Enhancing Carbon Reduction Estimation: A Time-Centric Analysis of Vermont's Clean Energy Programs
Vermont’s clean energy program efforts now include transitioning fossil fuel energy use onto an increasingly renewable electric grid and shifting energy time of use to periods where renewable energy is most abundant. Quantifying carbon reduction as a result of these efforts might require greater consideration for the time component of energy use. A more granular accounting of program outcomes would be possible with higher-frequency data sources for carbon emissions and program impact. This project explores the value of higher frequency methods to better inform impact estimates for carbon reduction, with two separate modeling exercises that compare carbon reduction estimates: one that reviews annual emissions reductions for a historical project scenario and compares estimations to a ground truth based on actual emissions data from the ISO New England, and a second that explores a program implementation context to compare those same methods to current program impact estimation practices using long-run emissions data from the New England Avoided Energy Supply Cost study. Ultimately, the researchers found using an average emission factor to determine the emissions saved by a particular measure is nearly as accurate as using an actual, unique emission factor for every hour of the year, with rare exceptions.