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About the Aggregation Analysis Report
This report aggregates (totalizes) multiple data points and shows the peak, minimum, and total consumption as well as computes load factor. This information is used to make decisions about demand limiting. By reducing peak consumption and leveling the total load, volatility is reduced and energy customers can make significant improvements in their energy procurement. This report helps identify complementary combinations and unattractive peaks. Organizations can use this report when writing Requests for Proposal (RFP) for commodity procurement.
Once you select this report, you define the parameters to chart, including: sites, data points, and time period. Additionally, you may choose whether or not to take floor area or weather into account when analyzing the data.
Note: This report only examines points that are in meters. You must configure energy points into meters using the Configuration tool in order to run those points in the Aggregation Analysis report.
The following graphic is an example of an Aggregation Analysis Report.
Figure 4-1 Aggregated Analysis Report Example.
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This example shows a report of electrical demand and consumption aggregated for three facilities. The report shows aggregated peak usage for each month of the year.
Creating the Aggregation Analysis Report
Perform the following tasks to create an aggregation analysis report:
- Start the report
- Select meters to aggregate.
- Set report parameters
Note: The following tasks assume the default home page setup. If you modify your home page to use the customHome page or semiCustom home page, navigation and screens will look different.
Start the report
- Launch
shortBrandName from your browser using the following URL: http://hostname/eas
where hostname is the name or IP address of the Web Supervisor.- Enter appropriate login information to gain access to the home page.
- From the home page, open Aggregation Analysis by clicking on the Aggregation Analysis link.
- Click on New. You may need to enter security information again for the Java Plug-in.
Select meters to aggregate.
- With the Aggregation Analysis Report open, expand a site, right click on the meter to bring up the selection menu, and select Add to Report.
- You will see now that the meter has been put in the Input Window.
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Note: In this report, the Copy/Paste commands perform the same function as Add to Report.
Set report parameters
- Define the Time Period covered (Year field only).
- Select the Value that you want to Chart (refer to the following paragraphs).
Selectable options are Total, Peak, Minimum, and Load Factor. These options are mutually exclusive for the report, so you can only view one of these values at a time. However, after running the report, you can switch your value selection and the chart will automatically change to reflect the newly selected option.
- Total
This is the total sum of all metered values for each month of the selected year.
- Peak
This will show the peak metered value within all the logs for each month of the selected year.
- Minimum
This will show the minimum metered value within all the logs for each month of the selected year.
- Load Factor
- Choose a Normalization option, if desired.
Note: Degree Days are a practical method for determining cumulative temperatures over the course of a season. Originally designed to evaluate energy demand and consumption, degree days are based on how far the average temperature departs from a human comfort level of 65˚ F. Each degree of temperature above 65˚F is counted as one cooling degree day, and each degree of temperature below 65˚ F is counted as one heating degree day. For example, a day with an average temperature of 80˚ F will have 15 cooling degree days.
- Click Run Report
- Your results should resemble Figure 4-2:
Figure 4-2 Sample Aggregation Analysis Report.![]()
Note: Click on the column headers to resort columns to help you see the highest and lowest levels of use. This should help you analyze your data to make management and purchasing decisions. You can also drag and drop columns by clicking on the column header.
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