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What’s your Energy Analytics DNA?

If your growing business spent $100,000 on electricity last year, it’s likely you will pay your utility $10 million on electricity over the next 25 years.  It’s also likely that you can use Energy Analytics to save millions instead.

It’s easy to get started with Energy Analytics by using existing data to measure what’s called your Energy Analytics DNA.  Your utility smart meter measures your peak demand (kW) every 15 minutes, generating 35,040 data points annually; this information is available to you free of charge.  By arranging these data by date (vertical axis) and hour (horizontal axis) then color coding them, HelioPower can quickly create a visual representation of that meter’s unique historic load profile: your “Energy Analytics DNA”.

Energy Analytics DNA Case Study: Reducing Demand Charges

To the right we see the Energy Analytics DNA of a vegetable packing house.  From January through July their energy loads are light (green); we can clearly see consumption picks up around 6am… when the first shift arrives.  Loads increase (yellow and red) in late July when packing operations begin.  The reddest region of the chart demonstrates their dates and times of peak energy intensity… which unfortunately fall squarely in PG&E’s Peak Rate Period, as represented by the black box.  Like many California Agribusinesses, this firm uses the most energy when it is most expensive.Avoid Demand Spikes

Some of that expense can be easily avoided.  As you can see from the red line chart, there was a significant demand (kW) spike in July; further examination reveals this occurred at 1:45 PM on July 4… an early celebration perhaps?  HelioPower brought this to the client’s attention and we quickly learned that this resulted from maintenance performed on a refrigeration system.  Had that refrigerator been started up just 2 hours earlier or 4 hours later, the company would have saved over $1,300 on their utility bill… with no investment.

Some of that expense can be easily avoided.  As you can see from the red line chart, there was a significant demand (kW) spike in July; further examination reveals this occurred at 1:45 PM on July 2.  HelioPower brought this to the client’s attention and we quickly learned that this resulted from maintenance performed on a refrigeration system.  Had that refrigerator been started up just 2 hours earlier or 4 hours later, the company would have saved over $1,300 on their utility bill… with no investment.

In my next post we’ll consider the Energy Analytics DNA of a seasonal nut processor… stay tuned.