Aggregation report

This report plots aggregation (consumption) against demand using total, peak, minimum, and load factor values at various sites, meters, time periods and commodities. With this information you can increase total energy procured and determine complementary loads to improve your load factor. When negotiating a contract, this information can provide accurate consumption patterns versus the arbitrary classifications used by commercial and industrial customers.

Load factor values are between 0 and 1. The closer the load factor value is to 1 the more consistent is the building’s load profile, meaning that demand does not vary much.

Figure 245. Aggregation report

This report supports only one group. You add multiple nodes under this group.

NOTE: In this multi-node group, the system aggregates the data for all records based on the Aggregation property defined in the Advanced Settings window.

Chart Value

In addition to the standard properties, this report allows you to select a single Chart Value to apply to the graph:

Sum — sum of the energy consumption values for each interval.
Min — minimum power value for each interval.
Max — maximum power value for each interval.
Load Factor — calculated load factor value for each interval.

Table area columns

The table area shows information for each node.

Column	Description
Date	Identifies the start timestamp for each interval period.
Minimum	Reports the minimum power value for each interval.
Total	Reports the sum of the energy consumption values.
Peak	Reports the maximum power value for each interval.
Load Factor	Reports the load factor calculated for each interval.

Advanced Settings window

The rollup function for this report is fixed based on the data being displayed.

Property	Value	Description
Interval	optional drop-down list (defaults to the optimal number of records on reports); interval=option	Refers to the BInterval component, which the framework uses to identify the time between values in a trend (time series). When specified, a rollup is required, which causes the system to combine all values that fall into a single interval. Options range from `None` to a `Year`. Above the drop-down list, the `Use This Value` check box turns on and off the check box next to `Interval` in the Settings window (you access this window by clicking the Edit button (), followed by clicking the Settings button () on the chart). The availability of this check box provides an easy way for a user to enable and disable the use of intervals in chart calculations.
Aggregation	check box (if optional, and) drop-down list (property, defaults to `First`) or ORD parameter (aggregation=option)	Configures the default function to apply when the analytic request needs to combine values from multiple data sources into a single value. This applies to both value and trend requests. If aggregation is not enabled in the binding/settings window, the aggregation value defined in the Data Definition applies to all chart bindings, reports and tables. `And` returns the logical “and” of Boolean values. `Avg` returns the statistical mean, which is determined by calculating the sum of all values and dividing by the number of values. `Count` returns the total number or quantity of values in a combination. If you request this value on a binding in a PX view, the system counts the number of values based on the properties defined by the data source block and the algorithm’s Property Sheet. `First` returns the first value in the combination. `Last` returns the last value in the combination. `Max` returns the highest value in the combination. `Median` returns the value in the middle of a sorted combination—the number that separates the higher half from the lower half. `Min` returns the lowest value in the combination. `Mode` returns the statistically most frequently occurring number in the combination. `Or` returns the logical “or” of Boolean values. `Range` returns the statistical difference between the largest and smallest values in the combination. `Sum` adds together all values in the combination resulting in a single value. `Load Factor` returns the average value divided by peak value. `Std Dev` returns the standard deviation of the values in the combination.
Data Filter	optional NEQL query (property) or ORD parameter (dataFilter=query)	Identifies data sources in the subtree of the request node. When a predicate accepts a node that contains the desired data, the system does not search the node’s subtree for additional values (including the root node).
Data Mapping	Tag Choosers (defaults to `Sum` = hs:energy, `Min` = hs:power, `Max` = hs:power, `Load Factor` = hs:power)	Assigns tags to four options. Clicking the Tag Chooser opens a standard Select Tag window.
Totalize	`true` (true) or `false` or hisTotEnabled=option (ORD scheme parameter)	Turns on (`true`) and off (`false`) value accumulation. By default, the framework totalizes (accumulates) all consumption history values in charts, tables and reports. To prevent cumulative values, disable this property (set it to `false`).
Show Interpolation Status	false check box	Enables and disables the display of the interpolation status columns in report tables. Clicking this check box removes the status columns leaving only the record value columns.
Legend Position	drop-down list (defaults to `Inset`)	Changes the position of the legends that label graphical elements in charts. Three positions are possible: `None` removes the legend from the chart. `Inset` places the legend inside the chart area. `Bottom` places the legend below the chart area. `Right` places the legend to the right of the chart area.
Missing Data Strategy, Use This Value	check box	Enables and disables missing data interpolation for the current value. When enabled, the framework applies this strategy to all requests. When enabled, the framework applies this strategy to all requests.
Missing Data Strategy, Aggregation Strategy	drop-down list; aggStrategy=option (ORD scheme parameter)	Configures how the framework handles missing trend data (data in a series) when processing analytic requests and one or more records are missing for an interval. It applies when even a single record for an interval is missing. It does not apply to value requests. NOTE: If the analytic trend request specifies `Interval` = `none`, the framework ignores the Missing Data Strategy. `Ignore Series` ignores the entire series if any record even one interval is missing. `Ignore Point` ignores any missing records and aggregates the values in the existing records.
Missing Data Strategy, Interpolation Algorithm	drop-down list	Defines the algorithm used to interpolate values for missing values (missing records). `None` does not interpolate values for missing records. `Linear Interpolation` replaces a missing record by linearly interpolating the missing value using the prior and next records on either side of the missing record. `K-Nearest Neighbor` is for numeric, enum and Boolean records. This strategy replaces a missing value by calculating the majority value recorded for the item’s nearest K number of neighbors.
Missing Data Strategy, K Value	Numeric field editor (default = 1, min =1, max = 30)	Defines the number of records used by the configured interpolation algorithm when a record is missing to calculate the interpolated value.

Select Tag window

Figure 246. Select Tag window