Open Energy Efficiency Meter
EEmeter — an open source toolkit for implementing and developing standard methods for calculating normalized metered energy consumption (NMEC) and avoided energy use.
Background - why use the EEMeter library
At time of writing (Sept 2018), the OpenEEmeter, as implemented in the eemeter package and sibling eeweather package, contains the most complete open source implementation of the CalTRACK Methods, which specify a family of ways to calculate and aggregate estimates avoided energy use at a single meter particularly suitable for use in pay-for-performance (P4P) programs.
The eemeter package contains a toolkit written in the python langage which may help in implementing a CalTRACK compliant analysis.
It contains a modular set of of functions, parameters, and classes which can be configured to run the CalTRACK methods and close variants.
EEmeter is a python package and can be installed with pip.
$ pip install eemeter
Reference implementation of standard methods
CalTRACK Daily Method
CalTRACK Monthly Billing Method
CalTRACK Hourly Method
Flexible sources of temperature data. See EEweather.
Candidate model selection
Data sufficiency checking
First-class warnings reporting
Pandas dataframe support
Roadmap for 2020 development
The OpenEEmeter project growth goals for the year fall into two categories:
Community goals - we want help our community thrive and continue to grow.
Technical goals - we want to keep building the library in new ways that make it as easy as possible to use.
Develop project documentation and tutorials
A number of users have expressed how hard it is to get started when tutorials are out of date. We will dedicate time and energy this year to help create high quality tutorials that build upon the API documentation and existing tutorials.
Make it easier to contribute
As our user base grows, the need and desire for users to contribute back to the library also grows, and we want to make this as seamless as possible. This means writing and maintaining contribution guides, and creating checklists to guide users through the process.
Implement new CalTRACK recommendations
The CalTRACK process continues to improve the underlying methods used in the OpenEEmeter. Our primary technical goal is to keep up with these changes and continue to be a resource for testing and experimentation during the CalTRACK methods setting process.
Hourly model visualizations
The hourly methods implemented in the OpenEEMeter library are not yet packaged with high quality visualizations like the daily and billing methods are. As we build and package new visualizations with the library, more users will be able to understand, deploy, and contribute to the hourly methods.
Weather normal and unusual scenarios
The EEweather package, which supports the OpenEEmeter, comes packaged with publicly available weather normal scenarios, but one feature that could help make that easier would be to package methods for creating custom weather year scenarios.
Greater weather coverage
The weather station coverage in the EEweather package includes full coverage of US and Australia, but with some technical work, it could be expanded to include greater, or even worldwide coverage.
This project is licensed under [Apache 2.0](LICENSE).
CONTRIBUTING: how to contribute to the project.
MAINTAINERS: an ordered list of project maintainers.
CHARTER: open source project charter.
CODE_OF_CONDUCT: Code of conduct for contributors.
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