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My Energy Optimization with IoT-Ticket 2/3

This is a blog series about optimizing my energy consumption with IoT-TICKET®. Basically I am controlling the energy load of my house as optimal as possible taking electricity price, own solar energy production and weather conditions into consideration. This series will include posts about how the idea developed and how it was implemented technically. There will be several posts about this topic. See the first post from here.

Charge the car v2.0

Back to this car I purchased and what triggered me to this project. The car comes with the own travel charging station and by connecting it to 16A 3 phase plug it charges the battery full (7 kW) within 2.5 hours. However, this is a travel charging solution and when considering electrical vehicle (hereafter EV) you should plan a permanent wall charging station to your home. You can purchase it from many places, but remember that electrician have to install it.

My style of doing things is first to find out how things work and after that to find the best solution for my needs. This time my solution was to build a wall charger by using Phoenix Contact charging technology for electromobility. The reason for this was price, programmability and connectivity.

In summer vacation 2017 I used two days to make this happen. I created charging station and connected it to IoT-Ticket. I have two operation modes; manual charging and energy save charging. Manual charging loads with full power and it works with any car with type 2 charging cable. Energy save mode has a day and a night modes, which also works with any type 2 compatible EVs.

In a day mode, when the sun is still shining, the situation is normally like this:

Figure 1. Sun energy is sold to energy utility.

The situation above is not good and the best solution is to use all the solar energy at home, not to sell it. In my situation, the optimal solution is just to plug car into charging socket and charge the car with the optimal power. Optimal power means that the system takes solar production and other house energy consumption into account and that the energy selling is minimized.

Figure 2. Car charging with 5000 W and 1000 W is used in house. Energy comes from the sun.

This happens only in daytime and when the sun is shining. In case energy consumption of the house increases, then car charging will be reduced. Control algorithm is the following (solar is 6 kWp and car can charge max 2x16A):

If energy production to grid is (20 minute average):

  • > 1500 W -> start charging 6 A / 2.7 kW
  • > 4000 W -> start charging 10 A / 4.4 kW
  • > 5000 W -> start charging 13 A / 5.7 kW
  • < 1500 W -> stop charging 

Above is a day mode and always the battery cannot be charged full. In a night time the energy save mode finds out the cheapest charge window and continues to charge battery full:

Figure 3. Energy save mode: car charging at night.

Next steps

My system has a weather forecast and electricity spot prices. I have also connected other energy loads of the house to the system, including floor heating with 6 kW/10 kW/16 kW and warm water heating. The electricity price based control of the house and water heating is identical to car charge night mode (see the previous post), but there are more variables to take into account:

  • Outside temperature
  • How people living in the house are feeling?
  • Next day weather forecast
  • Cold, windy -> means more heating need
  • UV index -> means solar energy availability

The electricity spot prices are delivered daily at 14:00 for the next 24 hours. At 14:30 I calculate how the energy loads should be turned on timewise.

Figure 4. Nordspool electricity prices in IoT-Ticket.

In order to implement a floor heating I need colder weather, so this must wait a couple of months to implement and test it.

On next blog posts I'll go to technical details how I have made some energy optimization to my home.


IoT-Ticket IoT WRM247+ energy optimization solar power hybrid car

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Teemu Niemi

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