1. Data from your electric company. Most, if not all, companies allow customers to download what the electric company says is the amount of electricity you used and the times the usage occurred. Create an account with your electric company, if you don't already have one, then login frequently and download your data.
   IMPORTANT: Until you are sure that the electric company either is honest OR is careful in their thievery, download the data in overlapping chunks. In other words, lets say you logged in on March 3rd and downloaded all your data from January 1-March 2. When you login again on April 2nd, download all the data from January 1-April 1. This will allow you to compare the data between January 1-March 2 between the downloads. Believe it or not, some electric companies are sloppy enough to make their data manipulation public! I caught our electric company changing data LONG after it left the meter over and over again.
2. Data from an independent monitoring system.  I have used several, but if you have a Tesla Powerwall installation that included a revenue-grade meter, and you can see data from your system through your Tesla app, then you will be in good shape. Some 3rd-party monitoring systems have issues.  Emporia makes a good monitor that goes inside your home's or business' electric panel which monitors each circuit.  However, this only gives you insight into usage of those circuits you can monitor.  Furthermore, if you have solar production or a battery backup, then it won't monitor those.  Emporia makes another product that communicates with Zigbee electric meters.  In other words, it reads your wireless meter the same way that the electric company does, EXCEPT it does so more frequently.  Unfortunately, I've seen instances of freshly-captured data from this device that reflected our actual household usage, only to CHANGE at a later time in a way that matched the electric company's published data.  Does Emporia coordinate with large utility companies to prevent customers finding out about their theft?  You decide.
3. A basic understanding of any differences that exist in how the two monitoring systems report data.  Tesla reports data in 5 minute intervals as kW (kilowatts).  Our power company reports their data in 15 minute increments as kWh (kilowatt hours).  Using the common analogy between electricity and water, kW can be thought of as the rate of flow of electricity, whereas kWh is the accumulated amount of power usage (or production).  You have to be able to convert sensibly so that you are comparing like to like.
         There may be other differences in the data that you must account for and others that you should ignore (at least for the direct comparison).  For instance, if you have a solar array, Tesla Powerwall(s) and one or more new-ish Tesla automobiles, then you will see data for "Grid", "Solar", "Home", "Vehicle" and "Powerwall".  However, our electric company reports only "Delivered" (to the customer) and "Received" (from the customer's solar array and/or battery bank).  For our situation, the only Tesla category that is directly comparable is "Grid", because Tesla's "Solar" category is upstream of the electric company's meter.  Our home uses some of that solar power to run whatever electrical devices we happen to running at the time and some will go to refill our batteries, until they are full.  Only afterwards, does excess solar power from our roof go to the electric company's meter, which should then register it as "Received".  If you aren't on net metering, then your electric company might report things differently.
4. A way to compare the two datasets.  I've shared a template that works for me and some tips on how to use it.  However, you may have to make modifications to match your specific situation.  As I said above, you must be very careful to compare like-to-like in a logical, fair way in order to get a true answer about whether or not your electric company steals from you in the way ours does.
5. Data regarding your major electrical loads.  This is a very personalized collection, but it's important.  Understand what your major loads are and notice when they turn on and when they turn off.  Sometimes this is impractical.  I get it.  But other times it is easy to track.  For instance, we had a swimming pool with all those pumps.  Those pumps drew a lot of power.  When I converted the pool to a fishpond and permanently shut off the pumps, I noted the date.  Yet my electric company did not change our electrical usage!
        We also have several electric cars.  Electric cars don't all draw power in the same way.  It will depend on both the type of "charging station" that you have AND the car's onboard charger.  All of our cars are programmed to avoid power usage during peak hours.  One car (a Tesla Model X) draws a lot of power when it's charging  It's our home's major load as far as usage rate, even though it's not a major load over an entire billing cycle because we don't drive it that much.  It is programmed to start charging every day (that it's in the garage and plugged in) at precisely 10:00 AM because the sun is typically shining brightly by that time and it is not peak hours, so even during extended cloudy periods when our batteries are empty and we aren't getting much solar power, the grid power we use will be taken when the rates are lower.  Knowing these facts became very useful in diagnosing our electric company's fraud.  Whenever I take this particular car out during the day, return home during non-peak hours and plug it in, I note the date and time when I plugged it in because its power draw that day will differ from a typical day and I want to see if that is reflected in the various monitors I have.

However, I didn't have a plan of how to follow it up and kind of forgot about it for a few years.

