This fix implements the long term goal to have the EOS server run optimization (or
energy management) on regular intervals automatically. Thus clients can request
the current energy management plan at any time and it is updated on regular
intervals without interaction by the client.
This fix started out to "only" make automatic optimization (or energy management)
runs working. It turned out there are several endpoints that in some way
update predictions or run the optimization. To lock against such concurrent attempts
the code had to be refactored to allow control of execution. During refactoring it
became clear that some classes and files are named without a proper reference
to their usage. Thus not only refactoring but also renaming became necessary.
The names are still not the best, but I hope they are more intuitive.
The fix includes several bug fixes that are not directly related to the automatic optimization
but are necessary to keep EOS running properly to do the automatic optimization and
to test and document the changes.
This is a breaking change as the configuration structure changed once again and
the server API was also enhanced and streamlined. The server API that is used by
Andreas and Jörg in their videos has not changed.
* fix: automatic optimization
Allow optimization to automatically run on configured intervals gathering all
optimization parameters from configuration and predictions. The automatic run
can be configured to only run prediction updates skipping the optimization.
Extend documentaion to also cover automatic optimization. Lock automatic runs
against runs initiated by the /optimize or other endpoints. Provide new
endpoints to retrieve the energy management plan and the genetic solution
of the latest automatic optimization run. Offload energy management to thread
pool executor to keep the app more responsive during the CPU heavy optimization
run.
* fix: EOS servers recognize environment variables on startup
Force initialisation of EOS configuration on server startup to assure
all sources of EOS configuration are properly set up and read. Adapt
server tests and configuration tests to also test for environment
variable configuration.
* fix: Remove 0.0.0.0 to localhost translation under Windows
EOS imposed a 0.0.0.0 to localhost translation under Windows for
convenience. This caused some trouble in user configurations. Now, as the
default IP address configuration is 127.0.0.1, the user is responsible
for to set up the correct Windows compliant IP address.
* fix: allow names for hosts additional to IP addresses
* fix: access pydantic model fields by class
Access by instance is deprecated.
* fix: down sampling key_to_array
* fix: make cache clear endpoint clear all cache files
Make /v1/admin/cache/clear clear all cache files. Before it only cleared
expired cache files by default. Add new endpoint /v1/admin/clear-expired
to only clear expired cache files.
* fix: timezonefinder returns Europe/Paris instead of Europe/Berlin
timezonefinder 8.10 got more inaccurate for timezones in europe as there is
a common timezone. Use new package tzfpy instead which is still returning
Europe/Berlin if you are in Germany. tzfpy also claims to be faster than
timezonefinder.
* fix: provider settings configuration
Provider configuration used to be a union holding the settings for several
providers. Pydantic union handling does not always find the correct type
for a provider setting. This led to exceptions in specific configurations.
Now provider settings are explicit comfiguration items for each possible
provider. This is a breaking change as the configuration structure was
changed.
* fix: ClearOutside weather prediction irradiance calculation
Pvlib needs a pandas time index. Convert time index.
* fix: test config file priority
Do not use config_eos fixture as this fixture already creates a config file.
* fix: optimization sample request documentation
Provide all data in documentation of optimization sample request.
* fix: gitlint blocking pip dependency resolution
Replace gitlint by commitizen. Gitlint is not actively maintained anymore.
Gitlint dependencies blocked pip from dependency resolution.
* fix: sync pre-commit config to actual dependency requirements
.pre-commit-config.yaml was out of sync, also requirements-dev.txt.
* fix: missing babel in requirements.txt
Add babel to requirements.txt
* feat: setup default device configuration for automatic optimization
In case the parameters for automatic optimization are not fully defined a
default configuration is setup to allow the automatic energy management
run. The default configuration may help the user to correctly define
the device configuration.
* feat: allow configuration of genetic algorithm parameters
The genetic algorithm parameters for number of individuals, number of
generations, the seed and penalty function parameters are now avaliable
as configuration options.
* feat: allow configuration of home appliance time windows
The time windows a home appliance is allowed to run are now configurable
by the configuration (for /v1 API) and also by the home appliance parameters
(for the classic /optimize API). If there is no such configuration the
time window defaults to optimization hours, which was the standard before
the change. Documentation on how to configure time windows is added.
* feat: standardize mesaurement keys for battery/ ev SoC measurements
The standardized measurement keys to report battery SoC to the device
simulations can now be retrieved from the device configuration as a
read-only config option.
* feat: feed in tariff prediction
Add feed in tarif predictions needed for automatic optimization. The feed in
tariff can be retrieved as fixed feed in tarif or can be imported. Also add
tests for the different feed in tariff providers. Extend documentation to
cover the feed in tariff providers.
* feat: add energy management plan based on S2 standard instructions
EOS can generate an energy management plan as a list of simple instructions.
