The Solar Foundation’s National Solar Jobs Census 2014 is the fifth annual update of current employment, trends, and projected growth in the U.S. solar industry.
Resources tagged Renewable Energy Deployment
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Capturing the value that solar photovoltaic (PV) systems may add to home sales transactions is increasingly important. This study enhances the PV-home-valuation literature by more than doubling the number of PV home sales analyzed (22,822 homes in total, 3,951 of which are PV) and examining transactions in eight states that span the years 2002–2013.
In this report, the authors examine California's leadership in US expansion of renewable energy electricity generation by discussing first the boom in utility-scale solar farms in California and the subsequent employment effects of having built 4,250 MW of utility-scale solar powered electricity generating facilities in California over the last five years.
In the report, a team of researchers from Yale University, University of Wisconsin-Madison, University of Texas-Austin, and Lawrence Berkeley National Laboratory empirically examined heterogeneity in PV prices in the United States.
This whitepaper, commissioned by Oncor Electric Delivery Company, shows that deploying electricity storage on distribution systems across Texas could provide substantial net benefits to the state.
U.S. Solar Market Insight™ is a collaboration between the Solar Energy Industries Association® (SEIA®) and GTM Research that brings high-quality, solar-specific analysis and forecasts to industry professionals in the form of quarterly and annual reports. Released December 9, 2014.
In this report, Rocky Mountain Institute (RMI), with support from the U.S. Department of Energy’s SunShot Initiative, investigates opportunities to optimize and demonstrate DPV’s value as it is integrated into the grid to utilities, customers, and solar companies alike.
As distributed generation continues its rapid expansion, these new resources will have an increasingly larger role.
To identify opportunities to decrease costs associated with residential PV adoption, in this letter we use multivariate regression models to analyze a unique, household-level dataset of PV adopters in Texas (USA) to systematically quantify the effect of different information channels on aspiring PV adopters’ decision-making.