Incorporation of electricity GHG emissions intensity variability into building environmental assessment

Highlights: • Current building assessment does not account for variability in the electric grid. • A new method incorporates hourly grid variability into building assessment. • The method is complementary with peak-shaving policies. • The assessment method can affect building design decisions. - Abstract: Current building energy and GHG emissions assessments do not account for the variable performance of the electric grid. Incorporating hourly grid variability into building assessment methods can help to better prioritize energy efficiency measures that result in the largest environmental benefits. This article proposes a method to incorporate GHG emissions intensity changes due to grid variability into building environmental assessment. The proposed method encourages building systems that reduce electricity use during peak periods while accounting for differences in grid GHG emissions intensity (i.e., peak shaving is more strongly encouraged in grids that have GHG intense peak generation). A set of energy saving building technologies are evaluated in a set of building variants (office, residential) and grid types (hydro/nuclear dominated, coal/gas dominated) to demonstrate the proposed method. Differences between total GHG emissions calculated with the new method compared with the standard (which assumes a constant GHG emissions intensity throughout the year) are in the 5–15% range when the contribution of electricity to total GHG emissions is more significant. The influence of the method on the assessment of the relative performance of some energy efficiency measures is much higher. For example, the estimated GHG emissions savings with heat pumps and photovoltaics can change by −40% and +20%, respectively, using the new assessment method instead of the standard. These differences in GHG emissions estimates can influence building design decisions. The new method could be implemented easily, and would lead to better decision making and more accurate estimates of the emissions from buildings and building technologies.