.m. Scenario 5 13.17% 11.45 a.m.


c. Feeder Voltage Level

31. In Scenario 2, considerable impact on feeder voltage level was not observed. Maximum feeder voltage levels of Scenarios 3, 4 and 5 were observed at 12.00 p.m. Voltage profile of Phase A of Feeder 3 is shown in Figure 6.


32. In all scenarios, voltage rises along the feeder up to PoC of solar photovoltaic system and thereafter voltage starts to decrease. Decrease in voltage is very low due to low demand at 12:00 p.m. Figure 7 depicts the 15-minute voltage profile at the PoC of solar photovoltaic system in Scenario 5. All customers who are connected closer to the PoC experience approximately same voltage variation throughout the day. Even though the voltage is below the upper limit defined in Sri Lanka Distribution Code, the probability of disconnecting the inverter due to over voltage condition is high.

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Figure 6: Calculated Voltage Profile of Phase A of Feeder 3 (Case Study 2)

Scenario 5 Scenario 4 Scenario 3

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33. Due to unavailability of load and solar irradiance data in very short intervals (less than one minute), voltage variation within such short intervals was not analyzed. Voltage of PoC and along the feeder depends on the amount of power generated by the solar photovoltaic system. In a cloudy day power generation of a solar photovoltaic system can have rapid variations due to varying solar irradiance, resulting in rapid variations in the voltage. Customers may experience voltage flickers, which is a serious power quality issue.

d. System Losses 34. Distribution transformer loss and low voltage feeder losses were analysed in this study. Table 12 summarizes the daily system losses in the five scenarios.

Table 12: Summary of Daily System Losses, Case Study 2 External

Infeed (kWh) Transformer Loss Feeder Loss Total LV Loss

kWh % kWh % kWh %

Scenario 1 808.8 11.8 1.46% 16.6 2.08% 28.4 3.51% Scenario 2 786.2 11.6 1.48% 16.7 2.16% 28.3 3.60% Scenario 3 630.1 11.2 1.78% 17.6 2.84% 28.8 4.57% Scenario 4 632.0 11.2 1.77% 19.5 3.14% 30.7 4.86% Scenario 5 634.7 11.2 1.76% 22.2 3.56% 33.4 5.26%

kWh = kilowatt hour, LV = low voltage.


35. When modelling Scenarios 3, 4 and 5, a hypothetical, high electricity consuming customer was introduced into the system to study the impact of connecting a high capacity solar photovoltaic system. Therefore, when comparing losses, Scenarios 3, 4 and 5 should be considered separate to Scenarios 1 and 2. Minor loss reductions can be observed when moving from Scenario 1 to Scenario 2. Since the reduction in losses are less when compared with the reduction in external infeed, the overall percentage losses increase. Results of Scenarios 3, 4 and 5 indicate that feeder losses increase when PoC of solar photovoltaic system moves away from the transformer.

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Figure 7: Voltage Variation at Point of Connection in Scenario 5

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e. System Harmonic Level 36. Observed THD levels are negligible in all scenarios in Case Study 2. Therefore, results have not been shown here. D. Conclusions 37. The results of two case studies indicate that the impact of solar photovoltaic penetration on low voltage distribution network depends on the characteristics of loads, the PoC and the capacity of solar photovoltaic systems. Results may have deviated from actual values due to assumptions made when carrying out the study. 38. When most of the customers are in the high electricity consuming groups, negative impacts on transformer loading level, feeder loading level and feeder voltage level due to solar photovoltaic power generation can be expected only when solar photovoltaic penetration level is extremely high. When solar photovoltaic systems are well distributed along feeders, there is an optimal cumulative solar photovoltaic capacity level where system losses are minimum. When solar photovoltaic capacity is increased above this level, high reverse power flows are observed for longer periods, increasing the total low voltage losses. If solar photovoltaic systems are concentrated on a particular segment of the feeder, system losses can increase when compared with the without solar photovoltaic systems scenario. It is important to install high quality inverters with minimum harmonic injections to keep the network THD below the allowed limit. 39. When most customers are in the low electricity consuming groups, negative impacts on transformer loading level, feeder loading level and THD due to solar photovoltaic power generation are unlikely. In such distribution schemes, instead of adding lower capacity solar photovoltaic systems, probability of adding higher capacity solar photovoltaic systems is high. Increase in system losses can be expected in such a scenario and if the solar photovoltaic system is located at the end of the feeder, losses will further increase, making the mid-day voltage rise along the feeder the main issue of concern.

