Changelog

All notable changes to the akkudoktoreos project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

0.2.0 (2025-11-09)

The most important new feature is automatic optimization. EOS can now independently perform optimization at regular intervals. This is based on the configured system parameters and forecasts, and also uses supplied measurement data, such as the current battery SoC. The result is an energy-management plan as well as the optimization output. The existing optimization interface using POST /optimize remains available and can still be used as before.

In addition, bugs were fixed and new features were added:

  • Automatic optimization creates a default configuration if none is provided. This is intended to make it easier to create a custom configuration by adapting the default.

  • The parameters of the genetic optimization algorithm (number of generations, etc.) are now configurable.

  • For home appliances, start windows can now be specified (experimental).

  • Configuration files from previous versions are converted to the current format on first launch.

  • There are now measurement keys that are permanently assigned to a specific device simulation. This simplifies providing measurement values for device simulations (e.g. battery SoC).

  • The infrastructure and first applications for feed-in tariff forecasting (currently only fixed tariffs) are now integrated.

  • EOSdash has been expanded with new tabs for displaying the energy-management plan and predictions.

  • The documentation has been updated and expanded in many places.

Feat

  • Energy-management plan generation based on S2 standard instructions

  • Feed-in-tariff prediction support (incl. tests & docs)

  • LoadAkkudoktorAdjusted load prediction variant

  • Standardized measurement keys for battery/EV SoC

  • Measurement keys configurable via EOS configuration

  • Setup default device configuration for automatic optimization

  • Health endpoints show version + last optimization timestamps

  • Configuration of genetic algorithm parameters

  • Configuration options for home-appliance time windows

  • Mitigation of legacy configuration

  • Config backup enhancements:

    • Timestamp-based backup IDs

    • API to list backups

    • API to revert to a specific backup

    • EOSdash Admin tab integration

  • Pendulum date types via pydantic_extra_types.pendulum_dt

  • Time, TimeWindow, TimeWindowSequence, and to_time helpers in datetimeutil

  • Extended DataRecord with configurable field-like semantics

  • EOSdash: Solution view now displays genetic optimization results and aggregated totals

  • EOSdash UI:

    • Plan tab

    • Predictions tab

    • Cache management in Admin tab

    • About tab

  • Pydantic merge model tests

  • Developer profiling entry in Makefile

  • Changelog & docs updated for commitizen release flow

  • Developer documentation updated

  • Improved install & development documentation

Changed

  • Battery simulation

    • Performance improvements

    • Charge + start times now reflect realistic simulation

  • Appliance simulation:

    • Time windows may roll over to next day

  • Revised load prediction by splitting original LoadAkkudoktor into:

    • LoadAkkudoktor

    • LoadAkkudoktorAdjusted

Fixed

  • Correct URL/path for Akkudoktor forum in README

  • Automatic optimization:

    • Reuses previous start solution

    • Interval execution + locking + new endpoints

    • Properly loads required data

    • EV charge-rate migration for proper availability

  • Genetic common settings consistently available

  • Config markdown generation

  • Recognize environment variables on EOS server startup

  • Remove 0.0.0.0 → localhost translation on Windows

  • Allow hostnames as well as IPs

  • Access Pydantic model fields via class instead of instance

  • Down-sampling in key_to_array

  • /v1/admin/cache/clear clears all cache files; added /clear-expired

  • Use tzfpy instead of timezonefinder for more accurate EU timezones

  • Explicit provider settings in config instead of union

  • ClearOutside weather prediction irradiance calculation

  • Test config file priority without config_eos fixture

  • Complete optimization sample-request documentation

  • Replace gitlint with commitizen

  • Synchronize pre-commit config with real dependencies

  • Add missing babel to requirements

  • Fix documentation, tests, and implementation around optimization + predictions

Chore

  • Use memory cache for inverter interpolation

  • Refactor genetic modules (split config, remove device singleton)

  • Rename memory cache to CacheEnergyManagementStore

  • Use class properties for config/EMS/prediction mixins

  • Skip matplotlib debug logs

  • Auto-sync Bokeh JS CDN version

  • Rename hello.py → about.py in EOSdash

  • Remove EOSdash demo page

  • Split server test from system test

  • Move doc utils to generate_config_md.py

  • Improve documentation for pydantic merge models

  • Remove pendulum warning from README

  • Drop GitHub Discussions from contributing docs

  • Rename or reorganize files / classes during refactors

BREAKING CHANGES

EOS configuration + v1 API have changed:

