The USgrid R package provides a set of high frequency (hourly) time-series datasets, describing the demand and generation of electricity in the US (lower-48 states, excluding Alaska and Hawaii). That includes the following series:

  • US_elec - the total hourly demand and supply (generation) for electricity in the US since July 2015

  • US_source - the US net generation of electricity by energy source (natural gas, coal, solar, etc.) since July 2018

  • Cal_elec - The California subregion hourly demand by operator since July 2018

All datasets are in tsibble format

Source: US Energy Information Administration, Dec 2019

Installation

Install the stable version from CRAN:

or install the development version from Github:

Examples

The hourly demand and generation (supply) of electricty in the US:

library(USgrid)
library(plotly)

data(US_elec)

plot_ly(data = US_elec,
        x = ~ date_time,
        y = ~ series,
        color = ~ type,
        colors = c("#66C2A5","#8DA0CB"),
        type = "scatter",
        mode = "lines") %>%
        layout(title = "US Electricity Demand vs. Supply (Hourly)",
               yaxis = list(title = "Mwh"),
               xaxis = list(title = "Source: US Energy Information Administration (Dec 2019)"))

The hourly generation (supply) of electricty in the US by source:

plot_ly(data = US_source,
        x = ~ date_time,
        y = ~ series,
        color = ~ source,
        type = "scatter",
        mode = "lines") %>%
  layout(title = "US Electricity Generation by Energy Source",
         yaxis = list(title = "Mwh"),
         xaxis = list(title = "Source: US Energy Information Administration (Dec 2019)"))

The California subregion hourly demand by operator

plot_ly(data = Cal_elec,
        x = ~ date_time,
        y = ~ series,
        color = ~ operator,
        type = "scatter",
        mode = "lines") %>%
  layout(title = "California Hourly Demand by Operator",
         yaxis = list(title = "Mwh"),
         xaxis = list(title = "Source: US Energy Information Administration (Dec 2019)"))