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Powering the Dream_ The History and Promise of Green Technology - Alexis Madrigal [133]

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investments.10 Gross unknowingly echoed Etzler’s thinking in deciding to make small, flat mirrors that would huddle close to the ground, reducing the wind’s effects. In fact, the mirrors are so small—less than two square meters—that they are “self-ballasting,” meaning that they aren’t actually screwed into the ground. Their diminutive size also means they can be manufactured in a factory and shipped to a project.

All these ideas may have made sense to previous engineers, but when the mirrors get that tiny, the enormous numbers of mirrors need to be controlled precisely. A single forty-six-megawatt eSolar modular unit uses a field of 200,000 mirrors. By fossil fuel standards, even a modest-sized plant of 230 megawatts would use one million mirrors. In the past, that would have been a daunting software control problem. Every single mirror needs to be independently pointed to keep the plant working. Gross said that

in the last decade, there’s been a 1,000-fold increase in computational power, so now we can put a $2 microprocessor in every mirror and it costs almost nothing—about one and half percent of the material cost. So every mirror that is tracking the sun during the day has its own computer. And the computational power of a microprocessor today is mind-boggling. It’s a 16-bit microprocessor with eight I/O ports. It’s like an IBM AT (PC) in every mirror—that was a $5,000 computer in 1985. This completely wouldn’t be possible without Moore’s Law.11

In the classic formulation, Moore’s Law holds that the number of transistors on an integrated chip would double every eighteen months. Though the definition has been extended and squished and morphed since Intel chief Gordon Moore first brought the idea into the mainstream in 1965, the basic storyline still holds.12 As Gross likes to say, commodity prices are headed up in the coming years whereas “CPU power per dollar” continues to get cheaper. He’s structured eSolar to take maximum advantage of cheap computation. They should have plants running in the United States, India, and China in the next few years, and all of them will be running the same algorithms. Improvements in software in any of the plant locations will be portable to its cousins overnight. “Now that we see and saw that software is the solution, we push for it even harder to see if you can make a power plant that has a larger software component and less steel,” Gross concluded.

By applying information technology to energy problems, eSolar is one company among many new venture backed–startups that has realized that they can achieve major breakthroughs. To twist the old Danish wind mantra that many problems could be solved by “throwing steel on the problem,” these entrepreneurs are learning how to throw software on the problem. Beyond the code first, Gross and his ilk are also bringing a new sensibility to energy space. Silicon Valley technologists live for disruption. Weaned in the computer industry, their engineers do not have the same sense of technological aesthetics or traditions that engineers who work for utilities and power companies do.

The software and computer entrepreneurs who are pouring into green tech bring into the energy space fundamentally different ideas about the way technology and organizations should work. Historian Thomas Hughes identified the ways in which what he calls the second industrial revolution—closely linked to electrification—differs from the information age. “Hierarchy, specialization, standardization, centralization, expertise, and bureaucracy became the hallmarks of management during the second industrial revolution,” Hughes wrote. “Flatness, interdisciplinarity, heterogeneity, distributed control, meritocracy and nimble flexibility characterize information-age management.”13

Silicon Valley, in particular, has a fundamentally different culture from the industrial ones that preceded it. The Valley is into “information sharing, collective learning, informal communication,” and the companies it produces are usually fast-moving startups who are flexible and networked.14 It

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