Residential Precooling on a high-solar grid: Impacts across home designs and California climate zones: Data Repository

Published: 2 May 2023| Version 1 | DOI: 10.17632/333jfmpvb8.1
Contributor:
Stepp Mayes

Description

Data supporting the research for the article "Residential Precooling on a high-solar grid: Impacts across home designs and California climate zones." This study focused on analyzing building precooling in the residential sector in California. We analyze four single-family home designs in 16 climate zones to determine precooling's impact on peak electricity loads, CO2 emissions, and residential electricity costs. use EnergyPlus to simulate 480 distinct precooling schedules as well as a constant setpoint schedule as a reference point over a three month period. We find that for most building types and locations, there exists a precooling schedule that simultaneously reduces all three target variables. This data repository includes three main datasets. The first dataset includes information on the emissions associated with electricity demand in the CAISO region. This data was generated by tracking emissions and generation from powerplants within the CAISO region, as well as accounting for the trade of electricity between balancing authorities (and the associated traded emissions). The second dataset contains information about the buildings simulated in this study. These buildings came from NREL's ResStock project and are available for download free online. Their properties are summarized in the table included here. The third dataset is a summary of the results of each precooling simulation. These are aggregate results over the three month simulation period, with a separate table for climate zone and building combination. Please reach out to ktsanders@usc.edu or steppmay@usc.edu for questions about this dataset.

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Institutions

University of Southern California

Categories

Solar Energy, Energy Demand, Building, Air Conditioning

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