Validating the model by comparing projections based on actual and

This section addresses the first research question:

1. Compare the spot price, energy generated, carbon emissions and transmission congestion using projected and actual demand for the base weather year 2009- 10 to validate the model projections.

The reason for making the comparison between actual and projected demand for the year 2009-10 is to ensure the veracity of the models findings before addressing the more relevant research questions 2 to 5. If the ANEM model produces similar results using the actual and projected demand for 2009-10, this adds confidence when making comparison between 2009-10 and 2030-31 to evaluate the effects of climate change.

7.1.1 Methodology

The ANEM model described in Appendix C is used to make projections of four economics variables using the actual and projected demand from Chapter 5 for the year 2009-10 and the node structure in Appendix B. The four economic variables include:

• spot price;

• energy generated by type of generator; • carbon emissions; and

• transmission line congestion.

The methodology involves comparing the closeness of the output of the ANEM model of the four economic variables above based on the actual and projected demand for 2009-10. The output is presented in tables in Section D.2. The methodology employed in this Section is discussed in greater detail in Section D.1.

Analysis of institutional adaptability 111

7.1.2 Results

The results are too lengthy to include in the main text and detract from the more relevant research questions. Sections D.3.1 and D.3.2 present the results.

7.1.3 Discussion

The following discussion provides a summary of the analysis in Appendix D that compares the output of the ANEM model using actual and modelled demand for 2009- 10 from Chapter 5. The four outputs from the ANEM model are discussed in turn:

• carbon emissions;

• energy produced by generation type; • spot prices; and

• transmission line congestion. 7.1.3.1 Carbon emissions

There is less than 0.1 of one per cent difference between the ANEM model’s projection of carbon emission using the actual and projected demand from Chapter 5. This high level of comparison holds whether analysing the carbon emissions by state or fuel type. 7.1.3.2 Energy produced by generator type

There is less than 0.1 of one per cent difference between the ANEM model’s projection of energy produced by generator type using the actual and projected demand from Chapter 5. This high level of comparison for energy produced by generator type holds whether analysing by fuel type or state.

However, hydro generation has a greater than 0.1 of a per cent difference. The percentage difference in energy produced by generator type for hydro generation in New South Wales was between 1.0 and 1.3 per cent and 0.4 to 0.7 of a per cent in Victoria depending upon carbon price. The ratio of the average production level of hydro generation to its nameplate capacity for New South Wales and Victoria is 0.0003% and 0.008%, respectively. So, average hydro production levels being such a small fraction of total hydro capacity ameliorates any concern over the higher per cent difference for hydro generation.

7.1.3.3 Wholesale spot price

Average spot prices:

Victoria experiences the most difference with the percentage change being in the order of 0.3 to 0.7 of one per cent depending upon carbon price setting. South Australia’s difference is in the range of 0.1 to 0.4 of one per cent depending upon carbon price.

Spot price volatility:

Queensland experienced the largest increase in spot price volatility with differences in the range of 0.5 to 0.9 of one per cent depending upon carbon price. Increasing the carbon price from $0/tC02 to $23/tC02 reduced the difference between ANEM model’s

spot price projection based in projected and actual demand. This holds true for both average spot price and spot price volatility.

112 Analysis of institutional adaptability 7.1.3.4 Line congestion

Average power flows

The percentage difference in average power flows on intra-state transmission lines have diminished with an increase in carbon price from $0/tC02 to $23/tC02. Under both

carbon pricing scenarios, all intra-state transmission lines have similar values seen in Panel (J) of Tables D-1 and D-2 in Appendix D. The difference in average power flow on inter-state transmission lines is less than 0.2 of one per cent and in many cases, less than 0.1 of one per cent.

Measures of direct branch congestion

The QLD-NSW interconnector (QNI) is the transmission line with the largest difference between simulations based on actual and predicted demand. The difference is 0.1 of one per cent. Depending upon carbon price setting, the Tumut to Regional Victoria line number 37 has up to 0.2 of one per cent difference.

The results seen in Panel (L) of Tables D-1 and D-2 in Appendix D relating to the Marulan-Yass line 31 indicates significant variation in congestion outcomes when using the actual and projected 2009-10 demand profiles. However, ameliorating concerns over these marked percentage difference outcomes is the recognition that these outcomes are coming off an extremely small base congestion value of 0.0005%. As such, the incidence of congestion on this branch is extremely marginal and does not show up in the simulation utilising the actual 2009-10 demand profile.

7.1.4 Conclusion

The results show that the projections for the four economic factors listed below based on the actual and projected demand are extremely close:

• spot price;

• energy generated by type of generator; • carbon emissions; and

• transmission line congestion.

This result allows us to proceed with some confidence to address the remaining research questions and use the ANEM model to make the comparisons between the years 2009-10 and 2030-31 based on the demand projections for those years.