InverterChargeController

This project aims to charge the battery pack of a photovoltaic system when the energy rates are as low as possible.

Usage

Setup

1. Create a virtual environment

   python -m venv .venv

2. Activate the virtual environment

   source .venv/bin/activate

3. Install the requirements

   poetry install

4. Create an .env and fill in your values

   vi .env

   Variable Name	Description	Default Value	Possible Values
   ERROR_MAIL_ADDRESS	The mail address to send error logs to in error_mailer.sh. Only necessary if script is used.	-	A string containing an email address, example [email protected]
   USE_DEBUG_SOLAR_OUTPUT	Use a debug value for the expected solar output (can be used while debugging since the solar forecast API offers a very limited amount of API calls per day). Should be set to False in normal production mode.	False	[True, False]
   LOGLEVEL	The level to log at.	INFO	[TRACE, DEBUG, INFO, WARNING, ERROR, CRITICAL]
   DIRECTORY_OF_LOGS	The directory where the logs of the application shall be stored. Ensure the user running the application has permissions to write in this directory.	<path to repository>/logs/	A string containing an absolute path, example: /var/log/inverterchargecontroller/
   PRINT_TO_STDOUT	Whether to print to stdout in addition to the logfile.	True	[True, False]
   TIBBER_API_TOKEN	The token to crawl the Tibber API. See https://developer.tibber.com/docs/guides/calling-api for more information.	-	A string, example: my-secret-token
   INVERTER_HOSTNAME	The hostname or IP of the inverter.	-	[inverter.mydomain.com, 192.168.5.10, ...]
   INVERTER_BATTERY_CAPACITY	The capacity of the battery in watt hours without any separators.	-	A number, typically between 3000 and 15000
   INVERTER_TARGET_MIN_STATE_OF_CHARGE	The state of charge the battery shall have when reaching the next minimum as a buffer.	15	A number between 0 and 100, typically between 0 and 40
   INVERTER_TARGET_MAX_STATE_OF_CHARGE	The maximum state of charge the inverter will charge to since the last few percent take a long time to charge.	95	A number between 0 and 100, typically between 80 and 100
   SEMSPORTAL_USERNAME	The username to login into the SEMSPortal.	-	A string, example: [email protected]
   SEMSPORTAL_PASSWORD	The password to login into the SEMSPortal.	-	A string, example: my-secret-password
   SEMSPORTAL_POWERSTATION_ID	The ID of the inverter in the SEMSPortal. This can be found at the end of the URL in the browser after logging in.	-	A string, example: aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee
   SOLCAST_API_KEY	The API-Key of https://www.solcast.com/	-	A string, example: my-secret-token
   ROOFTOP_ID_1	The ID of the rooftop in solcast.	-	A string, example: aaaa-bbbb-cccc-dddd
   ROOFTOP_ID_2	The ID of the second rooftop in solcast. This can be used if you have solar panels on both sides of your roof or a small balcony power plant, can be omitted if unused.	-	A string, example: aaaa-bbbb-cccc-dddd
   LONGITUDE	The longitude of your home.	-	A string, example: 39.02861632833333
   LATITUDE	The latitude of your home.	-	A string, example: 125.75958167791751
   ABSENCE_TIMEFRAME	This variable CAN be set in order to set a timeframe for an absence. During the absence the value of ABSENCE_POWER_CONSUMPTION is used to determine the power consumption (not the average of the last week). The timestamps have to be in ISO8601 format and contain a timezone.	-	A string in the format <START_OF_ABSENCE>;<START_OF_ABSENCE>. Example: 2024-11-03T00:00:00+0100;2024-11-10T11:00:00+0100
   ABSENCE_POWER_CONSUMPTION	The power consumption to use during the absence (instead of lass week's average)	150	A number, typically between 0 and 250.

   All the environment variables are read in every time they are used. As a consequence, the program does not have to be restarted when they are altered. If a .env.override exists values of the .env are overwritten.

Running

Manually

You can run the program manually

python3 source/main.py

Systemd

or you can install the program as a systemd service.

