NEMLink : Augmenting the Australian National Electricity Market transmission grid to facilitate increased wind turbine generation and its effect on transmission congestion

This report compares the effect of increasing the number of wind turbine generators on transmission line congestion in the Australian National Electricity Market’s (NEM) under the existing transmission grid and an augmented version of the transmission grid called NEMLink (AEMO 2010a, 2010b, 2011a, 2011b). The comparison is made from 2014 to 2025. We use a sensitivity analysis to compare the effect of five different levels of wind penetration on transmission congestion in the original NEM grid and NEMLink augmented grid. The five levels of wind penetration span Scenarios A to E where Scenario A represents ‘no wind’ and Scenario E includes all the existing and planned wind power sufficient to meet Australia’s original 2020 41TWh Large Renewable Energy Target (LRET). We also use sensitivity analysis to evaluate the effect on transmission congestion of growth in electricity demand over the projections years 2014 to 2025 and weather over the years 2010 to 2012. The sensitivity analysis uses simulations from the ‘Australian National Electricity Market (ANEM) model version 1.10’ (Wild et al. 2015).


Introduction
We identified constraints in the national electricity market (NEM) transmission grid affecting the beneficial deployment of wind turbine generation to reduce both wholesale spot prices and carbon dioxide emissions (Bell et al. 2015a(Bell et al. , 2015b(Bell et al. , 2015c(Bell et al. , 2015d, 2015f), 2015f).The higher penetration of wind turbine generation required to address climate change and reduce wholesale spot prices will require either energy storage or augmenting the NEM's transmission grid to overcome the limitations of grid that was primarily built to accommodate supply from a coal generation fleet.This coal generation fleet is a major source of carbon dioxide emissions in Australia and cause of climate change.The coal fleet is nearing the end of its economic life and the opportunity presents to phase out the coal fleet and replace with renewable energy but augmenting the existing transmission structure is required to ensure a smooth transition.
Our findings from a wind speed-electricity demand correlation analysis in the NEM shows that the greatest benefit from wind turbine generation comes from connecting the NEM's peripheral States: Queensland (QLD), South Australia (SA) and Tasmania (TAS) (Bell et al. 2015f).An improved peripheral connection would help both ameliorate the intermittency of wind turbine generation to improve system stability and improve wind turbine generators' ability to match changes in electricity demand.However, delivering these benefits requires improving the transmission capacity through both New South Wales (NSW) and Victoria (VIC).

Australian National Electricity Market Model
The following description provides a simplified computer input-output overview of the ANEM model.
The inputs of the ANEM model are:  half hourly electricity "total demand" for 50 nodes in the NEM;  parameter and constraint values for 68 transmission lines and 330 generators, albeit incorporating the de-commissioning of generation plant occurring over the period 2007-2014;  carbon price, which is assumed zero in this project;  fossil fuel prices; and  network topology of nodes, transmission lines and generators.
The outputs of the ANEM model are:  wholesale spot price at each node (half hourly),  energy generated by each generator (half hourly),  energy dispatched by each generator (half hourly),  power flow on each transmission line (half hourly), and  carbon dioxide emissions for each generator (daily).

Five levels of wind penetration
We group existing and planned windfarms into five levels of wind penetration.NEMLink: Augmenting the Australian National Electricity Market transmission grid to facilitate increased wind turbine generation and its effect on transmission congestion page10

Baseline years 2010-12 and projections years 2014-25
The project uses electricity demand profiles from three calendar years 2010, 2011 and 2012.
Using the demand profiles from these three calendar years reduces the chances of modelling an unrepresentative weather year.Additionally, these weather years provide halfhourly correspondence between electricity demand for each node on the NEM and wind power generated for the five levels of wind penetration for each node on the NEM.The wind power generated is calculated from half-hourly wind climatology results for the years 2010 to 2012 (Wild et al. 2015).
The demand profiles in the three baseline-years are incremented to form projections for the years 2014 to 2025, making three projections.We simulated the five levels of wind penetration for each projection base year, making fifteen projections in all to allow sensitivity analysis.
Examining difference between the three baseline years 2010 to 2012 considers the effect of differing annual weather systems on the dynamics of the NEM and wind generation output of the different wind power penetration scenarios.In contrast, the projections years 2014 to 2025 consider the effect of growth in electricity demand on the dynamics of the NEM.This section has the following structure.Section 1 evaluates changes in congestion induced by NEMLink and identifies those lines still congested.Section 2 compares NEMLink transmission line congestion between transmission lines to identify system wide effects and Section 3 examines individual lines in detail to evaluate the observations made in Section 2 in higher resolution.

