Load profiling is a method of tracking energy usage with software that recognizes the on/off signature a particular device. When the device turns on, the software recognizes the specific load increase and begins logging. Likewise, when the device turns off, the same decrease in load signals the software to stop logging.
By programming electrical rates into the software both cost and kilowatt-hours are displayed on a run time profile. This profile is represented with a bar chart that shows how much power was used and when it was on during a 24 hour period.
Our research, thus far, has found only one manufacturer in the home energy metering market that is using this technology. Energy, Inc. of Charleston, SC offers load profiling in their Footprints software which is compatible with the TED 1000 and TED 5000 home energy monitors.
||Hot Water Tank Load Profile Using
TED Footprints Software.
Click image to enlarge.
The biggest advantage of the software is that it offers a concise picture of the cost, power draw and amount of energy used by an appliance or device without having to add current transformers (CT's). The Footprints software can capture and store up to five different load profiles. The daily history can be accessed by device and by calendar day.
The main drawback we found was its inability to capture more complex household loads reliably.
Load Profile Software Testing
Our testing was performed over a period of several months. Simple on-off loads that draw a constant amount of power track well. Examples of this are an electric hot water heater, as shown above, and the auxiliary heat strips in a central air system if they are designated as specific devices. However, more complex loads that projected different levels power as they turned on and off did not track well. Examples were a variable speed heat pump and multiple burners on the electric range.
The software does offer a learn feature which is handy if you do not know the size of the load you are trying to track. Simply turn on the learn mode and the software searches for a sudden increase in load over the next 30 seconds. During this period you can turn on the dryer, bump up the thermostat or energize what ever other device you want to measure. When the new load is detected, the kilowatts are displayed and recorded as the anticipated load for the device. This value can be edited as well as the variance threshold which defaults to +/- 10%.
Loads that ramp up or go through various stages of start-up and shut down are difficult for the software to recognize and do not track well. Examples of this are variable speed heat pumps and kitchen ranges that draw different amounts of power as burners are turned on and off. These devices do not project a constant load pattern.
The software has a provision to define the load in in stages. However, this provision anticipates that the stages will turn off in the opposite sequence in which they turned on. This is not always the case.
For example, if tracking an entire HCVAC system, the auxiliary heat strip may or may not turn on after the heat pump compressor turns on. It depends upon the outside temperature and how many degrees of change the thermostat has requested. In another example, dinner is not cooked using same number or sequence of burners from night to night.
Similar sized loads on the same channel were difficult for the software to differentiate. In our test case we used two, four-ton heat pump compressors on the same sub-panel. Even though the loads were slightly different as captured in the Learn Mode, and variance was tightened to +/- 5%, the load profile software had difficulty differentiating between them. Both loads showed up primarily as one device.
Load profiling in the Footprints software is a good tool for tracking large, simple on-off, 240 volt loads. Smaller, 120 volt loads tend to be difficult for the software to recognize due to similar profiles on other circuits. Plug-in meters are better suited to measure these smaller loads.
Since the load profiling feature can only track up to five devices, only the largest loads in the home should be monitored because that is where the most energy dollars are spent. Algorithms will need to be improved to capture HVAC equipment profiles more reliably. Sub-metering or circuit level monitoring still remain the most reliable tool for gathering this variable HVAC energy data.