Characterization of the Life Cycle Environmental Impacts and Benefits of Smart Electric Meters and Consequences of their Deployment in California
- Author(s): Sias, Glenn Gregory
- Advisor(s): Ambrose, Richard F;
- Rajagopal, Deepak
- et al.
Electric utilities across the United States and the world are involved in large scale efforts to develop electric smart grids, of which smart meters are a key component. In this dissertation, I use life-cycle assessment (LCA) techniques to characterize the environmental impacts and benefits of the recent smart meter deployment in California and of smart meter-enabled programs to manage electrical demand.
Background on smart meters, smart grid, electrical generation in California, and integrated demand side management is presented in Chapter 1. I highlight the key role smart meters will play in new initiatives to manage residential electrical demand; to reduce the greenhouse gas (GHG) emissions from electricity consumption; and to facilitate the incorporation of increased amounts of renewable generation into California’s grid mix.
In Chapter 2, results are presented from a comparative, attributional LCA of a smart electric meter and a conventional meter. I find that the smart meter has a larger footprint relative to the conventional meter for each of seven different environmental burdens investigated including global warming potential. The use phase dominates the production and end-of-life phases for both meters driven primarily by electricity used to operate both meters. The elimination of manual meter reading due to smart meter deployment provides some environmental benefits but not enough to offset increased impacts from the smart meter. This LCA establishes baseline impacts for the smart meter’s life cycle that can be used to assess the consequences of its deployment in California.
I next characterize potential future benefits from smart meter-enabled load reduction (energy efficiency and conservation) programs and investigate scenarios informed by the literature on information strategies and conservation under which these benefits could offset smart meter impacts. I find that smart meter-enabled load reduction programs in California have high potential to yield significant environmental benefits including reductions in GHG emissions. These benefits could be even greater in states with more GHG-intensive grid mixes. My analyses of the environmental payback period and the effect of participation rates demonstrate these benefits are achievable, even with low levels of conservation and participation. However, data from smart meter-enabled load reduction programs in California demonstrate environmental benefits have yet to materialize primarily due to low participation rates.
In Chapter 4, smart meter-enabled demand response (or load shifting) programs in California are investigated. Utility data demonstrate existing programs can yield overall load reduction in addition to load shifting, but they also shift electricity use from peak demand periods with lower GHG-intensive grid mixes to those with higher GHG intensity. However, increases in GHG emissions from load shifting are offset by overall energy conservation seen amongst program participants during demand response event days. This results in reductions in GHG emissions that partially offset annual emissions increases due to smart meter deployment.
In the last chapter, conclusions from this research are presented along with policy recommendations to drive more effective smart meter-enabled, integrated demand side management programs. Areas for future research are also identified.