The change in transmission line congestion induced by NEMLink
In this section, we discuss the change in transmission line congestion induced by NEMLink and identify those lines still congested in the NEMLink configuration.We identify those congested lines to evaluate the effect of three factors on their congestion.The three factors include wind power penetration, weather and demand growth effects.The project report Bell et al. (2015c) has already analysed the effect of the three factors on the original unaugmented grid.
Table 2 shows the effect of NEMLink on transmission congestion and consolidates the information in Table 3, Table 4 and Table 5.Table 3 and Table 4 present transmission line congestion with and without NEMLink.We measure congestion as the percentage of the time transmission lines have reached their maximum thermal capacity during the year.In comparison, Table 5 presents the percentage point reduction in congestion induced by NEMLink.Simply, Table 5 is the difference between Table 3 and Table 4 that is Table 3 less Table 4.
Table 4 shows the transmission lines with congestion in the unaugmented original NEM grid.Those congested include Lines 4, 11, 14, 26, 30, 37, 42, 47, 48, 50, 52, 53, 60 and 64.Table 3 shows that NEMLink has eliminated congestion on Lines 11, 26, 37, 48 and 53 for all wind power, weather and demand growth scenarios.Those lines with zero congestion are no longer of interest to this report.In contrast, NEMLink has only reduced congestion in Lines 4, 60 and 64 and increased congestion on Lines 14, 30, 36, 42, 47, 50.However, the effect of NEMLink on Line 53 is mixed.Notably, the now congested NSW-VIC interconnector Line 36 had zero congestion in the original unaugmented grid.
In the following sections, we examine the effect of the three factors on the congested lines in the NEMLink augmented grid.However, some of the lines experience extremely little congestion and their inclusion would crowd the graphical presentation for such a tiny effect.Therefore, we examine those transmission lines with sizable congestion marked with "XX" in Table 2 and those with smaller congestion separately.page13

Inter transmission line comparison to identify system wide effects
We examined system wide changes in percentage point congestion induced by NEMLink using the lowest and highest wind penetration scenarios, A and E, and the first and last projection years, 2014 and 2025 for each of the baseline weather years 2010 to 2012.We examine the NEMLink induced change in congestion under the following three effects.
 Wind penetration effect shown between scenario A and E  Weather effect shown between the baseline years 2010 to 2012  Growth in demand effect shown between the projection years 2014 to 2025

Wind penetration effect shown between scenarios A and E
Figure 1 compares with and without NEMLink the average percentage of the time the transmission lines are at their thermal maximum for the wind penetration scenarios A and E. Scenario A is no wind generation.In contrast, Scenario E contains all existing and planned wind generation that would meet the 2020 41TWh LRET. Figure 1  Finally, the NEMLink augmentation excludes BassLink in this report.The submarine HVDC cable is the most capital costly interconnector augmentation.However, both the higher penetration of wind and NEMLink induce slightly more congestion in BassLink, which indicate a higher benefit from augmenting BassLink.NEMLink induces a slight reduction in congestion on both TAS intrastate lines Palmerston-Sheffield and Tarraleah-Waddamana. Lastly, the wind penetration effect is by far the largest of the three effects.Our wholesale spot price report (Bell et al. 2015e) discusses the effects of this congestion on price differential between TAS and the other mainland NEM states.

Growth in electricity demand effect shown in the difference between projection years 2014-25
Figure 3 shows the average percentage of the time the transmission lines are at their thermal maximum for the projection years 2014 and 2025.We model the demand for electricity to grow from 2014 to 2025.Hence, a growth effect can account for the redistribution of the proportion of time the transmission lines are at their maximums.Figure 3 is the average across the wind scenarios A and E and baseline years 2010 to 2012.We would expect the growth in demand to increase the proportion of time the lines are at their maximum thermal capacity.
Without NEMLink in Panel (a), congestion increases for lines 11, 37, 48, 60 and 64 but lines 14 and 42 experience a decrease.The largest growth effect is for line 37, which is slightly less than 10 percentage points.
Comparing the patterns of transmission line congestion in Panel (a) and (b) shows the general direction, that is increase or decrease from 2014 to 2025, is the same with or without NEMLink.However, the magnitudes differ.
This growth effect is the smallest of the three effects.
NEMLink: Augmenting the Australian National Electricity Market transmission grid to facilitate increased wind turbine generation and its effect on transmission congestion page22

