Joseph Brewer

Utah State University

Subject Areas: Smart Meter Data Management

 Recent Activity

ABSTRACT:

As global populations continue to increase and become more urbanized, relationships between water and energy are becoming more important. Both are limited in supply, but both are required to satisfy the needs of residential water users. In the context of urbanization and residential water use, domestic hot water (DHW), which is a resource consumed in nearly every residential structure in the developed world, represents one of the most significant water-related uses of energy. However, quantifying hot water use and the energy associated with heating it can be difficult. Water and energy use are typically evaluated separately, and paired datasets that enable direct evaluation of hot water use and its associated energy consumption are rare. Yet, quantifying water and water-related energy use are important in better understanding how they are linked and in identifying opportunities for conservation. We collected high resolution water use and water temperature data within five multi-unit residential structures on a college campus and then developed a water and energy budget model for quantifying water and water-related energy consumption within each building. Results showed varying behavioral consumption patterns across the buildings. Results also showed tradeoffs between data volume and ability to quantify use associated with sampling and data recording frequency. This resource is the result of an effort to establish reproducibility of the methods undertaken to quantify and characterize water and water-related energy with high-resolution smart meter data in multi-unit residential structures. This undertaking was a part of the research obligations associated with a Masters thesis completed at Utah State University in Aug 2020.

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ABSTRACT:

ThisPython script was developed as part of a semester project that tests a hydroinformatics data architecture for high-resolution smart meter water-use in a case study of multi-resident structures. The script is a basic visualization tool for the researcher to quickly, and simply, query collected one-second resolution hot and cold water flowrate data.

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ABSTRACT:

This resource contains a Jupyter Notebook that connects to a hydrologic data web service, downloads hydrologic data, performs some statistical analysis, and visualizes the results. The purpose of this notebook is to provide a simple method for reproducing visualizations of USGS 15-minute discharge data. With editable parameters for USGS siteID and time interval, the notebook can quickly be modified to display results from the desired USGS site and measurement period.

In summary, the code in the Notebook performs the following tasks:
1) Connect to the USGS WaterOneFlow web service
2) Based on SiteID and begin/end date parameters, 15-minute discharge data is downloaded.
3) Resample 15-minute data to daily data while also calculating max, min, and avg values for the day
4) Plot the daily max, daily min, daily avg, and raw 15-minute discharge data on a single plot for comparison,

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Resources
All 0
Collection 0
Composite Resource 0
Generic 0
Geographic Feature 0
Geographic Raster 0
HIS Referenced Time Series 0
Model Instance 0
Model Program 0
MODFLOW Model Instance Resource 0
Multidimensional (NetCDF) 0
Script Resource 0
SWAT Model Instance 0
Time Series 0
Web App 0
Composite Resource Composite Resource

ABSTRACT:

This resource contains a Jupyter Notebook that connects to a hydrologic data web service, downloads hydrologic data, performs some statistical analysis, and visualizes the results. The purpose of this notebook is to provide a simple method for reproducing visualizations of USGS 15-minute discharge data. With editable parameters for USGS siteID and time interval, the notebook can quickly be modified to display results from the desired USGS site and measurement period.

In summary, the code in the Notebook performs the following tasks:
1) Connect to the USGS WaterOneFlow web service
2) Based on SiteID and begin/end date parameters, 15-minute discharge data is downloaded.
3) Resample 15-minute data to daily data while also calculating max, min, and avg values for the day
4) Plot the daily max, daily min, daily avg, and raw 15-minute discharge data on a single plot for comparison,

Show More
Composite Resource Composite Resource
USU LLC Flowrate Data Visualization Tool
Created: Dec. 3, 2018, 10:08 p.m.
Authors: Joseph Brewer

ABSTRACT:

ThisPython script was developed as part of a semester project that tests a hydroinformatics data architecture for high-resolution smart meter water-use in a case study of multi-resident structures. The script is a basic visualization tool for the researcher to quickly, and simply, query collected one-second resolution hot and cold water flowrate data.

Show More
Composite Resource Composite Resource

ABSTRACT:

As global populations continue to increase and become more urbanized, relationships between water and energy are becoming more important. Both are limited in supply, but both are required to satisfy the needs of residential water users. In the context of urbanization and residential water use, domestic hot water (DHW), which is a resource consumed in nearly every residential structure in the developed world, represents one of the most significant water-related uses of energy. However, quantifying hot water use and the energy associated with heating it can be difficult. Water and energy use are typically evaluated separately, and paired datasets that enable direct evaluation of hot water use and its associated energy consumption are rare. Yet, quantifying water and water-related energy use are important in better understanding how they are linked and in identifying opportunities for conservation. We collected high resolution water use and water temperature data within five multi-unit residential structures on a college campus and then developed a water and energy budget model for quantifying water and water-related energy consumption within each building. Results showed varying behavioral consumption patterns across the buildings. Results also showed tradeoffs between data volume and ability to quantify use associated with sampling and data recording frequency. This resource is the result of an effort to establish reproducibility of the methods undertaken to quantify and characterize water and water-related energy with high-resolution smart meter data in multi-unit residential structures. This undertaking was a part of the research obligations associated with a Masters thesis completed at Utah State University in Aug 2020.

Show More