[Evan Wright]

Thanks for your response, Kate. It’s really helpful to hear the approaches others are taking. 

By “near-census”, I’m referring specifically to the use of all of our metered interval data to replace load research sampling. Previously, we would sample a small portion of meters in each rate class to get hourly loads and then apply an expansion factor to scale up the kwh to represent the total hourly load for that rate class. Since we will be using all meters with interval reads, we are taking a census of interval meter usage, but I’m calling it a “near-census” because there are a small portion of meters that do not have interval reads. 

Thanks again! 

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Evan Wright
Energy Forecast Analyst, Lead
Evergy
816-652-1063
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Original Message:
Sent: 02-24-2021 09:19
From: kate lemay
Subject: AMI/meter data validation

We perform extensive data validation as the data goes into our data hub to ensure the load process works properly. From there we are also comparing the intervals to the register reads used for billing. This helps identify anomalies in the interval data. Can you clarify what you mean by a ‘near census’ of metered usage?

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kate lemay
Director of Enterprise Analytics
Black Hills Energy
6166343919
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Original Message:
Sent: 02-22-2021 17:40
From: Evan Wright
Subject: AMI/meter data validation

Hello, everyone. Thanks in advance for your help!
I’m looking for some insight on what criteria others have used to validate AMI customer usage compared to other data sources.

Evergy is currently moving interval kwh meter data into a data hub and will be replacing the previous load research sample with a “near-census” of customer metered usage.

Thanks again!

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Evan Wright
Energy Forecast Analyst, Lead
Evergy
816-652-1063
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