Wind power has the potential to generate large amounts of electricity, but the intermittency of wind poses an increasingly significant challenge as the wind share of total power increases. Moreover, much of the very best and largest wind resources are remote from electricity demand centers.

These two concerns about wind have been addressed over the last two years in an activity led by Jeff Greenblatt (now at Environmental Defense) and Samir Succar, with contributions from Williams, Socolow, and David Denkenberger. The group’s study found that wind’s intermittency and remoteness can be dealt with, at a price premium, by firming up the wind power to provide baseload electricity, and then transporting that baseload electricity from large wind farms to distant demand centers via dedicated high voltage electric transmission lines.

Two wind power firming strategies were investigated and compared to a natural gas combined cycle plant providing baseload power: wind energy backed up by dedicated natural gas simple cycle and combined cycle generation; and wind energy with compressed air energy storage (CAES). In the CAES option, excess wind power is used to compress air and store it in underground caverns. During times of low wind, air is withdrawn and heated by burning fuel (e.g., natural gas) to power a turbine and generate electricity. Overall, fuel consumption is only one-quarter of that in a natural gas combined cycle plant.

The group’s general methodology enables cost comparisons to be made under a variety of physical and market conditions. The group found that by increasing the value of GHG emissions, wind in combination with one of these backup strategies becomes increasingly attractive relative to the natural gas combined cycle option in providing baseload power. Increasing natural gas prices and decreasing wind turbine cost also strengthen the competitiveness of baseload wind power. The findings of this activity are summarized in Figure 5.

The analysis presented in Figure 5 is for system-wide capacity factors determined by the forced outage rate for each technology. In real energy markets, capacity factors are instead determined by relative dispatch costs (fuel cost plus variable operation and maintenance costs), such that plants with the least dispatch cost are dispatched first. Dispatch costs are lower for the wind-CAES option than for all other options considered, including alternative coal power options, as shown in Table 1. This finding suggests wind-CAES has the potential to provide baseload electricity at the least total cost per kWh, because its deployment would force down the capacity factors of the alternatives via dispatch competition. This outlook also suggests a substantial growth opportunity for natural gas, because wind-CAES makes it feasible for natural gas to compete in baseload power markets despite prospects for high natural gas prices.

One concern with deploying large amounts of wind power is its possible impact on global and regional climate. A study by Steve Pacala’s team in the Science Group incorporated the effects of massively deployed wind turbines on climate and suggested that wind energy production would have minimal impact on global average surface temperature, even if wind power was scaled up to produce 20 trillion watts of electric power (an amount twenty times the entire generating capacity of the United States). On regional scales, however, simulations indicate that temperature changes of up to half a degree Celsius and small but significant changes in precipitation might occur.

Figure 5: Economics of Baseload Wind Power
The four central figures show the comparative economics and least-cost technology under varying conditions among three baseload electricity options (1) natural gas combined cycle (NGCC) (2) wind energy backed by dedicated natural gas simple cycle and combined cycle generation (yellow and green) and (3) wind energy with compressed air energy storage (CAES). Since all three technologies use natural gas as a fuel, the carbon prices in the top figure can also be expressed as an effective fuel price that adds the carbon price to the direct fuel price (top axis).