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Residential load shapes: AMI analysis breaks the mold

05/2/2019

The utility industry has been using the same basic average load shapes for decades. But how well do they describe the behavior of individual homes? What can AMI analysis tell us about the volatility of residential loads and what might this mean for your utility?

If you've been using industry standard residential average load shapes for load planning, rate design and energy procurement the chart below will look very familiar:Residential Average Electric Load

Chart 1: Example average residential load profile

But how reflective is this average of the day-to-day behavior of individual households?
The answer: not very.

Examining the patterns of energy use for specific meters reveals a chaotic and often unpredictable reality. In the chart below, we can see the actual daily load shapes for a specific residential meter over a four day period, with each color representing a different day. The amount of energy used in any particular hour is very different each day (sometimes ranging from as much as 0.5 kWh to 5.5 kWh), and the time of day that the meter "peaks" is different every day, and by more that just an hour or so. 

volatility_chart

Chart 2: Individual household load shapes for four sequential summer days  (each day is separate color)

This unpredictability is rarely, if ever, factored into rate case analysis as these depend upon the aggregate patterns over large numbers of meters and large period of time. But utility economics are often determined by actual energy use at specific hours, such as the annual coincident capacity peak or monthly transmission peaks. In these cases, load at one specific point in time determines a significant proportion of annual costs.

It is important, therefore, to factor in this volatility for analyses such as estimating the potential value of a new residential development, or the impact of new technologies such as electric vehicles, battery storage and air-source heat pumps. The net benefit of these new in-home devices will depend upon how well their peak load contributions can be understood and managed, and traditional methods of utility load projections need to be updated in order to reflect this reality.

We recommend spending some time doing this kind of exploratory analysis with your own AMI meter data, so that you can see for yourselves how this plays out for your particular location and customer base. You never know what insights may come from simply observing the energy consumption patterns of your own customers!

 

All analysis performed using SageSight AMI analytics platform.

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