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DOE OSTI · 1871588

Solar Photovoltaics: Supply Chain Deep Dive Assessment

Abstract

This is one of a series of reports and deep dive assessments produced in response to Executive Order 14017 “America’s Supply Chains,” which directs the Secretary of Energy to submit a report on supply chains for the energy sector industrial base. The Executive Order is helping the federal government to build more secure and diverse U.S. supply chains, including energy supply chains. Over the past decade, solar power has gone from an emerging, niche technology to a mature energy industry. By 2035, solar power could supply 40% or more of U.S. electricity demand, dramatically accelerating the decarbonization of buildings, transportation, and industry; and, if current technology trends continue, it could do so without increasing the price of electricity. The rapid expansion of solar energy has the potential to yield broad benefits in the form of economic activity and workforce development. The solar industry already employs roughly 230,000 people in the United States, at an average wage that is higher than the national average for most comparable positions. By decarbonizing the electricity sector by 2035, the U.S. solar industry could employ 500,000–1,500,000 people by 2030. The components that are assembled to install a photovoltaic power system are produced by a global supply chain. Photovoltaic (PV) modules (also called panels) are made of cells that use a variety of technologies. There are two leading types of solar modules used in the United States, with crystalline silicon (c-Si) modules representing 84% of the market and cadmium telluride (CdTe) modules representing 16% of the market. Modules of either type require mounting structures to provide mechanical support (racking), which may be configured to follow the sun (tracking). The output of any PV module is direct current (dc), which is almost always converted to alternating current (ac) by an inverter.

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Basore, Paul, Feldman, David. 2022-02-24. Solar Photovoltaics: Supply Chain Deep Dive Assessment. https://doi.org/10.2172/1871588

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