Then in 2022, I noticed another anomaly.  The electrick [sic] company said that I used a ton of peak hour power that simply didn't make sense with what I knew about our usage.  So I investigated further.  I downloaded data from our electric company and from our Tesla Powerwall app and I made a spreadsheet to compare the two.  I went to Tesla Powerwall online forums and asked the public to review how I did the comparisons to see if errors could be found.  People tried to find errors, but were unable to find any.  I then called Tesla and asked them if there was anything wrong with the Tesla system that might explain the discrepancies I was finding.  They investigated and said our system was functioning correctly.  (Full disclosure, they did not review my spreadsheet, they only reviewed the hardware and software of the Tesla system.  They were unwilling to publicly criticize our electric company, but privately, several Tesla employees have expressed a lack of surprise about my findings.)
I then called Southern California Edison (our electric company).  To avoid repeating myself, I'll let letter of my formal complaint to the California Public Utilities' Commission (a.k.a. "CPUC"; apostrophe added by me to express the true situation) speak for the state of my knowledge in mid-2023:

"July 10, 2023

To: The Honorable Justice presiding over this hearing

Background and sequence of Events:

In an attempt to provide a benefit to my community and my family through our rooftop solar + battery system, I have programmed our system to strictly avoid use of electricity during peak hours and even supply power to the grid during this time of high demand. This is accomplished using a smartphone app linked to our solar/battery system. This app also makes it possible to independently monitor our energy usage and production, including the amount and time of electricity generated by our solar panels, the amount and time of electricity flowing to and from the batteries and the time and amount of electricity flowing to or from the grid.

When the sun is shining, the solar power from our roof first is used to supply power to our house and to charge the batteries, if needed. Any power produced in excess of the home + battery bank needs is exported to the grid and should be recorded by Southern California Edison’s (SCE) generation meter. At night, or other times when the electricity demands of our home exceed the production from the solar panels, our batteries provide the power needed. Only under unusual circumstances (e.g. multi-day cloudy periods, the hottest parts of summer, or inverter failure) do we use any grid power at all.

In late 2022, I decided to monitor our home electricity usage and production more closely and thus downloaded these data from Southern California Edison’s customer-facing website. To my dismay, when I compared the data from our Tesla solar + battery system with that from SCE, I noticed several glaring discrepancies wherein SCE claimed that on several bright, sunny days when our battery bank was full (and thus fully capable of supplying our home’s needs) we suddenly ceased supplying electricity and instead began consuming quantities of grid power during peak hours. In contrast, the Tesla data showed that we used no grid power during these same times, in fact we often continued to supply power to the grid during the early part of peak hours.

I initially believed that SCE would be interested in my findings and would want to investigate, so I called to inform them and invite them to look over my calculations to see if they could figure out the cause of the discrepancies. Instead, my first contact with SCE was greeted with hostility with the spokesperson at one point saying, "I know how you customers think!" as if customers are their enemy instead of the basis for their existence. The call concluded with a promise by the SCE spokesperson that I would receive a letter summarizing their review of the bill in question within 30-45 days. The letter, dated December 22, 2022, simply said that the bill in question was correct without addressing the discrepancies. My second call to them soon afterwards was less hostile, but they failed to provide any explanation of the noted discrepancies and did not inquire about my methodology. This call resulted in an offer to check the meter. I did not suspect the meter, but I agreed anyway. The technician checked the meter 2023-Jan-06 and found that it was functioning correctly, consistent with the idea that the discrepancy is happening downstream of the household meter or is due to an intermittent meter issue.

At this point, I could see that SCE was completely uninterested in investigating the discrepancies between the data in their final customer-facing database and the data from the independent monitoring system of Tesla. Perhaps their lack of interest is due to the fact that the discrepancies are to their financial benefit (graphic attached; “ErrorFrequencies.pdf”). So on January 20, 2023, I filed a complaint with the California Public Utilities Commission (CPUC) (attached; “CPUC_complaint20230120.pdf”). My complaint was acknowledged by CPUC on January 24, 2023. On May 24, 2023, I spoke with [name redacted], Senior Supervisor, Consumer Affairs, Southern California Edison and tried to explain the situation again, even offering to send her one of my spreadsheets to illustrate my methodology for uncovering these discrepancies. She allowed me to send her the spreadsheet, but her email reply on June 1 (attached; “EmailFrom[name redacted]_SCE_20230601.pdf”) ignored all the points that I brought up during our phone call and did not mention the spreadsheet. I sent her another email on June 3 to remind her of some key points in our discussion (attached; “EmailTo[name redacted]_SCE_20230603.pdf”), but have not received a reply as of this writing (July 10, 2023).

