Wisconsin's Public Benefits Approach to Quantifying Environmental Benefits: Creating Different Emissions Factors for Peak/Off-Peak Energy Savings

David Sumi and Jeff Erickson, PA Government Services Inc.
Jim Mapp, Wisconsin Department of Administration, Division of Energy

Keywords

Abstract

This paper will present an extended approach and preliminary results for the quantification of environmental benefits in Wisconsin’s Focus on Energy Program. A key objective of the evaluation is to document the environmental benefits associated with avoided electricity generation attributable to energy impacts of the Department of Administration’s statewide programs, with specific attention to reductions in air pollutants (NOx and SO2) and emissions of the green house gas CO2.

The emissions model described in this paper was developed as an expansion of a model developed under the pilot Focus on Energy program by staff from Lawrence Berkeley National Laboratory (LBNL). The earlier model used plant-specific data from Energy Information Administration’s (EIA’s) National Energy Modeling System to calculate emissions rates for each plant. This approach was taken to create a simple, straight-forward model that provides area-wide emissions factors that could be used to calculate emissions savings from energy efficiency programs. The emissions factors created in this model are applied across full-year savings, regardless of seasonal or daily variations in energy savings patterns. Since some kinds of energy efficiency measures and some kinds of programs are more likely to create energy savings in certain times of the year or certain times of day, it seemed a natural extension of this model to examine emissions on a seasonal and peak vs. off-peak basis. This paper describes the extension of the model using hourly emissions and energy data to calculate winter and summer, peak and off-peak emission factors. We present results of the model, application to early evaluation energy savings results, discuss a possible interpretation of the results, and discuss possible enhancements to the model.