Introducing new technologies into existing residences provides opportunities for the utility to enhance a community's power system performance. To validate the benefits of such technologies, an energy model is required in which their integration with a community's power system may be simulated. It can be difficult or impossible to properly model a power system without sufficient sample data. This paper proposes a method that uses Gaussian kernel density estimation (GKDE) to calculate the aggregated net power flow of a community's distribution system with only limited sample points at each time step. Example case studies that confirm the usefulness of the GKDE method are presented in which the power system benefits of improved insulation and heating, ventilation, and air conditioning (HVAC) system control are analyzed. This analysis was performed using an EnergyPlus (EP) house model that was created and calibrated based upon an individual house. This power representation of the individual house was determined by accurately estimating the aggregated net power flow of a community in Glasgow, KY with GKDE. Simulation results based on the equivalent house energy model show that improved insulation reduces the energy consumption and the peak power at the power system level. Simulation results also show that the HVAC control reduces the peak power for the entire community.

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Conference Proceeding

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Notes/Citation Information

Published in 2020 IEEE Power & Energy Society General Meeting (PESGM).

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The document available for download is the authors’ manuscript version accepted for publication. The final published version is copyrighted by IEEE and is available as: H. Gong, E. S. Jones, and D. M. Ionel, “An Aggregated and Equivalent Home Model for Power System Studies with Examples of Building Insulation and HVAC Control Improvements,” Rec. 2020 IEEE Power & Energy Society General Meeting (PESGM), Montreal, Canada, Aug 2020, pp. 1-4, doi: 10.1109/PESGM41954.2020.9281438

Digital Object Identifier (DOI)


Funding Information

The support of University of Kentucky, the L. Stanley Pigman endowment, and of the SPARK program and the Power and Energy Institute of Kentucky (PEIK) is gratefully acknowledged.