Soon thereafter I received an email from CPUC dated June 9, 2023 that essentially repeated the SCE talking points from Ms. [name redacted]. This communication also indicated that I had a 15-day window to file an appeal. I filed an appeal (attached; “InformalAppeal_578410.pdf”) the following day (June 10) via email. Thankfully, as relayed in a letter dated June 23, 2023, CPUC reopened 578410 and allowed this formal appeal.

Proposed resolution:

1) Most importantly, a fair resolution of this case has to include, at a bare minimum, a thorough investigation by an independent third party to monitor a representative sample of rooftop solar and rooftop solar + battery customers’ net export to the grid and import from the grid over several billing cycles and comparing that data to the data SCE uses to generate bills. In those cases where significant discrepancies are found, the investigation should determine the root cause of said discrepancies and this source of error should be corrected. If similar discrepancies that I have found at our home are widespread, millions of dollars that rightly belong to California customers is being siphoned into SCE accounts.

2) In addition, affected customers should be notified of the error and compensated accordingly.

3) Based on the six billing cycles from our own home that I’ve analyzed within the last year, SCE owes us $791.26 for the combined effects of the power that we did not use that they have falsely stated we did and the power that we provided to the grid, but for which SCE did not compensate us. (Spreadsheets detailing how this figure was arrived at will be made available upon request, but did not lend themselves to PDF format, so are not attached, but a description of the method used is attached; “SummaryOfComparisonMethod.pdf”.)

Respectfully,

[my name redacted]"

   This was the most glaring evidence that SCE manipulates usage data in order to charge customers whatever they want.  For this kind of sloppiness, you don't even need a second monitoring system to detect it!!!  But I also had copious data from my revenue-grade Tesla meter, via the Tesla app.  You can probably see why I was so confident at that time that justice would be served because my case was so solid.

Because I had chosen to have a CPUC hearing without attorneys present, it would be just me, an SCE representative (Robert) and the administrative law "judge".  (From this point on, I will refer to her as "the fudge", the reasons for which will become clear shortly.
Before the hearing, the fudge instructed us to exchange information.  This was easy for me because I had already shared my methodology in the form of a spreadsheet with SCE months before.  I then uploaded my formal complaint and SCE uploaded their "rebuttal" to the CPUC website.  Their "rebuttal" was so full of falsehoods and misleading information that I debunked point-by-point.  The fudge instructed me to share this information with the SCE representatives and the CPUC "court", including herself via email at least 5 days before the hearing (which I did).  I didn't know that I should have also insisted on uploading it to the CPUC website because 1) the fudge told me to send it around via email, she didn't mention uploading it and 2) I naïvely thought that I'd have plenty of time to upload it to their website later.
At the hearing, it quickly became clear that this was a rigged, corrupt, kangaroo court.  When I started to show my evidence that SCE manipulates data, the fudge asked Robert, "Do you know anything about this?", to which he lied, "It's the first time I've ever seen it.".  The fudge immediately barred me from talking about SCE's own data any further.  It didn't matter that Robert was demonstrably lying.  The fudge had been copied on my data sharing with SCE, including Robert.  It didn't matter that he was present in the room when the billing department representative had talked about their "QC" process.  It didn't even matter that, to this day (2026-January-01), all data downloads from SCE have this disclaimer at the top: "Based on how our systems process and categorize usage data, your download may contain usage data of the following types: actual, estimated, validated or missing." (my emphasis).  The fudge just accepted his lie as truth.  At this point in the hearing, I knew I was being screwed by the state of California's CPUC as well as SCE.
Nevertheless, I persisted.  After all, I still had the Tesla data and some other documentation.  After I presented the Tesla data, the fudge dismissed that as well, saying, "What concerns me is:  You've been checking up on Southern California Edison, but WHO's been checking up on YOU?!?".  That's right folks, the California Public Utilities' Commission (now you know why I inserted the apostrophe) that is supposed to protect the public from rapacious utility companies was instead laser-focused on protecting the itty-witty utility company against Big Consumer!  Given how extremely biased the fudge was, it was no surprise when I got the letter informing me that I'd lost the case.
I was surprised and angered, though, when I was denied permission to upload my rebuttal to their rebuttal to the CPUC website.  It did not matter that the fudge's own instructions had misled me into sharing the data in a way that the public would never see it... until now, because I'm publishing it all here.  Of course, who is going to look on some agricultural history website for information about utility company fraud?  Oh well, it may be all I've got.

