Sensitivity analysis helps investigate how the variation (or uncertainty) in the output of a mathematical model can be apportioned, qualitatively or quantitatively, to different sources of variation in the input parameters of a model. Put differently, it is a technique for systematically changing parameters in a model to determine the effects of such changes. In this study, the capacity factor (CP) could be influenced by wind conditions, turbine technology, rated power and many other factors, so it is crucial in this calculation as it determines the quantity of elec- tricity generation from wind power plants. In case 1, whose CP 1⁄4 40.7%, a 10% increase of CP will result in 8% decrease in CO2 emissions per kWh. This means that the sensitivity of the CP to the result is about 0.8. The sensitivity of a 10% CP increase for other cases is shown in Table 8. The case with higher original CP would have higher sensitivity of CP, which means the marginal benefit on CO2 emissions will increase with increasing CP. Therefore, the measures taken to increase the CP would be more rewarding.