One important thing to know if you want more commercial customers is interval data. What is it, how do you use it, how can you get it and why is it so bloody important?
What Interval Data Is
Interval data is a collection of information about energy usage over time. Usually it is quite detailed and at a minimum contains information about each hour of energy use for the time period.
Interval data can be data collected at any time interval but most commonly:
- 15 Minute Interval Data
- 30 Minute Interval Data
- Hourly Interval Data
If you collect interval data from a data logger it is usually capable of recording much shorter time segments (e.g. 5 seconds) depending on the setting.
Interval data comes in different formats but we can divide them into 2 broad groups:
- Vertical Interval Data (download vertical example)
- Horizontal Interval Data (download horizontal example)
Vertical data shows the data with respect to time moving in one direction top to bottom.
Horizontal data shows the data where each row represents 1 day, and each column moves 1 interval through time (e.g. 15 minutes).
How To Collect Interval Data From Your Customer
It’s often possible to collect interval data from your customer to assess. Not all customers will have an interval data recorder although most larger (commercial) customers will.
To collect your customer’s interval data you need to request it from their energy retailer (e.g. AGL, Origin etc). Often in order to grant your request, the retailer will ask you for a signed Letter of Permission from the account holder (for privacy reasons).
So here’s what you do:
- Ask your customer to sign a Letter of Permission (so that you can access their data) – Download our letter of permission template
- Send the letter of permission along with your request to the energy retailer (Use our email template to request interval data)
What To Do With The Interval Data
OK so there was a time earlier in my solar career where I jumped through the hoops, got the interval data file on my computer… Now what? I spent several hours on excel analysing the data and getting some pretty graphs which I then put together in a proposal for the customer. Obviously this wasn’t ideal.
When you get the interval data from your customer, you need some way to decipher it.
A few nice ideas:
- Get the view of a full week and compare it to the expected solar system energy production. This can give a really clear picture of what a typical week of usage vs production looks like.
- Take each day of the week and average them out so you get an idea of average energy patterns on different weekdays (should confirm what you see in the point above).
- Take each day from each month and average them to get a clear picture of how your monthly energy use varies. This should show any seasonal loads such as heating or cooling.
- Add up the production for each day of the year and plot it as a bar chart over 365 days. This gives a really clear picture of energy use including holidays, weekends and any spikes in consumption.
Why Interval Data Is Important
Interval data can give you a really clear picture of energy use patterns. Now it’s never going to exactly reflect someones energy use 100% (because usage may vary day to day, week to week, year to year). However it gives you the closest possible view of what their energy use is likely to be in the future.
When we’re talking about installing a secondary energy source (such as solar panels) it’s vital to have an understanding of their energy use first.
If you have interval data, you can easily compare a customer’s likely future energy use to the likely solar production you’d expect from an xkW solar system. Then this information can help the customer make an informed decision. It also helps to minimise solar export (if it’s desirable to do so), maximise battery energy storage and solar energy self-consumption.
The Difference It Makes
Here is an example of the numbers you might get by assessing a customer’s potential solar installation. One uses the customer’s actual interval data, the other uses a residential profile shaped to their average energy use.
As you can see in the example above, both cases use the same amount of energy. But because the data profile on the right is estimated using a similar profile (Primary School) to the one on the left (Child Care Center) we see almost 6% additional export which adds 2 and a half months on to the payback period! This is significant (given the quick payback period anyway).
As you can see, interval data is very important to get an accurate picture for your customers. You can upload interval data, use interval data profiles or even create your own (easily) using Solar Proof. Good luck out there! I hope you got something valuable out of this article.