I reached out to the press. I reached out to various "public advocacy" groups.  The press ghosted me, with the exception of LA Taco (yes, they are a local news organization).  However, the LA Taco representative told me that they had only 2 employees and couldn't handle such a big case.  One "public advocacy" group, "TURN" acted very peculiarly.  When I shared my information with them, they first put me in touch with someone who acted interested, but who could never arrange a meeting with the organization's leaders so that I could present my data to more than just her.  Eventually, I was told that they don't deal with actual fraud, instead they are solely focused on reducing rate hikes.  It didn't matter to them that SCE's fraud obviates the need for rate hikes!  When you can just fabricate whatever usage data you want to customer's bills, you can engineer your own rate hikes without asking for anyone's approval!!!  TURN didn't care.  They are just another cog in a massive fraudulent machine.  I am still in contact with a few other public advocacy groups and while the smaller one seems interested, they wanted me to contact a larger group, which is also acting strangely, insisting that I get Tesla's feedback on my methodology, even though 1) Tesla has nothing to gain and much to lose if they piss off SCE, 2) I had already spoken with Tesla and 3) the Tesla data matches with what I know about my own usage!  I smell another rat.

I also tried to organize a class-action lawsuit.  One needs 40 co-litigants to bring a class action lawsuit in California.  No law firm would help me recruit.  Few would even call me back.  This is in a state where suing is like California's number 1 sport.
So that brings us to the present.  I have a website, so I am self-publishing this information so that others may be better armed in dealing with their electric company and if enough folks share information with me, we may get that class-action lawsuit going after all.  I'm not willing to publish my email address yet, but you can reach me via this site's blog.  You can even do so anonymously by instructing me in your blog post to not publish it.  This is possible because no blog post gets displayed on the Web unless I approve it.  This is to prevent trolls and other miscreants from posting garbage on my website.  It isn't military-grade security, but it will prevent the average person from seeing what shouldn't be posted.

SCE's gaslighting debunked, point-by-point.

Instructions on how to use a spreadsheet.  Yes, Mr. Rojas of SCE actually claimed that no one at the massive Southern California Edison could understand my simple spreadsheet (one example is on page 11 of their "Answer" document above, lines 3 & 4).  So I spelled it out for them.  At the hearing, when I confronted him directly, he denied that SCE lacked the expertise to evaluate my spreadsheet, but if you read what they wrote themselves, it's clear that he was lying again.  Side note:  He also lied during the hearing by saying that I had said that inviting Tesla to the me-&-SCE sitdown "was unecessary"... exactly projecting his words onto me!  Mr. Rojas proved to be a proficient liar, which is, I expect, why he has the position he has at SCE.

A summary of the frequency of discrepancies above a specified threshold that I compiled as of July 2023.  I have since updated this and other information and some of it is shared in the next section.

A slide deck with lots of information, including numerous examples comparing SCE vs. Tesla data.
Here's one example (2 slides) from it:

1. Data for relevant period downloaded from SCE’s customer-facing database.
2. Data for corresponding period downloaded from Tesla servers.
3. Data from the two systems are formatted differently, so Tesla data is converted from 5-minute intervals of kW to 15 minute intervals of kWh to match the SCE format.
4. Peak hours are marked using the SCE timestamps and SCE definitions of what constitutes peak hours.
5. Net kWh exported to or consumed from the grid as reported by the Tesla monitoring system is compared to the net kWh reported by SCE, taking into account both their grid meter reading and the generation meter reading within every 15 minute interval and then compiled for each day and each billing cycle. Care is taken to account for the fact that the Tesla data uses +/- to indicate direction of electricity flow, whereas SCE uses only positive numbers for both generation and consumption."

Southern California Edison now hides their data manipulation somewhat, meaning their data usually stays constant by the time they release it to consumers.  Comparison with the Tesla data strongly suggests that they are still fraudulently padding bills with extra usage that consumers don't actually use, but the evidence now comes by comparing with outside monitoring instead of appearing in SCE's own consumer-facing data.

