Electricity prices for today and tomorrow with Nordpool #494
Replies: 5 comments 6 replies
-
|
Thanks for sharing! Let me only suggest using math instead of big ms numbers. It's easier to read if you ever need to tweak it:
|
Beta Was this translation helpful? Give feedback.
-
|
Hi. The data ist correctly transmitted to home assistant. In home assistant the sensor state has the value of hour 00
any chance to manage this or can i change the data to achive this? |
Beta Was this translation helpful? Give feedback.
-
|
Hi, It seems that it should work with your data as well. You just have different variable names, so for example here: ({ meta }) => ({
xs: meta.raw_tomorrow.map(({ start }) => new Date(start)),
ys: meta.raw_tomorrow.map(({ value }, i) => value),
})you should use something like: ({ meta }) => ({
xs: meta.data.map(({ time }) => new Date(time)),
ys: meta.data.map(({ total }, i) => total),
})If you can share your yaml configuration we can perhaps help better. |
Beta Was this translation helpful? Give feedback.
-
|
Hello. Thank you for the reply. I have not found any suitable information in the Plotly Graph Card on GitHub "dbuezas/lovelace-plotly-graph-card". I want to be able to do that too. Unfortunately, my project is somewhat more complex as previously described. I control my Victron inverters via Node-RED. Among other things, I also use the Tibber data from the last few weeks. These processed Tibber data are then combined with the solar forecasts, which then lead to certain automatic control commands. I then prepare the Node-RED data separately for Home Assistant to then transfer them to Home Assistant via an "HTTP in" node. node-red function node: home assistant tibber.yaml: The "state" is unimportant, the important things are the attributes, "total", "time" and "category" which should influence the color of the "bar graph". I am now faced with the task of making this data accessible for the Plotly graph, which I am unable to do. This is partly due to the lack of documentation and I can't really interpret the numerous examples. To be honest, I don't really want a ready-made solution presented here - I want to understand how it works and how I can do things more easily and efficiently. Several small hints on how to achieve the graph would be very useful. If it's not a problem, we can stay in touch here and exchange ideas, if that's okay. Thank you for the support and best regards from Germany |
Beta Was this translation helpful? Give feedback.
-
|
Sorry for the delay in replying. I agree that the documentation is not that clear and I struggled myself a bit when doing the code for my graph. - fn: |- # arbitrary function. Only the keys that are returned are replaced. Returning null or undefined, leaves the data unchanged (useful )
({xs, ys, vars, meta, states, statistics, hass}) => {
# either statistics or states will be available, depending on if "statistics" are fetched or not
# attributes will be available inside states only if an attribute is picked in the trace
return {
ys: states.map(state => +state?.attributes?.current_temperature - state?.attributes?.target_temperature + hass.states["sensor.temperature"].state,
meta: { unit_of_measurement: "delta" }
};
},So effectively I'm applying a function filter ( Since my sensor exposes a list of values in the attributes raw_today and raw_tomorrow like this: Then my code just maps those values to xs and ys (xs has to be converted to type Date): ({ meta }) => ({
xs: meta.raw_tomorrow.map(({ start }) => new Date(start)),
ys: meta.raw_tomorrow.map(({ value }, i) => value),
}) |
Beta Was this translation helpful? Give feedback.
-
|
This looks awesome! |
Beta Was this translation helpful? Give feedback.
-
|
Hi, data_generator: |
return entity.attributes.data.map((d, index) => {
return [d["Timestamp"]*1000, d["TotalPrice"]*100];
});So for it to work with this plotly graph I believe the following would work filters:
- fn: |-
({ meta }) => ({
xs: meta.data.map((d, index) => new Date(d["Timestamp"]*1000) ),
ys: meta.data.map((d, index) => d["TotalPrice"]*100 ),
})However I don't know if the sensor data attribute supports showing past hours of the day of if it only shows the hours from now and in the future - might be a limitation of the integration. Personally I would avoid using this integration for the following reasons:
|
Beta Was this translation helpful? Give feedback.
-
|
Data produced with that integration is like this: I just left some out from the middle.. |
Beta Was this translation helpful? Give feedback.
-
|
It seems then that this filter would work: ({ meta }) => ({
xs: meta.data.map((d, index) => new Date(d["Timestamp"]) ),
ys: meta.data.map((d, index) => d["TotalPrice"]*100 ),
})Since for each item in the data attribute, it will take the |
Beta Was this translation helpful? Give feedback.
-
|
Thanks for trying, but it didn't work. |
Beta Was this translation helpful? Give feedback.
-
|
You need to replace all other logic that was referencing the old sensor as well. For example there's this other function that calculates the minimum and maximum value of the day to set the range of the fn: |-
$ex {
vars.current = states
vars.max = Math.ceil(Math.max(20, ...meta.raw_today.map(o => o.value), ...(meta.raw_tomorrow || []).map(o => o.value))/ 10) * 10;
vars.min = Math.floor(Math.min(0, ...meta.raw_today.map(o => o.value), ...(meta.raw_tomorrow || []).map(o => o.value))/ 10) * 10;
}That needs to change to something like: fn: |-
$ex {
vars.current = states
vars.max = Math.ceil(Math.max(20, ...meta.data.map((d, index) => d["TotalPrice"]))/ 10) * 10;
vars.min = Math.floor(Math.min(0, ...meta.data.map((d, index) => d["TotalPrice"]))/ 10) * 10;
}I assume you are not familiar with programming? If that's the case, you could try using chatgpt for help with changes. |
Beta Was this translation helpful? Give feedback.
-
I was previously using ApexCharts and getting annoyed by bugs and performance issues, so I have decided to migrate to Plotly and I am very satisfied with how these came out.
I use Nordpool integration to obtain hourly electricity prices for today and tomorrow. I have two entities: one with buying prices (in which I add distribution fees, etc) and another with selling prices (basically the nordpool price minus a margin I pay to sell). I also wanted to plot the forecasted solar production during those days (which I obtain with a REST template sensor and Solar Forecast API).
My requirements for the graph were:
Obs: the solar forecast is barely visible in the image since it is now November in Finland 😅 . I wanted to keep the y scale fixed to the maximum capacity of my solar panels system.
The prices for the following day (tomorrow) are usually published only in the afternoon of the current day, so I have a visibility condition to hide tomorrow's card until the prices become available.
Here are the yamls:
Today's prices yaml
Tomorrow's prices yaml
For anyone wanting to integrate Solar Forecast in a graph and curious about how I integrated with the API, here's the REST template sensor configuration:
REST template sensor yaml
Beta Was this translation helpful? Give feedback.
All reactions