Skip to content

Releases: davidusb-geek/emhass-add-on

EMHASS add-on v0.11.4

24 Dec 09:19
Compare
Choose a tag to compare

Fix

  • Fix bug when treating runtime params, fix optimization_time_step timedelta

Full Changelog: v0.11.3...v0.11.4

EMHASS add-on v0.11.3

23 Dec 13:44
Compare
Choose a tag to compare

0.11.3 - 2024-10-31

Improvement

  • Runtime parameters now support all config parameters
  • Adopted the Ruff code fomatting
  • Added a Github Actions for Google OSV security code scan
  • Updated the param_definitions.json
  • Bump skforecast from 0.13.0 to 0.14.0. This needed upgrading a bunch of deprecated options. Notably skforcast now uses the time series cross-validation object (cv) from sklearn

Fix

  • Updated the default battery optimization weights
  • Fix publish_data defaulting to opt_res_latest, tweak warning logs
  • Added MLForecaster options to load_forecast_method for param_definitions.json

Full Changelog: v0.11.2...v0.11.3

EMHASS add-on v0.11.2

31 Oct 00:19
Compare
Choose a tag to compare

Improvement

  • Added support to retrieve HA configuration. This will be used in the future to automatically retrieve some parameters as the currency

Fix

  • utils fix runtime parameter merge bugs
  • configuration_script.js fix placeholder value bug

Full Changelog: v0.11.1...v0.11.2

EMHASS add-on v0.11.1

29 Oct 00:07
Compare
Choose a tag to compare

Fix

  • Fix parameter saving and duplicate battery bugs
  • utils.py add more specific logging information for config
  • Fix issue where thermal runtime parameters were not being propagated into optim_conf

What's Changed

  • Update README.md from emhass/README.md by @GeoDerp in #104

Full Changelog: v0.11.0...v0.11.1

EMHASS add-on v0.11.0

25 Oct 22:01
Compare
Choose a tag to compare

This version marks huge improvement works by @GeoDerp aiming to simplfy the intial and normal setup of EMHASS. The workflow for setting the EMHASS configuration regardless of the installation method has now been centralized on the single config.json file. The webserver has now a configuration tab that can be used to to modify and save the config.json file.

The complete discussion of the changes on this thread:
davidusb-geek/emhass#334

Automatic version bot improvements

  • Bump h5py from 3.11.0 to 3.12.1
  • Bump markupsafe from 2.1.5 to 3.0.2

What's Changed

Full Changelog: v0.10.6...v0.11.0

EMHASS add-on v0.10.6

13 Jul 23:29
Compare
Choose a tag to compare

Fix

  • Fixed bug on predicted room temeprature publish, wrong key on DataFrame

Full Changelog: v0.10.5...v0.10.6

EMHASS add-on v0.10.5

12 Jul 20:33
Compare
Choose a tag to compare

Improvement

  • Added support for pubishing thermal load data, namely the predicted room temperature

Full Changelog: v0.10.4...v0.10.5

EMHASS add-on v0.10.4

09 Jul 23:13
Compare
Choose a tag to compare

In this release a new thermal modeling for deferrable loads.
Thanks to @werdnum for this contribution!

Improvement

  • Added a new thermal modeling, see the new section in the documentation for help to implement this of model for thermal deferrable loads
  • Improved documentation

Full Changelog: v0.10.3...v0.10.4

EMHASS add-on v0.10.3

06 Jul 21:18
Compare
Choose a tag to compare

Some minor improvements:

Improvement

  • Added improved support for def_start_penalty option
  • Improved documentation

What's Changed

  • Davidusb geek/dev/preparing new version by @davidusb-geek in #97
  • en.yaml add description for list_set_deferrable_startup_penalty by @GeoDerp in #98

Full Changelog: v0.10.2...v0.10.3

EMHASS add-on v0.10.2

05 Jul 22:51
Compare
Choose a tag to compare

In this release:

Improvement

  • Weather forecast caching and Solcast method fix by @GeoDerp
  • Added a new configuration parameter to control wether we compute PV curtailment or not
  • Added hybrid inverter to data publish
  • It is now possible to pass these battery parameters at runtime: SOCmin, SOCmax, Pd_max and Pc_max

Fix

  • Fixed problem with negative PV forecast values in optimization.py, by @GeoDerp

Full Changelog: v0.10.1...v0.10.2