d2ba0adb5f
* Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
Energy System Simulation and Optimization
This project provides a comprehensive solution for simulating and optimizing an energy system based on renewable energy sources. With a focus on photovoltaic (PV) systems, battery storage (batteries), load management (consumer requirements), heat pumps, electric vehicles, and consideration of electricity price data, this system enables forecasting and optimization of energy flow and costs over a specified period.
Getting Involved
See CONTRIBUTING.md.
Installation
Good installation guide: https://meintechblog.de/2024/09/05/andreas-schmitz-joerg-installiert-mein-energieoptimierungssystem/
The project requires Python 3.10 or newer.
Quick Start Guide
On Linux (Ubuntu/Debian):
sudo apt install make
On MacOS (requires Homebrew):
brew install make
Next, adjust config.py.
The server can then be started with make run. A full overview of the main shortcuts is given by make help.
Detailed Instructions
All necessary dependencies can be installed via pip. Clone the repository and install the required packages with:
git clone https://github.com/Akkudoktor-EOS/EOS
cd EOS
Next, create a virtual environment. This serves to store the Python dependencies, which we will install later using pip:
virtualenv .venv
Finally, install the Python dependencies for EOS:
.venv/bin/pip install -r requirements.txt
To always use the Python version from the virtual environment, you should activate it before working in EOS:
source .venv/bin/activate
(for Bash users, the default under Linux) or
. .venv/bin/activate
Usage
Adjust config.py.
To use the system, run flask_server.py, which starts the server:
./flask_server.py
Classes and Functionalities
This project uses various classes to simulate and optimize the components of an energy system. Each class represents a specific aspect of the system, as described below:
-
PVAkku: Simulates a battery storage system, including capacity, state of charge, and now charge and discharge losses. -
PVForecast: Provides forecast data for photovoltaic generation, based on weather data and historical generation data. -
Load: Models the load requirements of a household or business, enabling the prediction of future energy demand. -
Heatpump: Simulates a heat pump, including its energy consumption and efficiency under various operating conditions. -
Strompreis: Provides information on electricity prices, enabling optimization of energy consumption and generation based on tariff information. -
EMS: The Energy Management System (EMS) coordinates the interaction between the various components, performs optimization, and simulates the operation of the entire energy system.
These classes work together to enable a detailed simulation and optimization of the energy system. For each class, specific parameters and settings can be adjusted to test different scenarios and strategies.
Customization and Extension
Each class is designed to be easily customized and extended to integrate additional functions or improvements. For example, new methods can be added for more accurate modeling of PV system or battery behavior. Developers are invited to modify and extend the system according to their needs.
Input for the Flask Server (as of 30.07.2024)
Describes the structure and data types of the JSON object sent to the Flask server, with a forecast period of 48 hours.
JSON Object Fields
strompreis_euro_pro_wh
- Description: An array of floats representing the electricity price in euros per watt-hour for different time intervals.
- Type: Array
- Element Type: Float
- Length: 48
gesamtlast
- Description: An array of floats representing the total load (consumption) in watts for different time intervals.
- Type: Array
- Element Type: Float
- Length: 48
pv_forecast
- Description: An array of floats representing the forecasted photovoltaic output in watts for different time intervals.
- Type: Array
- Element Type: Float
- Length: 48
temperature_forecast
- Description: An array of floats representing the temperature forecast in degrees Celsius for different time intervals.
- Type: Array
- Element Type: Float
- Length: 48
pv_soc
- Description: An integer representing the state of charge of the PV battery at the start of the current hour (not the current state).
- Type: Integer
pv_akku_cap
- Description: An integer representing the capacity of the photovoltaic battery in watt-hours.
- Type: Integer
einspeiseverguetung_euro_pro_wh
- Description: A float representing the feed-in compensation in euros per watt-hour.
- Type: Float
eauto_min_soc
- Description: An integer representing the minimum state of charge (SOC) of the electric vehicle in percentage.
- Type: Integer
eauto_cap
- Description: An integer representing the capacity of the electric vehicle battery in watt-hours.
- Type: Integer
eauto_charge_efficiency
- Description: A float representing the charging efficiency of the electric vehicle.
- Type: Float
eauto_charge_power
- Description: An integer representing the charging power of the electric vehicle in watts.
- Type: Integer
eauto_soc
- Description: An integer representing the current state of charge (SOC) of the electric vehicle in percentage.
- Type: Integer
start_solution
- Description: Can be
nullor contain a previous solution (if available). - Type:
nullor object
haushaltsgeraet_wh
- Description: An integer representing the energy consumption of a household device in watt-hours.
- Type: Integer
haushaltsgeraet_dauer
- Description: An integer representing the usage duration of a household device in hours.
- Type: Integer
JSON Output Description
This document describes the structure and data types of the JSON output returned by the Flask server, with a forecast period of 48 hours.
Note: The first value of "Last_Wh_pro_Stunde", "Netzeinspeisung_Wh_pro_Stunde" and "Netzbezug_Wh_pro_Stunde", will be set to null in the JSON output and represented as NaN or None in the corresponding classes' data returns. This approach is adopted to ensure that the current hour's processing remains unchanged.