May be retrieved by the /v1/energy-management/plan endpoint. The instructions
loosely follow the S2 energy management standard.
* feat: make measurement keys configurable by EOS configuration.
The fixed measurement keys are replaced by configurable measurement keys.
* feat: make pendulum DateTime, Date, Duration types usable for pydantic models
Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are
added to the datetimeutil utility. Remove custom made pendulum adaptations
from EOS pydantic module. Make EOS modules use the pydantic pendulum types
managed by the datetimeutil module instead of the core pendulum types.
* feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil.
The time windows are are added to support home appliance time window
configuration. All time classes are also pydantic models. Time is the base
class for time definition derived from pendulum.Time.
* feat: Extend DataRecord by configurable field like data.
Configurable field like data was added to support the configuration of
measurement records.
* feat: Add additional information to health information
Version information is added to the health endpoints of eos and eosDash.
The start time of the last optimization and the latest run time of the energy
management is added to the EOS health information.
* feat: add pydantic merge model tests
* feat: add plan tab to EOSdash
The plan tab displays the current energy management instructions.
* feat: add predictions tab to EOSdash
The predictions tab displays the current predictions.
* feat: add cache management to EOSdash admin tab
The admin tab is extended by a section for cache management. It allows to
clear the cache.
* feat: add about tab to EOSdash
The about tab resembles the former hello tab and provides extra information.
* feat: Adapt changelog and prepare for release management
Release management using commitizen is added. The changelog file is adapted and
teh changelog and a description for release management is added in the
documentation.
* feat(doc): Improve install and devlopment documentation
Provide a more concise installation description in Readme.md and add extra
installation page and development page to documentation.
* chore: Use memory cache for interpolation instead of dict in inverter
Decorate calculate_self_consumption() with @cachemethod_until_update to cache
results in memory during an energy management/ optimization run. Replacement
of dict type caching in inverter is now possible because all optimization
runs are properly locked and the memory cache CacheUntilUpdateStore is properly
cleared at the start of any energy management/ optimization operation.
* chore: refactor genetic
Refactor the genetic algorithm modules for enhanced module structure and better
readability. Removed unnecessary and overcomplex devices singleton. Also
split devices configuration from genetic algorithm parameters to allow further
development independently from genetic algorithm parameter format. Move
charge rates configuration for electric vehicles from optimization to devices
configuration to allow to have different charge rates for different cars in
the future.
* chore: Rename memory cache to CacheEnergyManagementStore
The name better resembles the task of the cache to chache function and method
results for an energy management run. Also the decorator functions are renamed
accordingly: cachemethod_energy_management, cache_energy_management
* chore: use class properties for config/ems/prediction mixin classes
* chore: skip debug logs from mathplotlib
Mathplotlib is very noisy in debug mode.
* chore: automatically sync bokeh js to bokeh python package
bokeh was updated to 3.8.0, make JS CDN automatically follow the package version.
* chore: rename hello.py to about.py
Make hello.py the adapted EOSdash about page.
* chore: remove demo page from EOSdash
As no the plan and prediction pages are working without configuration, the demo
page is no longer necessary
* chore: split test_server.py for system test
Split test_server.py to create explicit test_system.py for system tests.
* chore: move doc utils to generate_config_md.py
The doc utils are only used in scripts/generate_config_md.py. Move it there to
attribute for strong cohesion.
* chore: improve pydantic merge model documentation
* chore: remove pendulum warning from readme
* chore: remove GitHub discussions from contributing documentation
Github discussions is to be replaced by Akkudoktor.net.
* chore(release): bump version to 0.1.0+dev for development
* build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1
bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break.
* build(deps): bump uvicorn from 0.36.0 to 0.37.0
BREAKING CHANGE: EOS configuration changed. V1 API changed.
- The available_charge_rates_percent configuration is removed from optimization.
Use the new charge_rate configuration for the electric vehicle
- Optimization configuration parameter hours renamed to horizon_hours
- Device configuration now has to provide the number of devices and device
properties per device.
- Specific prediction provider configuration to be provided by explicit
configuration item (no union for all providers).
- Measurement keys to be provided as a list.
- New feed in tariff providers have to be configured.
- /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints.
- /v1/admin/cache/clear now clears all cache files. Use
/v1/admin/cache/clear-expired to only clear all expired cache files.
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
* Fix logging configuration issues that made logging stop operation. Switch to Loguru
logging (from Python logging). Enable console and file logging with different log levels.
Add logging documentation.
* Fix logging configuration and EOS configuration out of sync. Added tracking support
for nested value updates of Pydantic models. This used to update the logging configuration
when the EOS configurationm for logging is changed. Should keep logging config and EOS
config in sync as long as all changes to the EOS logging configuration are done by
set_nested_value(), which is the case for the REST API.
