<p>I have a dataset that gives values of</p>
<ol>
<li>temperature,</li>
<li>Relative humidity</li>
<li>Geopotential</li>
<li>Ozone mass mixing ratio</li>
<li>Potential vorticity</li>
<li>Fraction of cloud cover</li>
<li>Specific cloud ice water content</li>
<li>Specific cloud</li>
<li>liquid water content</li>
<li>Specific humidity</li>
<li>Specific rainwater content</li>
<li>Specific snow water content</li>
<li>Divergence</li>
<li>U-component of wind</li>
<li>V-component of wind.</li>
<li>Vertical velocity</li>
</ol>
<p>which parameters will make sense to do regression for electricity consumption? In search of this, I got this paper, <a href="https://www.sciencedirect.com/science/article/pii/S0306261914005674" rel="nofollow noreferrer">https://www.sciencedirect.com/science/article/pii/S0306261914005674</a> which use temperature and relative humidity for the same, and there are other papers also which uses temperature only as a parameter. Do you think that any other parameter from above I should incorporate? Can anyone please give an answer to the above question and pointwise reasoning for each item parameter and why it is used to calculate electricity consumption?</p>

CC BY-SA 4.0
2022-04-25T13:31:23.883Z
I would think the main influence in power consumption is temperature (for air conditioners/heaters/refrigeration).  Cloudcover fraction could affect light usage.  RH/U and V winds/specific humidity will be factors in how the temperatures feels so also likely factors.  In theory people may sleep a bit more on rainy days, but also may do more things indoors, so that's an interesting one, so I'd think 11/12 are involved.  There are other indirect connections (3/5/13/16 are factors in cloud coverage and rain), clouds affect temperature, etc.
JeopardyTempest
CC BY-SA 4.0
2022-04-25T13:35:24.103Z
Not sure what altitude ozone you're talking. High ozone at low levels is likely indicative of sinking air/high pressure... so another indirect one. But I think basically it all comes down to 1) climate control usage 2) lighting and 3) whether people are home/more active (though a lot of electricity usage can be industrial too, which could affect things).  In the end, if it's easy, just toss them all in, why not.  If you want the most likely candidates, I'd think 1, a combined magnitude of 14/15, 10, 6, and maybe 11/12 (if they show precipitation, I'm not familiar with the terms) in that order.
JeopardyTempest
CC BY-SA 4.0
2022-04-25T19:43:24.543Z
I agree with @JeopardyTempest. If you have the data & the time compare temperature with apparent temperature, there may or may not be  a difference. Apparent temperature considers temperature, humidity & wind speed.
Fred
<meteorology><temperature><data-analysis><python>
Which atmospheric parameters will give accurate result of electricity consumption of an area by using multiple regression model?
Dvarkesh 
# Which atmospheric parameters will give accurate result of electricity consumption of an area by using multiple regression model?

(Asked by: username_0 on 2022-04-25)

I have a dataset that gives values of

1. temperature,
2. Relative humidity
3. Geopotential
4. Ozone mass mixing ratio
5. Potential vorticity
6. Fraction of cloud cover
7. Specific cloud ice water content
8. Specific cloud
9. liquid water content
10. Specific humidity
11. Specific rainwater content
12. Specific snow water content
13. Divergence
14. U-component of wind
15. V-component of wind.
16. Vertical velocity

which parameters will make sense to do regression for electricity consumption? In search of this, I got this paper, <https://www.sciencedirect.com/science/article/pii/S0306261914005674> which use temperature and relative humidity for the same, and there are other papers also which uses temperature only as a parameter. Do you think that any other parameter from above I should incorporate? Can anyone please give an answer to the above question and pointwise reasoning for each item parameter and why it is used to calculate electricity consumption?

**Tags:** meteorology, temperature, data-analysis, python

> **Comments:**
> **username_1**: I would think the main influence in power consumption is temperature (for air conditioners/heaters/refrigeration).  Cloudcover fraction could affect light usage.  RH/U and V winds/specific humidity will be factors in how the temperatures feels so also likely factors.  In theory people may sleep a bit more on rainy days, but also may do more things indoors, so that's an interesting one, so I'd think 11/12 are involved.  There are other indirect connections (3/5/13/16 are factors in cloud coverage and rain), clouds affect temperature, etc.  
> **username_1**: Not sure what altitude ozone you're talking. High ozone at low levels is likely indicative of sinking air/high pressure... so another indirect one. But I think basically it all comes down to 1) climate control usage 2) lighting and 3) whether people are home/more active (though a lot of electricity usage can be industrial too, which could affect things).  In the end, if it's easy, just toss them all in, why not.  If you want the most likely candidates, I'd think 1, a combined magnitude of 14/15, 10, 6, and maybe 11/12 (if they show precipitation, I'm not familiar with the terms) in that order.  
> **username_2**: I agree with @username_1. If you have the data & the time compare temperature with apparent temperature, there may or may not be  a difference. Apparent temperature considers temperature, humidity & wind speed.  

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## 0 answers

