# Real-Time Expressions: Compute Energy Costs

## Overview

Compute energy costs from Watts logged. This operation will use a combination of the summary statistics tile view and real-time expressions.**Two methods**to generating energy costs from Watts will be described, each with its own advantages and disadvantages.

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## Syntax (Method 1)

Tile Type: Summary Total (Events measured in Hours).

Real-Time Expression:

*=[data stream]/1000*<cost per kWh>*

## Example (Method 1)

A data stream from a smart outlet,*Kitchen Outlet(power)*, is logging data in Watts. This data stream needs to be converted to cost.

Add a tile and select the Tile Type to be Summary. Under the Summary Value drop-down, select Total. There are two options under Total Basis.

*Events by value*will simply add up every value in the data stream into a single summation. In the example above, there have been 33,953,657.80 Watts logged over time.

Watts needs to be converted to Watt-hours (Wh). To do this, simply select the second option under Total Basis,

*Events measured in Hours*. In the example above, there have been 2,692.40 Wh used.

Next, convert Wh to kWh by using a simple real-time expression to divide by 1000. In the example above, the expression is:

*=[Kitchen Outlet(power)]/1000*

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The final step is to multiply the total kWh by the your electricity rate, typically expressed as the cost per kWh. In the example above, the kWh rate is $0.10. The final expression is:

*=[Kitchen Outlet(power)]/1000*0.10*

The final computation for the total energy costs for the kitchen outlet is $0.27. Selecting specific time ranges in the timeline will automatically update this calculation for the energy costs in that time range.

## Advantage of Method 1

The energy cost show is responsive to the time range selected in the timeline.## Disadvantage of Method 1

You cannot draw the cost as a line graph or display it in any other way than a single value. You can only use this method in Tiles and not in Waves or Lines.----------------------------------------------------------

## Syntax (Method 2)

Tile Type: Any type ... Line Graph is particularly useful.

Real-Time Expression:

*=math.sum([data stream]*math.timeDelta([data stream], "hr")/1000*<cost per kWh>)*

## Example (Method 2)

A data stream from a Tesla charger,*power*, is logging the power, in Watts, consumed by charging the vehicle. This data stream needs to be converted to cost and displayed as a line graph.

*=[power]*math.timeDelta([power],"hr")*

This will create a data stream filled with values of Watts multiplied by hours. Next, perform a cumulative summation of each data point to add up the Watt-Hours from left to right:

*=math.sum([power]*math.timeDelta([power],"hr")*

Finally, divide by 1000 to get kWh and multiply by the cost per kWh (in this example, the cost per kWh is $0.10):

*=math.sum([power]*math.timeDelta([power],"hr")/1000*0.10)*

The result is, indeed, accumulated energy costs. However, the resulting numbers look something like this: 5.35277354892572. Let's pretty this up.

First, round the significant digits down to two to better match the way people like to see currency numbers. Use the math.round method:

*=math.round(math.sum([power]*math.timeDelta([power],"hr")/1000*0.10),2)*

Finally, add a $ to the beginning of each data point using the concatenate operator, &:

*='$' & math.round(math.sum([power]*math.timeDelta([power],"hr")/1000*0.10),2)*

Comparing the Watts logged line graph (top) with the energy costs (bottom) shows the cost progression as energy is consumed.