  • available_charge_rates_percent removed → replaced by charge_rate

  • Optimization parameter hours → renamed to horizon_hours

  • Device config must explicitly list devices + properties

  • Prediction providers now explicit (instead of union)

  • Measurement keys provided as lists

  • Feed-in-tariff providers must be explicitly configured

  • /v1/measurement/loadxxx endpoints removed → use generic measurement endpoints

  • /v1/admin/cache/clear now clears *all- cache files; /v1/admin/cache/clear-expired only clears expired entries

v0.1.0 (2025-09-30)

Feat

  • added Changelog for 0.0.0 and 0.1.0

v0.0.0 (2025-09-30)

This version represents one year of development of EOS (Energy Optimization System). From this point forward, release management will be introduced.

Feat

Core Features

  • energy Management System (EMS) with battery optimization

  • PV (Photovoltaic) forecast integration with multiple providers

  • load prediction and forecasting capabilities

  • electricity price integration

  • VRM API integration for load and PV forecasting

  • battery State of Charge (SoC) prediction and optimization

  • inverter class with AC/DC charging logic

  • electric vehicle (EV) charging optimization with configurable currents

  • home appliance scheduling optimization

  • horizon validation for shading calculations

API & Server

  • migration from Flask to FastAPI

  • RESTful API with comprehensive endpoints

  • EOSdash web interface for configuration and visualization

  • Docker support with multi-architecture builds

  • web-based visualization with interactive charts

  • OpenAPI/Swagger documentation

  • configurable server settings (port, host)

Configuration & Data Management

  • JSON-based configuration system with nested support

  • configuration validation with Pydantic

  • device registry for managing multiple devices

  • persistent caching for predictions and prices

  • manual prediction updates

  • timezone support with automatic detection

  • configurable VAT rates for electricity prices

Optimization

  • DEAP-based genetic algorithm optimization

  • multi-objective optimization (cost, battery usage, self-consumption)

  • 48-hour prediction and optimization window

  • AC/DC charging decision optimization

  • discharge hour optimization

  • start solution enforcement

  • fitness visualization with violin plots

  • self-consumption probability interpolator

Testing & Quality

  • comprehensive test suite with pytest

  • unit tests for major components (EMS, battery, inverter, load, optimization)

  • integration tests for server endpoints

  • pre-commit hooks for code quality

  • type checking with mypy

  • code formatting with ruff and isort

  • markdown linting

Documentation

  • conceptual documentation

  • API documentation with Sphinx

  • ReadTheDocs integration

  • Docker setup instructions

  • contributing guidelines

  • English README translation

Providers & Integrations

  • PVForecast.Akkudoktor provider

  • BrightSky weather provider

  • ClearOutside weather provider

  • electricity price provider

Refactor

  • optimized Inverter class for improved SCR calculation performance

  • improved caching mechanisms for better performance

  • enhanced visualization with proper timestamp handling

  • updated dependency management with automatic Dependabot updates

  • restructured code into logical submodules

  • package directory structure reorganization

  • improved error handling and logging

  • Windows compatibility improvements

Fix

  • cross-site scripting (XSS) vulnerabilities

  • ReDoS vulnerability in duration parsing

  • timezone and daylight saving time handling

  • BrightSky provider with None humidity data

  • negative values in load mean adjusted calculations

  • SoC calculation bugs

  • AC charge efficiency in price calculations

  • optimization timing bugs

  • Docker BuildKit compatibility

  • float value handling in user horizon configuration

  • circular runtime import issues

  • load simulation data return issues

  • multiple optimization-related bugs

Build

  • Python version requirement updated to 3.10+

  • added Bandit security checks

  • improved credential management with environment variables

Dependencies

Major dependencies included in this release:

  • FastAPI 0.115.14

  • Pydantic 2.11.9

  • NumPy 2.3.3

  • Pandas 2.3.2

  • Scikit-learn 1.7.2

  • Uvicorn 0.36.0

  • Bokeh 3.8.0

  • Matplotlib 3.10.6

  • PVLib 0.13.1

  • Python-FastHTML 0.12.29

Notes

Development Notes

This version encompasses all development from the initial commit (February 16, 2024) through September 29, 2025. The project evolved from a basic energy optimization concept to a comprehensive energy management system with:

  • 698+ commits

  • multiple contributor involvement

  • continuous integration/deployment setup

  • automated dependency updates

  • comprehensive testing infrastructure

Migration Notes

As this is the initial versioned release, no migration is required. Future releases will include migration guides as needed.