Sense is an excellent whole house power consumption tool. Real time power monitoring makes it simple to view current power consumption and determine which devices draw excessive power. After weeks or months, machine learning devices identification will take place and your whole house power consumption profile will start to emerge. Machine learning takes time so be patient.
Start by taking a whole house tour. Upon entering a room turn on and off individual switches and watch the power meter increase and decrease. Incandescent lighting is a power hog and the power meter will increase between 60w (watts) and 400w depending on the number of bulbs and their power rating; not good. Replace incandescent lighting with LED bulbs. LED lighting has a much lower operating cost; more efficient and will outlast an incandescent bulb. The annual operating cost of ten (20) sixty (60) watt bulbs operated for an average of six hours per day at 15 cents per kilowatt-hour is $395. Compared to equivalent LED lighting the annual operating cost is $52.00 a $342 annual savings.
In the early morning hours when everyone is sleeping analyze your always on usage. Many devices demand power at rest or powered off; for example, furnace, garage door opener, refrigerator, router, washer, etc… Garage door openers are a good example of always on power usage; while at rest they may demand 20w of continuous power to be ready for the next time you open and close the garage door. A Keurig brewer use the most power during initial startup and after brewing. If the power is kept on, the brewer continues to use 200 to 400 watts of power in short bursts to heat water when the Keurig is not in use. Set the Keurig energy saving mode or auto off timer to conserve power when not in use. There is little you can do about always on power usage until the next time you must replace an item. Look for Energy Start appliances, electronics, heating & cooling, lighting and fans.
Other usage will decrease over time as machine learning starts to identify devices and distributes power between each device; for example, washer, dryer fridge, circulator pump, microwave, etc.… Again, machine learning takes time so be patient and help the Sense community identify when prompted. For example, a heater was identified by Sense and it took some time to identify the source. The heater was a ceiling light/vent/heater combination in the guest bathroom.
I have noticed that Sense machine learning identified Incandescent lighting but has not identified LED lighting as of now.
FYI – after replacing incandescent lighting, turning off a 2nd refrigerator in the bar, turning off the garage door openers, replacing an old TV, setting the hot water heater to 120 degrees, turning on the refrigerator economy mode and using spot lighting the electrical bill dropped 50%. As a power consumption tool Sense is invaluable.
In closing Sense has other practical applications. No need for a home freeze alarm in the north, set a custom alarm to alert you when the furnace does is off for a period (days, hours or minutes). Tell when you kids turned off the TV and go to bed.
Would I recommend a Sense unit to my friends; YES.