Before installing the systemd service, you can optionally choose to create a user whose sole purpose is to run this application. This is not necessary at all but considered best practice. If you choose to run the application as your own user, skip this step.

sudo su
useradd -r -s /usr/sbin/nologin -m <username>
cd /home/<username>
git clone https://github.com/felixschndr/InverterChargeController.git app/
cd app/
python -m venv .venv
source .venv/bin/activate
poetry install
vi .env
chown -R <username>: app/

After that, you can create the systemd configuration:

vi systemd/inverter-charge-controller.service
sudo ln -s <path to repository>/systemd/inverter-charge-controller.service /etc/systemd/system
sudo systemctl daemon-reload

Once done, you can control the program like any other systemd service:

• Status: sudo systemctl status inverter-charge-controller.service
• Starting: sudo systemctl start inverter-charge-controller.service
• Stopping: sudo systemctl stop inverter-charge-controller.service
• Restarting: sudo systemctl restart inverter-charge-controller.service
• Enabling to run at boot: sudo systemctl enable inverter-charge-controller.service

Extra script

You can use the inverter script to control the inverter manually over the command line. It supports getting the current state of charge and operation mode and setting the operation mode.

Logs

The logs of the application are stored in <path to repository>/logs/. They are rolled over once a logfile reaches 1 MB in size. The current log and a maximum of 7 rolled over logfiles are saved. See also the environment variables DIRECTORY_OF_LOGS and LOGLEVEL.

Charging algorithm

InfluxDB commands

• Create bucket: influx bucket create -org default -token ${INFLUXDB_TOKEN} --name default
• Delete bucket: influx bucket delete -org default -token ${INFLUXDB_TOKEN} --name default
• Retrieve all solar forecast values:

  influx query -org default -token ${INFLUXDB_TOKEN} \
  '
  import "experimental"
  from(bucket: "default")
    |> range(start: 0, stop: experimental.addDuration(d: 2d, to: now()))
    |> filter(fn: (r) => r._measurement == "solar_forecast")
    |> pivot(rowKey:["_time"], columnKey:["_field"], valueColumn:"_value")
  '
  

• Retrieve all energy prices:

  influx query -org default -token ${INFLUXDB_TOKEN} \
  '
  import "experimental"
  from(bucket: "default")
    |> range(start: 0, stop: experimental.addDuration(d: 2d, to: now()))
    |> filter(fn: (r) => r._measurement == "energy_prices")
    |> pivot(rowKey:["_time"], columnKey:["_field"], valueColumn:"_value")
  '
  

• Retrieve all power data (semsportal):

  influx query -org default -token ${INFLUXDB_TOKEN} \
  '
  from(bucket: "default")
    |> range(start: 0, stop: now())
    |> filter(fn: (r) => r._measurement == "power")
    |> pivot(rowKey:["_time"], columnKey:["_field"], valueColumn:"_value")
  '
  

• Retrieve all power buy data:

  influx query -org default -token ${INFLUXDB_TOKEN} \
  '
  from(bucket: "default")
    |> range(start: 0, stop: now())
    |> filter(fn: (r) => r._measurement == "power_buy")
    |> pivot(rowKey:["_time"], columnKey:["_field"], valueColumn:"_value")
  '
  

• Rename a field within the same measurement:

  influx query -org default -token ${INFLUXDB_TOKEN} \
  '
  import "experimental"
  from(bucket: "default")
    |> range(start: 0, stop: experimental.addDuration(d: 2d, to: now()))
    |> filter(fn: (r) => r._measurement == "power")
    |> map(fn: (r) => ({
      _time: r._time,
      _value: if exists r.<old_field_name> then r.<old_field_name> else r._value,
      <new_field_name>: r.<old_field_name>,
      _field: "<new_field_name>"
    }))
    |> drop(columns: ["<old_field_name>"])
    |> to(bucket: "default", org: "default")
  '
  

• Copy values of _time into a new field within the same measurement:

  influx query -org default -token ${INFLUXDB_TOKEN} \
  '
  import "experimental"
  from(bucket: "default")
    |> range(start: 0, stop: experimental.addDuration(d: 2d, to: now()))
    |> filter(fn: (r) => r._measurement == "<measurement_to_copy>")
    |> map(fn: (r) => ({ _time: r._time, _value: r._value, <new_field_name>: r._time }))
    |> to(bucket: "default", org: "default")
  '
  

• Copy data from one measurement to another:

  influx query -org default -token ${INFLUXDB_TOKEN} \
  '
  import "experimental"
  from(bucket: "default")
    |> range(start: 0, stop: experimental.addDuration(d: 2d, to: now()))
    |> filter(fn: (r) => r._measurement == "<old_measurement>")
    |> set(key: "_measurement", value: "<new_measurement>")
    |> to(bucket: "default")
  '
  

• Delete data from one measurement:

  influx delete --bucket default -org default -token ${INFLUXDB_TOKEN} \
  --start='1970-01-01T00:00:00Z' --stop=$(date +"%Y-%m-%dT%H:%M:%SZ" -d "+2 days") \
  --predicate '_measurement=<old_measurement>'