* Fix energy management task looping endlessly after the second update when trying to update
the last_update datetime.
* Fix get_nested_value() to correctly take values from the dicts in a Pydantic model instance.
* Fix usage of model classes instead of model instances in nested value access when evaluation
the value type that is associated to each key.
* Fix illegal json format in prediction documentation for PVForecastAkkudoktor provider.
* Fix documentation qirks and add EOS Connect to integrations.
* Support deprecated fields in configuration in documentation generation and EOSdash.
* Enhance EOSdash demo to show BrightSky humidity data (that is often missing)
* Update documentation reference to German EOS installation videos.
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
* Pre-fetch data
* maintanance and extend tests
* comment clean up
* nansum usage (to be save)
* Feature/config nested (#421)
* Nested config, devices registry
* All config now nested.
- Use default config from model field default values. If providers
should be enabled by default, non-empty default config file could
be provided again.
- Environment variable support with EOS_ prefix and __ between levels,
e.g. EOS_SERVER__EOS_SERVER_PORT=8503 where all values are case
insensitive.
For more information see:
https://docs.pydantic.dev/latest/concepts/pydantic_settings/#parsing-environment-variable-values
- Use devices as registry for configured devices. DeviceBase as base
class with for now just initializion support (in the future expand
to operations during optimization).
- Strip down ConfigEOS to the only configuration instance. Reload
from file or reset to defaults is possible.
* Fix multi-initialization of derived SingletonMixin classes.
* Documentation: Support nested config
* Add examples to pydantic models.
* EOSdash: Support nested types
* Rename settings variables (remove prefixes)
* Fix API endpoint
* Fix EOSdash startup (docker)
* Docker: Copy the same directory structure (src/) to support the
lifespan startup of EOSdash.
Use EOS_SERVER_EOSDASH_SESSKEY environment variable to provide
EOSdash with session key.
* PR review
* PVForecast: planes as nested config (list)
* Update manual documentation for nested config.
* Add config_file_path, config_folder_path back to general
(ConfigCommonSettings). Overwrite in docs generation.
* Config: Move lat/long/timezone from prediction to general
* Docs: Add global example documentation.
* merge_models: Use deecopy to not change input data.
* EOSdash: Sort config by name
* Review comments
* Feature/config nested dependabot req. (#415)
* Bump numpydantic from 1.6.4 to 1.6.7 (#413)
Bumps [numpydantic](https://github.com/p2p-ld/numpydantic) from 1.6.4 to 1.6.7.
- [Release notes](https://github.com/p2p-ld/numpydantic/releases)
- [Changelog](https://github.com/p2p-ld/numpydantic/blob/main/docs/changelog.md)
- [Commits](https://github.com/p2p-ld/numpydantic/compare/v1.6.4...v1.6.7)
---
updated-dependencies:
- dependency-name: numpydantic
dependency-type: direct:production
update-type: version-update:semver-patch
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* Bump timezonefinder from 6.5.7 to 6.5.8 (#414)
Bumps [timezonefinder](https://github.com/jannikmi/timezonefinder) from 6.5.7 to 6.5.8.
- [Release notes](https://github.com/jannikmi/timezonefinder/releases)
- [Changelog](https://github.com/jannikmi/timezonefinder/blob/master/CHANGELOG.rst)
- [Commits](https://github.com/jannikmi/timezonefinder/compare/6.5.7...6.5.8)
---
updated-dependencies:
- dependency-name: timezonefinder
dependency-type: direct:production
update-type: version-update:semver-patch
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* Bump pydantic from 2.10.5 to 2.10.6 (#412)
Bumps [pydantic](https://github.com/pydantic/pydantic) from 2.10.5 to 2.10.6.
- [Release notes](https://github.com/pydantic/pydantic/releases)
- [Changelog](https://github.com/pydantic/pydantic/blob/main/HISTORY.md)
- [Commits](https://github.com/pydantic/pydantic/compare/v2.10.5...v2.10.6)
---
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- dependency-name: pydantic
dependency-type: direct:production
update-type: version-update:semver-patch
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* Bump fastapi[standard] from 0.115.6 to 0.115.7 (#411)
Bumps [fastapi[standard]](https://github.com/fastapi/fastapi) from 0.115.6 to 0.115.7.
- [Release notes](https://github.com/fastapi/fastapi/releases)
- [Commits](https://github.com/fastapi/fastapi/compare/0.115.6...0.115.7)
---
updated-dependencies:
- dependency-name: fastapi[standard]
dependency-type: direct:production
update-type: version-update:semver-patch
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* Readme: Add hint for interfering ports on Synology Closes#408 (#419)
* Pics or it didn't happen (#402)
* inverter added
* png creation
* save svg into cache folder
* mypy
* comment
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* inverter, prediction.hours
* self.config.general.data_cache_path
---------
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* All config now nested.
