Advanced Metering Infrastructure Deployment in the United States: The Impact of Polycentric Governance and Contextual Changes

Abstract

Advanced metering infrastructure provides the first building block in smart grids by empowering customers and utilities with real-time information regarding energy use. It is a key element in the U.S. government's push for electric grid modernization. Using a panel dataset for 50 U.S. states and the District of Columbia over the years 2007-2012, we evaluate the impacts of a polycentric governance system and socioeconomic contexts on states' performance in smart metering deployment. We find that the advanced metering technological change in the United States has been exclusively created by the interdependencies and interactions between different layers of government. High-tech industry is the only socioeconomic factor that has a negative impact on smart meter deployment, whereas other factors, such as pressures from energy consumers and environmental groups, and electric grid conditions, have negligible impacts.KEY WORDS: advanced metering infrastructure, technology diffusion, polycentric governance, fixed effects models 646 bs_bs_banner

The Early Diffusion of Smart Meters in the US Electric Power Industry

“…Duration analysis and fractional response analysis of smart meter adoption in the United States suggest that policy and regulatory support have positively influenced adoption and thus the rate and level of smart meter diffusion. This is consistent with the findings of Zhou and Matisoff (2016), but I also find that utility characteristics and some combination of learning, cost reductions, and technology standards are important. In the absence of public policy support for smart meter adoption, it is likely that the rate and level of smart meter diffusion would be lower than they currently are.…”

“…In the absence of public policy support for smart meter adoption, it is likely that the rate and level of smart meter diffusion would be lower than has occurred. This finding is consistent with previous research (Zhou and Matisoff 2016), but I also find that utility characteristics and some combination of learning, cost reductions, and technology standards are important determinants.…”

“…Although the econometric analysis of the previous chapter investigates the effects of smart meter diffusion policies, it does not explore theories of diffusion policy and rationales for the specific diffusion policies enacted. The empirical analysis suggests a prominent role for policy in extending the diffusion of smart meters, which is consistent with previous research (Zhang 2010;Spodniak, Jantunen, and Viljainen 2014;Zhou and Matisoff 2016). Three aspects of diffusion policy, and public policy in general, frame the discussion in this chapter: rationale, instruments, and impact.…”

“…In previous research on the diffusion of smart meters only one econometric model has been applied. Zhou and Matisoff (2016) use a linear panel analysis approach to model smart meter diffusion across the fifty United States using states as observational units. The authors use the same EIA dataset that I use but differ from my analysis by focusing exclusively on the impact of public policies across states and their interac-tion with federal policies.…”

Over a Decade of Scholarship on the Politics and Policy of Science and Technology

“…Over 60 articles in the last eleven years deal with energy in some fashion, which encompasses research on specific types of power generationwind (Laird, 2008), solar (Smith & Urpelainen, 2014), biofuels (L. A. German & Schoneveld, 2012), and renewables as an overall category (Rowlands, 2007)-to broader analyses of the energy sector and demand-side and grid management such as through smart metering technologies (Zhou & Matisoff, 2016).…”