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pointed out many times, if the government provides incentives for people to build machines, not produce electricity, they focus on putting the cheapest possible machine into the field as quickly as possible. As such, few of the early wind generators lasted much beyond the year in which they were installed. More subtly, because the wind farms had to be up and running by December 31 to get tax credits, the wind farmers’ schedule was incredibly difficult. Come hell, highwater, or massive amounts of overtime, the projects just had to get finished. The haste required made a lot of waste, even for those well-meaning wind farmers who very much wanted to produce good turbines.27

The tax credits were “much too generous—ridiculously so” even by Cashman’s own estimation, but he doesn’t regret the legislative “stick of dynamite” that he threw. “What we did was make it so seductive that they would invest—even if the wind turbines didn’t work.”28

And at first, the wind turbines did not work.

Andy Trenka, who ran a turbine testing program for the Department of Energy at Rocky Flats in Colorado, claims that his team “couldn’t keep the turbines running long enough to get good performance data.”29 And that was in the relatively boring and staid wind climate of Rocky Flats. In California, the wind was more capricious and more intense. Wind is a very, very local resource. Although the general direction and intensity of the wind can be culled from weather and climate models, the specifics of siting require understanding local topology and conditions extremely well. Even now, with all the science, data, and computing power we can muster, individual decisions about where a machine should go are still made on the basis of on-the-ground measurements conducted over the course of a year.30 Understanding and modeling the wind’s three-dimensonality is difficult. Imagine: It’s like constructing a topology map that changes every second.

And, as noted before, because the power that can be extracted from the wind varies with the cube of its speed, small variations in the speed of the wind have an outsized impact on how much electricity can be produced.

The people who rushed into California’s mountain passes did not have detailed wind knowledge from previous study nor did they have time to acquire it, especially given the conditions imposed by the tax incentives. And the bits of knowledge that companies like Kenetech (then known as U.S. Windpower) did generate from wind tunnel testing and experience was treated as a trade secret and kept from public consumption.31

An early Solar Energy Research Institute report then showed the surprise that analysts trying to work with the wind already felt. “Wind turbine developers/operators have been amazed at the enormous variability in energy production within the Pass, both between turbine arrays but especially within arrays,” the report’s authors wrote.32 Within a single ranch, the quality of potential turbine locations varied tremendously. The best site had a wind energy potential two-and-a-half greater times than the worst. Yet they were separated by just half a mile and only sixty feet of elevation.

Wind energy assessments began to be carried out in the mid-1970s, but they returned large data discrepancies and methodological issues. The Department of Energy and the Pacific Northwest National Laboratory steadily improved the quality of data and maps. But it took a decade to provide high-resolution maps that were useful for more than the coarsest analysis.33

The net effect of all of the immature technology and lack of data was that—frauds aside—wind technology companies started out posting terrible early results. In the early days, the companies routinely overestimated how much wind power they could produce. Furthermore, machines broke down, pitched blades, and nothing worked as expected. A 1981 survey found the life span of the first generation of turbines was only seven hours.34

Kenetech was the first company to install a wind farm at Altamont on the last day of 1980. They pressed a machine into service