Abstract

This report investigates the effect of increasing the number of wind turbine generators on energy generation in the Australian National Electricity Market’s (NEM) existing transmission grid from 2014 to 2025. This report answers urgent questions concerning the capability of the existing transmission grid to cope with significant increases in wind power and aid emissions reductions. The report findings will help develop a coherent government policy to phase in renewable energy in a cost effective manner. We use a sensitivity analysis to evaluate the effect of five different levels of wind penetration on energy generation. 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 2020 41TWh Large Renewable Energy Target (LRET). We compare the relative effect of five different levels of wind penetration on energy generation to the effect on emissions. We also use sensitivity analysis to evaluate the effect on energy generation of growth in electricity demand over the projections years 2014 to 2015 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). We find NSW, QLD and SA experience a larger decrease in percentage emissions than in percentage decrease in energy. The converse is true in TAS and VIC. In the NEM overall, there is a larger percentage decrease in energy than in emissions. TAS has the largest percent decrease in generation owing to its gas fleet that is readily displaced by wind power penetration and hydro-generation that is similarly displaced. However, TAS has the largest difference between percent energy decrease and percent emissions decrease that means reducing energy in TAS is most ineffective at reducing emissions. This is owing to TAS relatively large displaced gas fleet that produce relatively few emissions and the displaced hydro-generation that produces no emissions. In contrast, Victoria having the largest brown coal generation fleet in the NEM has the lowest percent decrease in energy in the NEM and an even lower percent decrease in emissions. This situation is suboptimal for the NEM because brown coal produces more carbon dioxide emissions per unit of electricity. Wind power via the merit order effect displaces the more expensive fossil fuel generators first in the order gas, black coal and brown coal. Reintroducing the Carbon Reduction Pricing Scheme would address this inefficiency. In addition, introducing a 100% RET would help reduce investment uncertainty both for wind turbine and fossil fuel generators and aid fossil fuel staff in their decisions to transition to the renewable energy sector. Refurbishing the old coal generators remains a viable option without a commitment to a higher RET. Such refurbishment detracts funds from a more sustainable future. In further research, we (Bell et al. 2015d, 2015e) investigate augmenting the NEM’s transmission grid to reduce transmission congestion across the NEM and address the price differential between states under increasing wind power penetration. This augmentation will affect both emissions and energy generations.

Highlights

  • This report’s primary aim is to investigate ‘The effect of increasing the number of wind turbine generators on generator energy in the Australian National Electricity Market from 2014 to 2025’

  • The wind power induced generator energy decrease rate in VIC is the smallest in the National Electricity Market (NEM) of about only 3 percent. This is a matter for attention given VIC is the largest emitter in the NEM

  • We find the average hourly generator energy for all States in the NEM decrease when wind power increases from Scenario A that is ‘0% or no wind power’ to Scenario E that meets Australia’s Large Renewable Energy Target (LRET) of 2020

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Summary

Introduction

This report’s primary aim is to investigate ‘The effect of increasing the number of wind turbine generators on generator energy in the Australian National Electricity Market from 2014 to 2025’. The sensitivity analysis in this report uses simulations from the ‘Australian National Electricity Market (ANEM) model version 1.10’ (Wild et al 2015) to model the effect of five different levels of wind penetration on generator energy. Bell et al (2015f) analyses wind speed and electricity demand correlation to determine the ability of wind turbine generators to meet electricity demand in the Australian National Electricity Market (NEM) without the aid of energy storage. They find the most advantage from the lack of correlation between wind speed between the NEM’s peripheral states including QLD, SA and TAS.

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