Comparing the effect of the five wind scenarios on different lines
In the previous three sections, the wind penetration effect was by far the largest, followed by the weather effect and the smallest being the growth in demand effects.Hence, this section evaluates the larger wind penetration effect in more detail.Figure 4 below shows the average percentage of the time the transmission lines are at their thermal maximum for the wind penetration scenarios A to E. These scenarios are progressive increases in wind power penetration.Figure 4 presents the five wind scenarios.In contrast, Figure 1  MurrayLink (Line 48) without NEMLink shown in Panel (a) shows a large increase in congestion after the initial introduction of wind power and progressively increases in congestion on the increase in wind power.MurrayLink constrains the export of wind power from SA to VIC and will become more constraining without suitable augmentation or energy storage solutions.The effect of NEMLink on MurrayLink is to eliminate congestion.However, congestion increases on the Heywood interconnector (Line 47), particularly under Scenario E. As noted in Section 3.2.1, the AER has recently approved an augmentation of the Heywood Interconnector.This would go some way to moderating or eliminating congestion effects on this line under Scenario E.
Without NEMLink shown in Panel (a), Tarraleah-Waddamana (Line 60) shows a similar trend to its near neighbour Palmerston-Sheffield (Line 64) with the exception of Scenario E. The effect of NEMLink is to decrease congestion on both Lines 60 and 64.
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Detailed investigation of individual lines
This section presents a detailed individual evaluation of each of all transmission lines in Table 3.The previous section identified the wind penetration effect as the largest, followed by the weather effect and the smallest being the growth in demand effects.Hence, the following presentation focuses on the larger effect but discussing each line individually also allows evaluation of the two other effects, weather and demand growth.Viewing the network diagrams in Wild et al. (2015, figs.1-6) while reading this section would aid comprehension for readers who are unfamiliar with the NEM's transmission line topology.

QLD-NSW Interconnectors: QNI and DirectLink (Lines 11 and 14)
This section and the following sections examine the lines in more detail to determine the effect of weather and demand growth on the five wind scenarios.The difference between the baseline years 2010 to 2012 shows the weather effect and the difference between the projection years 2014 and 2025 shows a demand growth effect.These baseline years and projection years are on the x-axis of Figure 5 and on the x-axis of the other figures in the following sections.We also evaluate whether the observations made in the previous sections hold under more detailed examination.
Both the QNI and DirectLink interconnect the QLD and NSW intrastate transmission systems.
Our transmission congestion report (Bell et al. 2015c, Sec.3.2.1)discusses the inverse congestion relationship between QNI and DirectLink without NEMLink in detail.The AEMO's NEMLink proposal includes augmenting QNI that eliminates congestion on QNI.However, Bell et al. (2015c, Fig. 5) clearly shows an inverse congestion relationship between QNI and DirectLink where congestion decreases on QNI and increases on DirectLink as wind power penetration increases from Scenario A to E. ANEM's proposed NEMLink QNI augmentation is addressing a congestion problem that will diminish as wind power penetration increases but fails to address the increasing congestion on DirectLink.
Figure 5 shows how the weather, demand growth and wind-penetration affect congestion on the DirectLink with and with NEMLink.The general patterns of these effects on congestion are similar with and without NEMLink.However, NEMLink induces a slightly higher level of congestion across all effects.This observation reinforces the argument in the previous paragraph to consider DirectLink in the NEMLink augmentation or at least as a separate augmentation proposal.As discussed in Section 3.21, Directlink and its surrounding 132 kV network have a limited transfer capacity of 180 MW.Thus, it is not surprising that this line would be a serious candidate for augmentation under both the 'NEMLink' and 'no NEMLink' network structures.