- Use default config from model field default values. If providers
should be enabled by default, non-empty default config file could
be provided again.
- Environment variable support with EOS_ prefix and __ between levels,
e.g. EOS_SERVER__EOS_SERVER_PORT=8503 where all values are case
insensitive.
For more information see:
https://docs.pydantic.dev/latest/concepts/pydantic_settings/#parsing-environment-variable-values
- Use devices as registry for configured devices. DeviceBase as base
class with for now just initializion support (in the future expand
to operations during optimization).
- Strip down ConfigEOS to the only configuration instance. Reload
from file or reset to defaults is possible.
* Fix multi-initialization of derived SingletonMixin classes.
* Cleanup: parameters: extra=forbid, optimize: battery, inverter optional
* Don't allow extra fields for parameters/REST-API (at least for now while
changing API).
* Allow both battery and inverter to be set optionally (atm optional
battery not implemented, no API constraints).
* inverter: Remove default max_power_wh
* single_test_optimization: Add more cli-parameters
* Workflow docker-build: Don't try to authenticate for PRs
* Secrets are not available anyway for forks.
Normalize electricity price prediction to €/Wh.
Provide electricity price prediction by €/kWh for convenience.
Allow to configure electricity price charges by €/kWh.
Also added error page to fastapi rest server to get rid of annoying
unrelated fault messages during testing.
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
Extend single_test_optimization.py to be able to use real world data from new prediction classes.
- .venv/bin/python single_test_optimization.py --real_world --verbose
Can also be run with profiling "--profile".
Add single_test_prediction.py to fetch predictions from remote prediction providers
- .venv/bin/python single_test_prediction.py --verbose --provider-id PVForecastAkkudoktor | more
- .venv/bin/python single_test_prediction.py --verbose --provider-id LoadAkkudoktor | more
- .venv/bin/python single_test_prediction.py --verbose --provider-id ElecPriceAkkudoktor | more
- .venv/bin/python single_test_prediction.py --verbose --provider-id BrightSky | more
- .venv/bin/python single_test_prediction.py --verbose --provider-id ClearOutside | more
Can also be run with profiling "--profile".
single_test_optimization.py is an example on how to retrieve prediction data for optimization and
use it to set up the optimization parameters.
Changes:
- load: Only one load provider at a time (vs. 5 before)
Bug fixes:
- prediction: only use providers that are enabled to retrieve or set data.
- prediction: fix pre pendulum format strings
- dataabc: Prevent error when resampling data with no datasets.
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
* Update utilities in utils submodule.
* Add base configuration modules.
* Add server base configuration modules.
* Add devices base configuration modules.
* Add optimization base configuration modules.
* Add utils base configuration modules.
* Add prediction abstract and base classes plus tests.
* Add PV forecast to prediction submodule.
The PV forecast modules are adapted from the class_pvforecast module and
replace it.
* Add weather forecast to prediction submodule.
The modules provide classes and methods to retrieve, manage, and process weather forecast data
from various sources. Includes are structured representations of weather data and utilities
for fetching forecasts for specific locations and time ranges.
BrightSky and ClearOutside are currently supported.
* Add electricity price forecast to prediction submodule.
* Adapt fastapi server to base config and add fasthtml server.
* Add ems to core submodule.
* Adapt genetic to config.
* Adapt visualize to config.
* Adapt common test fixtures to config.
* Add load forecast to prediction submodule.
* Add core abstract and base classes.
* Adapt single test optimization to config.
* Adapt devices to config.
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
* Mypy: Initial support
* Add to pre-commit (currently installs own deps, could maybe changed
to poetry venv in the future to reuse environment and don't need
duplicated types deps).
* Add type hints.
* Mypy: Add missing annotations
* Migrate from Flask to FastAPI
* FastAPI migration:
- Use pydantic model classes as input parameters to the
data/calculation classes.
- Interface field names changed to constructor parameter names (for
simplicity only during transition, should be updated in a followup
PR).
- Add basic interface requirements (e.g. some values > 0, etc.).
* Update tests for new data format.
* Python requirement down to 3.9 (TypeGuard no longer needed)
* Makefile: Add helpful targets (e.g. development server with reload)
* Move API doc from README to pydantic model classes (swagger)
* Link to swagger.io with own openapi.yml.
* Commit openapi.json and check with pytest for changes so the
documentation is always up-to-date.
* Streamline docker
* FastAPI: Run startup action on dev server
* Fix config for /strompreis, endpoint still broken however.
* test_openapi: Compare against docs/.../openapi.json
* Move fastapi to server/ submodule
* See #187 for new repository structure.
class_optimize: Timing Bugs fixed
class_numpy_encoder: JSON Encoder with Numpy support
visualize: AC / DC / Discharge
test_class_ems_2: New Test for AC / DC charging decision