JSON Output Fields (as of 30.7.2024)
discharge_hours_bin
An array that indicates for each hour of the forecast period (in this example, 48 hours) whether energy is discharged from the battery or not. The values are either 0 (no discharge) or 1 (discharge).
eauto_obj
This object contains information related to the electric vehicle and its charging and discharging behavior:
- charge_array: Indicates for each hour whether the EV is charging (
0for no charging,1for charging).- Type: Array
- Element Type: Integer (0 or 1)
- Length: 48
- discharge_array: Indicates for each hour whether the EV is discharging (
0for no discharging,1for discharging).- Type: Array
- Element Type: Integer (0 or 1)
- Length: 48
- entlade_effizienz: The discharge efficiency as a float.
- Type: Float
- hours: Amount of hours the simulation is done for.
- Type: Integer
- kapazitaet_wh: The capacity of the EV’s battery in watt-hours.
- Type: Integer
- lade_effizienz: The charging efficiency as a float.
- Type: Float
- max_ladeleistung_w: The maximum charging power of the EV in watts.
- Type: Float
- max_ladeleistung_w: Max charging power of the EV in Watts.
- Type: Integer
- soc_wh: The state of charge of the battery in watt-hours at the start of the simulation.
- Type: Integer
- start_soc_prozent: The state of charge of the battery in percentage at the start of the simulation.
- Type: Integer
eautocharge_hours_float
An array of binary values (0 or 1) that indicates whether the EV will be charged in a certain hour.
- Type: Array
- Element Type: Integer (0 or 1)
- Length: 48
result
This object contains the results of the simulation and provides insights into various parameters over the entire forecast period:
- E-Auto_SoC_pro_Stunde: The state of charge of the EV for each hour.
- Type: Array
- Element Type: Float
- Length: 35
- Eigenverbrauch_Wh_pro_Stunde: The self-consumption of the system in watt-hours per hour.
- Type: Array
- Element Type: Float
- Length: 35
- Einnahmen_Euro_pro_Stunde: The revenue from grid feed-in or other sources in euros per hour.
- Type: Array
- Element Type: Float
- Length: 35
- Gesamt_Verluste: The total losses in watt-hours over the entire period.
- Type: Float
- Gesamtbilanz_Euro: The total balance of revenues minus costs in euros.
- Type: Float
- Gesamteinnahmen_Euro: The total revenues in euros.
- Type: Float
- Gesamtkosten_Euro: The total costs in euros.
- Type: Float
- Haushaltsgeraet_wh_pro_stunde: The energy consumption of a household appliance in watt-hours per hour.
- Type: Array
- Element Type: Float
- Length: 35
- Kosten_Euro_pro_Stunde: The costs in euros per hour.
- Type: Array
- Element Type: Float
- Length: 35
- Netzbezug_Wh_pro_Stunde: The grid energy drawn in watt-hours per hour.
- Type: Array
- Element Type: Float
- Length: 35
- Netzeinspeisung_Wh_pro_Stunde: The energy fed into the grid in watt-hours per hour.
- Type: Array
- Element Type: Float
- Length: 35
- Verluste_Pro_Stunde: The losses in watt-hours per hour.
- Type: Array
- Element Type: Float
- Length: 35
- akku_soc_pro_stunde: The state of charge of the battery (not the EV) in percentage per hour.
- Type: Array
- Element Type: Float
- Length: 35
simulation_data
An object containing the simulated data.
- E-Auto_SoC_pro_Stunde: An array of floats representing the simulated state of charge of the electric car per hour.
- Type: Array
- Element Type: Float
- Length: 35
- Eigenverbrauch_Wh_pro_Stunde: An array of floats representing the simulated self-consumption in watt-hours per hour.
- Type: Array
- Element Type: Float
- Length: 35
- Einnahmen_Euro_pro_Stunde: An array of floats representing the simulated income in euros per hour.
- Type: Array
- Element Type: Float
- Length: 35
- Gesamt_Verluste: The total simulated losses in watt-hours.
- Type: Float
- Gesamtbilanz_Euro: The total simulated balance in euros.
- Type: Float
- Gesamteinnahmen_Euro: The total simulated income in euros.
- Type: Float
- Gesamtkosten_Euro: The total simulated costs in euros.
- Type: Float
- Haushaltsgeraet_wh_pro_stunde: An array of floats representing the simulated energy consumption of a household appliance in watt-hours per hour.
- Type: Array
- Element Type: Float
- Length: 35
- Kosten_Euro_pro_Stunde: An array of floats representing the simulated costs in euros per hour.
- Type: Array
- Element Type: Float
- Length: 35
- Netzbezug_Wh_pro_Stunde: An array of floats representing the simulated grid consumption in watt-hours per hour.
- Type: Array
- Element Type: Float
- Length: 35
- Netzeinspeisung_Wh_pro_Stunde: An array of floats representing the simulated grid feed-in in watt-hours per hour.
- Type: Array
- Element Type: Float
- Length: 35
- Verluste_Pro_Stunde: An array of floats representing the simulated losses per hour.
- Type: Array
- Element Type: Float
- Length: 35
- akku_soc_pro_stunde: An array of floats representing the simulated state of charge of the battery in percentage per hour.
- Type: Array
- Element Type: Float
- Length: 35
spuelstart
- Description: Can be
nullor contain an object representing the start of washing (if applicable). - Type: null or object
start_solution
- Description: An array of binary values (0 or 1) representing a possible starting solution for the simulation.
- Type: Array
- Element Type: Integer (0 or 1)
- Length: 48