NSW-VIC Interconnectors: Tumut NSW to Dederang and Regional VIC (Lines 36 and 37)
Figure 6 Panel (a) shows the without NEMLink congestion on the VIC-NSW Interconnector that connects 'Regional VIC' to 'Tumut NSW' (Line 37).The introduction of wind power, from Scenario A to B, has reduced the congestion projected in 2025 in the three weather scenarios 2010 to 2012.The effect of NEMLink is to eliminate congestion on Line 37.
However, Panel (b) shows that the NEMLink induces a slight congestion on Line 36 that previously has no congestion.This congestion tends to diminish over time but also increases with wind power penetration.In any case, however, Line 36's congestion rates of less than 6 percent are minor, making augmentation unnecessary.

VIC-TAS Interconnector: BassLink (Line 42)
Figure 7 shows the congestion on the interconnector BassLink that connects the VIC and TAS intrastate transmission networks.The projected increase in congestion in BassLink from Wind Penetration Scenario A to D and decrease in congestion from Scenario D to E is present with and without NEMLink.Both cases suggest a relocatable energy storage solution to this temporary increase in congestion.Additionally, both with and without NEMLink there is slightly lower congestion in 2025 relative to 2014.This pattern holds for all the base years 2010, 2011 and 2012 and is particularly strong moving from Scenario B to D. Overall NEMLink has slightly exacerbated congestion on BassLink.As discussed in Section 3.2.4,the power flow on BassLink depends strongly upon the Tasmanian hydro plant dispatch.Modelling hydro dispatch with differing assumptions could produce different dispatch patterns, power flows and congestion patterns on BassLink.

SA-VIC Interconnectors: Heywood and MurrayLink (Lines 47 and 48)
The interconnectors Heywood (Line 47) and MurrayLink (Line 48) interconnect the SA and VIC intrastate transmission networks.Bell et al. (2015c, Sec.3.2.4)discuss how weather, demand growth and wind-penetration affect the congestion on these two interconnectors without NEMLink.These two interconnectors fail to show any complimentary pattern unlike QNI and DirectLink.MurrayLink augmentation is part of the AEMO's NEMLink proposal.
The augmentation eliminates MurrayLink's sizable congestion to allow the export of wind power from SA to VIC.However, NEMLink also increases the congestion on Heywood particularly at the highest wind penetration Scenario E see Figure 8.However, the recent approval by the AER to augment Heywood would reduce, if not eliminate, this congestion.

Wind penetration scenarios
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Comparing BassLink and Tarraleah-Waddamana (Lines 42 and 64)
Bell et al. (2015c, Sec.3.2.5)establish a complimentary congestion pattern between the BassLink and Tarraleah-Waddamana in TAS without NEMLink.In this section, we establish if the same complimentary congestion pattern holds with NEMLink. Figure 9 shows the complimentary congestion pattern also holds with NEMLink.Additionally, NEMLink increases congestion on BassLink and reduces congestion on the Tarraleah-Waddamana Line.

Gladstone-Central West QLD (Line 4)
Figure 11 shows the congestion on Gladstone-Central West QLD (Line 4).This congestion is exceedingly small in magnitude and largely weather dependent, being only present in the weather year 2011.NEMLink further reduces this congestion.

Riverland-SE SA (Lines 50)
Figure 13 compares the congestion on Riverland-South East SA (Line 50) with and without NEMLink.The congestion is exceedingly small in magnitude and only present in the higher wind penetration Scenarios.NEMLink marginally increases congestion on this line.However, the rates of congestion under both transmission network structures are still exceedingly small in magnitude.

Greater Adelaide-Mid North SA (Line 52)
Figure 14 compares the congestion on Greater Adelaide-Mid North SA (Line 52) with and without NEMLink.The congestion is also exceedingly small in magnitude and only present in the higher wind penetration Scenarios.NEMLink slightly increases congestion on this line, although the rates are still exceedingly small.

