Calculating energy intensity requires all of the water and energy meter data associated with an asset to be combined and reconciled.
Cleaning and pre-processing of the data can be handled entirely by the analyst, however, there are a few approaches built in to the energyintensity package, which implement commonly used methods. These methods are used to standardize the different time series, so that they can be merged and aggregated. The available methods fall into two general categories: (1) aggregation, and (2) resampling.
library(units)
library(energyintensity)
ps1_energy <- meter_df(time = seq.Date(as.Date("2013-1-1"),
by = "+1 month",
length.out = 12),
electricity = set_units(rnorm(12), kW))
ps1_water <- meter_df(time = seq.Date(as.Date("2013-1-1"),
by = "+1 month",
length.out = 12),
water = set_units(rnorm(12), parse_unit("Mgallon day-1")))
ps1_all <- reconcile(ps1_energy, ps1_water)Once you have a reconciled meter data frame, it is trivial to calculate energy intensity.
ps1_all$ei <- ps1_all$electricity / ps1_all$water
# convert units
ps1_all$ei_kwh_mg <- set_units(ps1_all$ei, parse_unit("kW hour Mgallon-1"))Split non-core components into other packages: - random data generation for simulation and testing - model development vis app - additional extensions?