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Annex 1: Methodology Followed in Case Studies

Select LV Distribution

Scheme

Model physical network from HV terminals of the transformer to

customer metering points

Apply tariff category and tariff

group wise demand patterns

Model rooftop solar PV

installations

Simulation

Transformer Loading

LV feeder loadingLV feeder voltage

riseLV distribution

lossesTHD

Increase rooftop solar PV

penetration

HV = high voltage, LV = low voltage, PV = photovoltaic, THD = total harmonic distortion

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Annex 2: Geographic Layout of the Distribution Network, Case Study 1

PowerFactory 15.0.0

Project:

Graphic: Grid

Date: 6/14/2017

Annex:

16

Annex 3: Geographic Layout of the Distribution Network, Case Study 2

Feeders

400V_Line (F1-P1)

400V_Line (F2-P2)

400V_Line (F3-P2)

PowerFactory 15.0.0

Project:

Graphic: Grid

Date: 6/14/2017

Annex:

17

Annex 4: Tariff Category of Customers in Case Study Areas

Tariff Category of Customers, Case Study 1

Tariff Category

Number of customers

Feeder 1 Feeder 2 Feeder 3

Domestic: single phase

0-30 8 1 6

31-60 5 1 3

61-90 22 2 6

91-120 24 6 10

121-180 36 14 15

>180 31 23 26

Sub Total 126 47 66

Domestic: three-phase

0-30 0 2 1

31-60 0 0 0

61-90 1 1 1

91-120 0 0 2

121-180 1 2 2

>180 13 21 29

Sub Total 15 26 35

Other

General Purpose 1: single phase

0-300 6 4 2

>300 2 0 0

Sub Total 8 4 2

General Purpose 1: three phase

0-300 5 0 2

>300 0 0 0

Sub Total 5 0 2

Total 154 77 105

Tariff Category of Customers, Case Study 2

Tariff Category

Number of customers

Feeder 1 Feeder 2 Feeder 3

Domestic: single phase

0-30 24 7 32

31-60 37 10 49

61-90 25 7 34

91-120 9 2 12

121-180 5 1 7

>180 1 0 1

Sub Total 101 27 135

Domestic: three phase

0-30 1 0 0

31-60 1 0 1

61-90 1 0 0

91-120 0 0 0

121-180 0 0 0

>180 0 0 0

Sub Total 3 0 1

Other

General Purpose 1 - 0-300 19 3 22

General Purpose 1 - >300 3 0 3

Industrial 1 - 0-300 1 0 1

Industrial 1 - >300 1 0 0

Sub Total 24 3 26

Total 128 30 162

18

Annex 5: Detailed Definition of Scenarios of Case Study 1

HH = household, kW = kilowatt, kWh = kilowatt hour, P = phase, PV = photovoltaic.

Case Tariff Category

Single unit solar PV

capacity (kW)

Energy demand

(kWh/month)

Solar PV electricity generation

(kWh/month)

Net electricity generation

(kWh/month)

Scenario 1: Without solar PV systems

- - - - -

Scenario 2: Present network HH-1P->180 4.00 277 559 282

HH-3P->180 5.25 696 707 11

HH-1P->180 4.00 832 559 (273)

HH-3P->180 4.00 501 559 58

HH-1P->180 4.00 707 559 (148)

HH-3P->180 6.20 967 854 (113)

HH-3P->180 3.25 816 442 (374)

HH-3P->180 3.80 723 530 (193)

HH-3P->121-180 3.00 157 412 255

HH-3P->180 4.00 936 559 (377)

HH-3P->180 5.00 707 677 (30)

HH-1P->180 5.60 711 765 54

HH-3P->180 3.00 404 412 8

HH-3P->180 4.30 619 589 (30)

HH-1P->180 1.75 404 236 (168)

HH-3P->91-120 3.50 98 471 373

HH-1P->180 1.00 322 147 (175)

HH-1P->180 2.00 247 265 18

HH-3P->180 3.15 381 442 61

HH-3P->180 6.00 920 824 (96)

HH-3P->180 3.00 336 412 76

HH-3P->180 7.25 1384 972 (412)

HH-3P->180 6.00 898 824 (74)

HH-3P->180 15.00 2119 2031 (88)

Scenario 3: Solar PV capacity is equal to 50% of the transformer capacity

HH-3P->180 7.50 910 1030 120

HH-3P->180 7.00 836 942 106

HH-3P->180 5.50 631 648 17

Scenario 4: Solar PV capacity is equal to 75% of the transformer capacity

HH-3P->180 7.50 954 1030 76

HH-1P->180 7.00 852 942 90

HH-1P->180 7.00 820 942 122

HH-3P->180 6.20 733 853 120

HH-3P->180 6.00 724 824 100

HH-1P->180 5.70 680 765 85

HH-1P->180 5.00 591 677 86

HH-3P->180 4.50 537 589 52

HH-3P->180 4.00 483 559 76

HH-3P->180 4.00 480 559 79

HH-3P->180 4.00 451 559 108

Scenario 5: 42 kW solar PV system into present network

HH-3P->180 42.00 3215 5711 2496

Scenario 6: All customers above 120 kWh/month electricity consumption

HH-3P->180 (49) 203.00 (Cumulative)

- - -

HH-1P->180 (72) 171.00 (Cumulative)

HH-3P-121-180 (4) 5.00 (Cumulative)

HH-1P-121-180 (65) 71.00 (Cumulative)

GP-3P-0-300 (1) 1.00

GP-1P-0-300 (4) 5.00 (Cumulative)

GP-1P->300 (1) 3.00