Mid North -Riverland SA (Line 53)
Figure 15 shows the congestion on Mid North SA -Riverland (Line 53) without NEMLink.This congestion is small and absent in the 'no wind' Scenario A. NEMLink eliminates congestion on this line.Both Tumut-Dederang and Tumut-Regional VIC interconnect NSW and VIC.Tumut-Regional VIC forms part of the NEMLink backbone and augmentation eliminates Tumut-Regional VIC's congestion.However, NEMLink induces a slight congestion on Tumut-Dederang (Line 36) that previously has no congestion.This congestion tends to diminish over time but also increases with wind power penetration.In any case, Line 36's congestion NEMLink: Augmenting the Australian National Electricity Market transmission grid to facilitate increased wind turbine generation and its effect on transmission congestion page39 rates of less than 6 percent are minor making augmentation unnecessary; see Figure 6 Panel (b).
BassLink interconnects VIC and TAS.BassLink falls outside the NEMLink backbone.The submarine HVDC cable is the most capital costly interconnector augmentation and subsequently excluded from a NEMLink proposal.However, both the higher penetration of wind and NEMLink induce slightly more congestion on BassLink, which indicate a higher benefit from augmenting BassLink.The congestion on BassLink increases from wind penetration Scenario A to D but decreases from Scenario D to E. Our transmission report (Bell et al. 2015c, Sec. 4) discusses the possibility of using temporary relocatable energy storage as a solution rather than the traditional approach of laying more lines to address the temporary increases in congestion.As discussed in Section 3.2.4,the power flow on BassLink depends strongly upon the Tasmanian hydro plant dispatch.Modelling hydro dispatch with differing assumptions could produce different dispatch patterns, power flows and congestion patterns on BassLink.This forms future research.
In our transmission report (Bell et al. 2015c, Sec.3.2.5)we establish and provide reasons for a complimentary congestion pattern between the BassLink and Tarraleah-Waddamana.The congestion on BassLink increases from wind penetration Scenario A to D but decreases from Scenario D to E. The congestion on Tarraleah-Waddamana decreases from wind penetration Scenario A to D but increases from Scenario D to E. NEMLink increases congestion on BassLink and reduces congestion on Tarraleah-Waddamana but the complementary pattern still holds.Again, in this situation using temporary relocatable energy storage is a possibility.
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Conclusion
We find that the NEMLink proposal goes some way to addressing the congestion amongst the transmission lines in the NEM when increasing wind power penetration from Scenario A that is no wind power penetration to Scenario E that meets Australia's 2020 Large Renewable Energy Target (LRET).Augmentation of both BassLink and DirectLink need considering in future augmentation proposals whether part of NEMLink or otherwise.There is a requirement to specifically model the higher penetrations of renewables to accommodate the inevitable shift from fossil fuels to renewable energy.
Our transmission report (Bell et al. 2015c, Sec. 5) has already discussed Australia's extremely modest 2020 renewable electricity target when compared to renewable electricity targets elsewhere.More ambitious targets are in keeping with other developed countries.
The planned phasing out the fossil fuel fleet and replacement with renewable energy requires appropriate network infrastructure.However, developing a cost effective NEMLink is contingent on the generation mix and renewable energy benefits from using a portfolio approach to help reduce the intermittency and variability present in each form of renewable energy generation.This presents a challenge concurrently optimising a NEMLink structure and renewable energy portfolio contingent on the NEM's geographically dispersed wind and solar resources.
We (Bell et al. 2015f) assessed correlation between wind speed and electricity demand that informed the importance of the NEMLink transmission network augmentation that connects the NEM's peripheral states for the NEM to avail itself of the advantages of wind power, including systems stability and enabling wind power to better meet electricity demand without storage.The backbone concept of the NEMLink proposal fits in with this requirement.The study also discovered an unwitting portfolio effect were solar PV is meeting an increasing portion of the midday demand.The residual demand better fitted the wind generators profile.
A further change to the deployment of NEMLink is the potential massive loss in profits for the fossil fuel generators from the combination of reduced congestion from NEMLink and the merit order effect from renewable energy.The fossil fuel lobby will find it in their interest to block or hinder the development of NEMLink.However, it is possible that some coal generators especially brown coal might do well under NEMLink as brown coal is also very cheap and NEMLink would increase its geographic reach.Both brown coal and wind production shares could well increase via the merit order effect at the expense of hydro and gas generation.
Further research is required to evaluate the effect of NEMLink on emissions and dispatch patterns.If the effect of NEMLink is to increase emissions and change dispatch patterns by reducing gas and hydro generation and increasing coal generation, a carbon price signal would be required to make coal relatively more expensive.
Bell et al. (2015c)  examine the effect of the five wind penetration levels on transmission congestion without the NEMLink augmentation.We use this congestion analysis without NEMLink report as a baseline in this report.The following outline provides a structure for the remainder of the report.Section 2 discusses the methodology for the sensitivity analysis and provides an outline of the 'Australian National Electricity Market (ANEM) model version 1.10' (Wild et al. 2015).Section 3 presents the results from the sensitivity analysis.Section 4 discusses the results and Section 5 concludes the report.NEMLink: Augmenting the Australian National Electricity Market transmission grid to facilitate increased wind turbine generation and its effect on transmission congestion page9 2 Methodology: Wild et al. (2015) provides a detailed description of the ANEM model, justification for the five levels of wind penetration and the incrementing of the baseline weather electricity demand profile years 2010 to 2012 to form three demand projections from 2014 to 2025.This section provides a brief outline of the ANEM model, the five levels of wind penetration and the demand profiles before presenting the results in the next section.
are shown in Wild et al. (2015, Sec. 2).We analyse the sensitivity of transmission flows on NEMLink to evaluate the change in transmission congestion.Bell et al. (2015c) analyse transmission congestion in the original NEM transmission grid without NEMLink.The results in Bell et al. (2015c) form the baseline for the sensitivity analysis.
a.No wind generation b.Operational and under construction c.Advanced planning (+all the windfarms above) d.Less advanced planning (+all the windfarms above) e. Least advanced planning (+all the windfarms above) Details of the windfarms within the five groups are in the project report 'ANEM model version 1.10' (Wild et al. 2015, tbls.4 & 5).

