This report investigates the effect of increasing the number of wind turbine generators on carbon dioxide emission 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 carbon dioxide emissions. 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 also use sensitivity analysis to evaluate the effect on carbon dioxide emissions 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 increasing wind power penetration decreases carbon dioxide emissions but retail prices fail to reflect the decrease in carbon dioxide emissions. We find Victoria has the largest carbon dioxide emissions and of the states in the NEM Victoria’s emissions respond the least to increasing wind power penetration. Victoria having the largest brown coal generation fleet in the NEM explains this unresponsiveness. Wind power via the merit order effect displaces the more expensive fossil fuel generators first in the order gas, black coal and brown coal. However, brown coal has the highest carbon dioxide emissions per unit of electricity. This is suboptimal for climate change mitigation and the reintroduction of a carbon pricing mechanism would adjust the relative costs of fossil fuels favouring the fuels with the lower emissions per unit of electricity. We find that uncertainty in electricity demand and the renewable energy target are hindering the deployment of wind power. Electricity demand uncertainty stems from permanent structural changes such as downward pressure on demand from the decline in manufacturing, price sensitivity, technological efficiency and meeting electricity demand behind the meter via solar PV and solar water heating. Electricity demand uncertainty also stems from cyclical uncertainty of the El Niño Southern Oscillation (ENSO). The recent reduction of the LRET from the 41 TWh to 20% of demand reflects both permanent and cyclic changes. Both the recent reduction and the annual review of the RET induces investment uncertainty for wind power generators. Introducing a 100% RET and making the percent a moving average of the demand of the last 10 years would encourage retailers to purchase the LRET certificates, help reduce investment uncertainty and accommodate the structural changes in electricity demand. We find transmission congestion is reducing wind power’s ability to reduce emissions. This is particularly noticeable in South Australia (SA) where there are negative wholesale prices inducing spillage of wind power. Factors causing this situation are SA large wind deployment and relatively small demand base plus interconnectors between SA and VIC that quickly exceed their maximum capacity. In further research, we (Bell et al. 2015b, 2015c) investigate augmenting the NEM’s transmission grid to reduce carbon dioxide emissions across the NEM and address the price differential between states under increasing wind power penetration.