by K.T. Weaver, SkyVision Solutions
From a recent peer-reviewed industry article , here is what is stated about the issue of privacy and smart meters for the “end user” of electricity:
“Conventional meters were only capable of measuring and displaying the aggregate consumption. The data was collected manually in intervals defined by utility company for billing. Smart meters however, are capable of collecting information with higher frequencies, i.e., every 15 min. Initial AMI deployed projects in Ontario, Canada, sustain readings at intervals of 5 to 60 min. Current technologies even allow for measurements every minute. By analyzing smart meter’s data, it is possible to perform ‘consumer profiling’ with an alarmingly high accuracy. Examples range from how many people live in the house, duration of occupancy, type of appliances, security and alarming systems, to inferring special conditions such as medical emergencies or [a] new born baby.
Profiling allows extracting residents’ behavior even without utilization of sophisticated algorithms and computer aided tools. Murrill and colleagues have shown that it is possible to identify the use of major appliances in a house, by analyzing only a 15 min interval cumulative energy consumption data. Molina-Markham et al. have shown that with the current general statistical schemes it is possible to identify the usage pattern from AMI data even without the detailed signatures of appliances or previous training.”
Despite the above information on how smart meters invade personal and behavioral privacy and the scores of articles I have personally written on the subject at this website, here is what the Vice-Chairman of DTE Energy said about smart meter privacy this past week at a hearing in Michigan :
“We believe AMI has actually improved the privacy of customers.”
“The information we gather despite what’s been reported here today is nothing but consumption, the exact same information that we recorded prior to the AMI installation, the exact same information you could gather by standing next to your analog meter and just looking at the meter.
We can’t tell what type of appliance is running, or what’s on or off, or who’s home or not home, nor are we actually interested in that in any way.”
In case the above words are so unbelievable that you think I may have just made it up, here is a video excerpt from the hearing in Michigan.
It is difficult to believe that an officer of a major corporation could either be so ignorant or could make such false statements of his own volition, … and to deny the clear and unambiguous privacy risks associated with smart meters and the granular data they collect.
First of all, the DTE Energy executive’s statements are likely literally false based upon the fact that most smart meters are capable of collecting additional energy-related data beyond usage in kWhrs, e.g., reactive power and voltage. You can’t observe those parameters watching an analog meter.
The main difference, however, between an analog meter and the smart meter is the frequency of data collection. No one is standing outside my home recording my meter reading every 15 minutes, and if they were, I would have them arrested for trespassing. That is essentially what is happening with a smart meter, and then the data can be analyzed, either by intuitive observation or software algorithms to reveal and to profile customer behavior as has been reported by countless expert reports and peer-reviewed articles.
Just to quickly refute one specific statement of the DTE Energy executive, stating that “we can’t tell … who’s home or not home,” please refer to my article from 2014, “Utilities Can Monitor Home Occupancy Using Smart Meters.” 
Maybe the DTE Energy executive should read the recent book on Big Data: A Revolution That Will Transform How We Live, Work, and Think :
“[U]tilities are rolling out ‘smart’ electrical meters in the United States and Europe that collect data throughout the day, perhaps as frequently as every six seconds — far more than the trickle of information on overall energy use that traditional meters gathered. Importantly, the way electrical devices draw power creates a ‘load signature’ that is unique to the appliance. So a hot-water heater is different from a computer, which differs from marijuana grow-lights. Thus a household’s energy use discloses private information, be it the residents’ daily behavior, health conditions or illegal activities.”
Finally, one of the reasons I continue to write about this subject of smart meters was summarized in the recent legal brief by Naperville Smart Meter Awareness (NSMA) :
“The most likely governmental use of smart-meter data — for law enforcement purposes — may well subject citizens to loss of liberty for activities within their homes that would otherwise go undetected. The use of the data in the marketplace, as is likely inevitable, will lead to unwanted marketing communications, as well as the collateral harms that will arise when commercially available data gets into the hands of criminals, fraudsters, and other wrongdoers.”
The DTE Energy executive quoted in this article is an example of the dogma and propaganda that continues to lead the citizens of this country toward the loss of liberty within their own homes as described above. In addition, if a utility executive can not present real facts as part of a prepared testimony, he is just wasting everyone’s time as well as deceiving them.
 Ramyar Rashed Mohassel et al., “A Survey on Advanced Metering Infrastructure,” International Journal of Electrical Power & Energy Systems, Volume 63, December 2014, pages 473 – 484; available as open access at http://www.sciencedirect.com/science/article/pii/S0142061514003743.
 Testimony of Steve Kurmas, Vice-Chairman of DTE Energy, before a hearing of the Michigan House Energy Policy Committee, February 21, 2017.
 “Utilities Can Monitor Home Occupancy Using Smart Meters,” SkyVision Solutions Blog Article, October 2014, at https://smartgridawareness.org/2014/10/08/occupancy-monitoring-using-smart-meters/.
 Mayer-Schönberger, Viktor; Cukier, Kenneth. Big Data: A Revolution That Will Transform How We Live, Work, and Think (pp. 152-153). Houghton Mifflin Harcourt. Kindle Edition; refer to https://www.amazon.com/Big-Data-Revolution-Transform-Think/dp/0544227751
 Brief of the Plaintiff-Appellant, Naperville Smart Meter Awareness, Docket 16-3766, U.S. Court of Appeals for the Seventh Circuit, February 21, 2017; available at https://skyvisionsolutions.files.wordpress.com/2017/02/020-nsma-brief-with-rule-30a-appendix.pdf