Core methods, models, and structures for the Open Energy Efficiency meter.
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README.rst

EEmeter: tools for calculating metered energy savings

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EEmeter — open source implementations of standard methods for calculating metered energy savings.

The eemeter contains the reference implementation of the CalTRACK methods for computing metered energy usage differences at sites with building efficiency interventions or at control sites without known interventions.

Installation

EEmeter is a python package and can be installed with pip.

$ pip install eemeter

Features

  • Candidate model selection
  • Data sufficiency checking
  • Reference implementation of standard methods
    • CalTRACK Daily Method
    • CalTRACK Monthly Method
  • Flexible sources of temperature data. See EEweather.
  • Model serialization
  • First-class warnings reporting
  • Pandas dataframe support
  • Visualization tools

Command-line Usage

Once installed, eemeter can be run from the command-line. To see all available commands, run eemeter --help.

Use CalTRACK methods on sample data:

$ eemeter caltrack --sample=il-electricity-cdd-hdd-daily

Save output:

$ eemeter caltrack --sample=il-electricity-cdd-only-billing_monthly --output-file=/path/to/output.json

Load custom data (see eemeter.meter_data_from_csv and eemeter.temperature_data_from_csv for formatting):

$ eemeter caltrack --meter-file=/path/to/meter/data.csv --temperature-file=/path/to/temperature/data.csv

Do not fit CDD-based candidate models (intended for gas data):

$ eemeter caltrack --sample=il-gas-hdd-only-billing_bimonthly --no-fit-cdd