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Results: Transmission CongestionThis section presents the results, which should be read while viewing the diagrams in the project report 'Australian National Electricity Market model version 1.10' (Wild et al. 2015, figs.1-6).These diagrams relate the transmission line numbers to the topology of the transmission network.
Figure1compares with and without NEMLink the average percentage of the time the transmission lines are at their thermal maximum for the wind penetration scenarios A and E. Scenario A is no wind generation.In contrast, Scenario E contains all existing and planned wind generation that would meet the 2020 41TWh LRET.Figure1is the average across the baseline weather years 2010 to 2012 and the projection growth years 2014 and 2025.Panel (a) without NEMLink shows the change in the proportion of time the transmission lines are at their maximum capacity is over 60 percentage points for MurrayLink (Line 48) and over 16 percentage points for Palmerston-Sheffield (Line 60).The other lines fall between these two extremes.The increase in wind penetration induces both large increases and decreases in the proportion of the time the transmission lines are at their thermal maximums.In Panel (b) with NEMLink, DirectLink shows a 44 percentage points change in congestion induced by the change in wind-power penetration from Scenario A to E, which is the largest change.NEMLink has reduced the range of percentage points of congestion.The smallest change is over 16 percentage points for Palmerston-Sheffield (Line 60).Comparing Panel (a) and Panel (b), there are some interesting dynamics occurring between the Interconnectors QNI and DirectLink and between MurrayLink and Heywood.QNI and DirectLink both interconnect QLD and NSW.These interconnectors exhibit an inverse relationship in Panel (a).Bell et al. (2015c, Sec.3.2.1)discuss the reasons for this relationship in detail.The introduction of NEMLink has eliminated congestion on QNI but slightly exacerbated the existing high rates of congestion on DirectLink present under the 'no NEMLink' baseline.However, Directlink and its surrounding 132 kV network have a limited transfer capacity of 180 MW.Thus, it is not surprising that this line would be a serious candidate for augmentation under both the 'NEMLink' and 'no NEMLink' network structures.MurrayLink and Heywood both interconnect SA and VIC.Similarly, the introduction of NEMLink has eliminated congestion in MurrayLink but has slightly exacerbated congestion on Heywood particularly under Scenario E. The inclusion of the large Ceres windfarm in the Adelaide Node under Scenario E is a likely cause of the congestion on Heywood.The AER has recently approved an augmentation of the Heywood Interconnector.This would go some way to moderating or eliminating congestion effects on this line under Scenario E. Regarding two NSW-VIC interconnectors Lines 36 and 37, the introduction of NEMLink has eliminated congestion on Line 37 but has caused slight congestion on the previously uncongested Line 36.Section 3.3.2indicates congestion rates on line 36 are less than 6 per

NEMLink:Figure 1 :PanelFigure 2 :
Figure 1: Average percent of time a line is at its thermal maximum for the wind power scenarios A and E Panel (a) Without NEMLink

Figure 3 :
Figure 3: Average percent of time a line is at thermal maximum for the projection years 2014-2025 Panel (a) Without NEMLink

Figure 4 :
Figure 4: Comparing the effect of the five wind scenarios on different lines Panel (a) Without NEMLink
Table2uses "XX" to denote those transmission lines with sizable congestion.In these tables, the four lines shaded in dark grey are part of the NEMLink augmentation.The first three are Interconnectors but the last line Mid North-Riverlands (line 53) is an intrastate transmission branch in SA.The four lines shaded light grey are interconnectors but excluded from the NEMLink augmentation.

