Hello Everyone
I am trying to combine two online data sets together (the electricity prices and electricity consumption/production). the two data sets are changing continuously (giving something similar to the heartbeats).
I want to build a mathematical model so it can predict when its the right decision to buy/sell electricity or charge/storage electricity.
I have some experience in MATLAB, Power BI, excel. but as far as I know, they are all dealing with static databases, not with changeable ones.
Could anyone advise me of the best tools or programs to achieve that?
Thanks in advance
You can try R-studio Cloud or the colab by Google(Working with Python) for the same. Both are online. You can give the data source. So it will update the data as the given intervals.
for Continuously changing data first chcek the range and set max and min value. Then standardize the data, where μ is the mean and σ is the standard deviation from the mean; standard scores (also called z scores) of the samples are calculated.
Then you can predict when to sell and buy electricity.
I know there are many tools for this, since you already know excel, excel does deal with dynamic data sets, you can specify the data source as a website with "Web Query" (Data>New Query>Other Source>From Web). Follow the process from it to get the online data in a sheet and use whatever you'd use to analyze the data. The data obtained this way will not be static.
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