This study evaluates potential aggregate effects of net-zero energy home (NZEH) implementations on the U.S. electrical grid in a simulation-based analysis. The aggregate impact of large-scale NZEH implementations on the U.S. electrical grid is evaluated through a simulation-based study of prototype residential building models with distributed photovoltaic (PV) generation systems. An EnergyPlus residential prototype building model (i.e., a multi-family low-rise apartment building) is used to determine the detailed electricity consumption of each residential building model using U.S. climate weather files. This study assumes that net-metering is available on the electrical grid so that the surplus on-site electricity generation can be fed to the electrical grid. This study also considers the impact of electrical energy storage (EES) within NZEHs to effectively use on-site generated electricity on the electrical grid. Finally, surveyed residential building permits in 2017 are used to estimate net-electricity demand profiles of NZEHs on a national scale. Results indicate that adding distributed PV systems to enable annual multi-family NZEH performance can significantly increase changes in imported and exported electricity demand from and to the electrical grid during the daytime. However, using the EES within NZEHs helps reduce the peak electricity demand during the daytime. The stored electricity in the EES can also be used during the evening time. The peak net-electricity differences on the U.S. electrical grid-level could potentially be reduced during the daytime and shifted to the evening. Comparison of hourly electricity demand profiles for the actual U.S. demand versus the calculated net-demand on a national scale indicates that the percentage differences of U.S. net-electricity demand include about 4.5% and 4.8% for the multi-family NZEH without the EES on representative winter and summer days, respectively, at a maximum point. In addition, when the EES is added within the multi-family NZEH, the peak percentage differences could be reduced to about 3.4% and 4.3% on representative winter and summer days, respectively, at a maximum point.

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