8 Marulan-Sydney and Canberra-Wollongong NSW (Lines 26 and 30)
Bell et al. (2015c, Sec.3.2.8)discuss the exceedingly small congestion on the two NSW lines Marulan-Sydney (Line 26) and Canberra-Wollongong (Line 30) without NEMLink.This exceedingly small congestion is only present in the highest wind penetration Scenario E. This reflects the extra congestion from windfarms Conroy's Gap 2 and Yass Valley at Yass, NSW (Node 24) commencing in Scenario E. This expansion in wind power at the Yass node in NSW, (Node 24) in Scenario E follows nearby wind power expansion at the Marulan, NSW (Node 23) and Canberra, ACT (Node 25) nodes in Scenarios C and D. Line 30) with and without NEMLink.Congestion on Line 30 becomes markedly lower under the wind power penetration Scenarios B to E when compared with the 'no wind' Scenario A. Given the wind farms already operational at the Canberra node, Scenarios B to E would represent the current and probable future windfarm deployment.Therefore, it would be unnecessary to augment Line 26 because in Scenarios B to E the congestion is minor, which is under 12 percent.
We have analysed the sensitivity of the Australian National Electricity Market transmission line congestion to the introduction of NEMLink outlined in the National Transmission Network Development Plan(AEMO 2010a(AEMO  , 2010b(AEMO  , 2011a(AEMO  , 2011b)).During this sensitivity analysis, we also considered the effect of increasing the number of wind turbine generators (WTG) on congestion from Scenario A that is no wind power to Scenario E that is sufficient wind power to meet the 2020 41TWh Large Renewable Energy Target.The sensitivity analysis also considered the effect of weather and electricity demand growth on congestion.We used simulations from the Australian National Electricity Market Model (Wild et al. 2015) to perform the sensitivity analysis.Without NEMLink, there is congestion on 14 of the 68 transmission lines in the ANEM Model (Wild et al. 2015).Notably, these 14 congested transmission lines include 6 of the NEM's interstate interconnectors and 8 intrastate transmission lines but only 3 of the intrastate transmission lines exhibited any significant congestion.The other 5 of the intrastate transmission lines exhibited extremely little congestion.With NEMLink, there is congestion on 12 of the 68 transmission lines.These 12 lines include 4 interconnectors.The magnitude of the congestion on the 8 intrastate transmission lines varies from tiny to small.We focus on the 4 interconnectors that remain congested after the NEMLink augmentation, namely, DirectLink, BassLink, Heywood and Tumut-Dederang (NSW-VIC).Both DirectLink and QNI interconnect QLD and NSW.QNI forms part of the NEMLink backbone and augmentation eliminates QNI's congestion.Our transmission congestion report(Bell et al. 2015c, Sec.3.2.1)discusses the inverse congestion relationship between QNI and DirectLink without NEMLink in detail.Bell et al. (2015c, Fig.5) clearly shows an inverse congestion relationship between QNI and DirectLink where congestion decreases on QNI and increases on DirectLink as wind power penetration increases from Scenario A to E. The QNI augmentation is addressing a congestion problem that will diminish as wind power penetration increases.In contrast, the congestion on DirectLink increases with increasing wind power penetration and NEMLink exacerbates the congestion on DirectLink, see Figure5.Directlink and its surrounding 132 kV network have a limited transfer capacity of 180 MW.DirectLink is a candidate for augmentation under both the 'NEMLink' and 'no NEMLink' network structures.Both Heywood and MurrayLink interconnect SA and VIC.MurrayLink forms part of the NEMLink backbone and augmentation eliminates MurrayLink's congestion.However, NEMLink also increases the congestion on Heywood particularly at the highest wind penetration Scenario E, see Figure8.However, the recent approval by the AER to augment Heywood would reduce, if not eliminate, this congestion