  The graph below summarizes the total documented theft as of the end of 2025:

In all data, there is what scientists call, "noise".  "Noise" is the variations one sees due to imprecisions in measurements or small rounding errors that don't reflect any real differences, but are non-zero.  Therefore, when assessing whether one monitoring system agrees with another, one has to set a boundary or threshold, below which reasonable people can agree that the observed differences aren't anything to worry about, but are probably just insignificant noise.  Setting DIFFERENT noise thresholds within the same data set can also be instructive because if one is observing random fluctuations above and below a true noise threshold, then moving the threshold will move the proportion above and below (in this case in favor or the customer vs. in favor of the electric company) to the same degree.  In other words, if we are looking at random noise, and one sets the threshold for agreement at 1 (as an arbitrary example), with anything below 1 being considered noise, then raising that arbitrary threshold to 10 should reduce the frequency of numbers in favor of the company by the same factor (10X) as the reduction in favor of the customer.  However, if you are looking at non-random changes in the data, for instance intentional data manipulation to fatten a company's profits, as a hypothetical example, then the percent in favor of the company will reduce by a lesser amount than the reduction in favor of the customer.
The series of slides below illustrates several points, including:

1. My methodology of comparison is accurate, because if there were a systemic error in my method, one would not see the observed high percentage of agreement between the two monitoring systems on a 15 minute basis.
2. The errors are non-random and almost exclusively in SCE's favor.
3. While there may be a rare few 15-minute intervals that randomly appear in favor of the customer, SCE makes sure that each day, and especially each billing cycle, they screw their customers to fraudulently fatten their profits.

1.  Find out if your electric company claims you are using electricity in ways that benefit them, but don't make sense to you.  Feel free to download my spreadsheet template and plug in your own numbers, making sure that your situation is reflected accurately (your setup may be somewhat different than mine).  Step-by-step instructions for using the template are below, but these instructions assume that your electric company and monitoring system are the same as mine.  Additional alterations may be required for your specific situation.  Feel free to reach out to me via my blog if you have questions (and if you prefer our communication to be private, please instruct me not to publish your question when you contact me!).

2.  O.R.G.A.N.I.Z.E!!!  Reach out to me and/or other watchdogs and let's compare notes.  Maybe we go with a class-action lawsuit or maybe we take some other actions.

1. Change the dates of Column A to match those from your bill
2. Paste in 15-minute interval, kWh data from your electric company into columns D & E.  Column D is what your electric company claims is your usage and Column E is what they claim they have received from you, so Column E is only applicable if you produce power.
3. Download data from your Tesla app by choosing your Powerwall display, then "Energy", then "Day", then "Choose Date...", then actually choose the date, then click the horizontal row of 3 dots at the upper right of your screen and choose "Download My Data".
4. Attach each .CSV file from Tesla that corresponds to a billing cycle to the template.
5. Change all the '626" (the first day on the template, Columns G-J) to the name of the tab containing the Tesla data corresponding to the first day of your billing cycle.
6. Make sure that each column in G-J corresponds to the correct column in your Tesla data sheet.  In other words, the "Grid" data should be looking in the "Grid" data in your attached Tesla sheet.  If not, change them to make them match.
7. Once you are sure that your first day of Tesla data is accurate, attach the .CSV files from Tesla for the remainder of that billing cycle to make a multi-tabbed spreadsheet.
8. Now copy the formulae from that first day (Cells G2-J97) and paste for each day of the billing cycle, being sure to change each day within each group of 384 cells to reflect the intended day.  (I do this via repeated, Ctrl-V, Ctrl-H, but your spreadsheet software may have different keyboard shortcuts.)
9. In cell P2, record the date(s) that you downloaded data from your electric company.  This can be useful if your company openly manipulates data the way SCE used to.
10. If you want to convert kWh's into cost, look at your bill and change the generation and distribution costs to reflect the rates for the dates within your billing cycle.  The rates first cells are K71 & L71 for off-peak and peak, respectively, but it will have to be changed for each day.  I write the rates from the template and the rates from my bill on a slip of paper, then do global search and replace within the respective columns.  Once the dates are updated, edit cell K6 to document that fact.
11. If you want to generate the information needed to look at error frequencies like the first 3 graphs here, copy columns T-AA and paste as plain text/DIF into a blank spreadsheet.  Put autofilter and your countA function on and record the totals.
12. Feel free to reach out to me, if you have questions.  It may take a while (even a month is possible), but I will respond to everyone who isn't a troll.  It is essential that you tell me NOT to publish your question, if you want our communication to be private.  In this case, I will read it and respond (also provide your email if you want a direct response), but will keep your name off the blog, if so instructed.
13. I would also appreciate it if you reach out to me to share your findings for your situation.  I do not know how widespread SCE's practice of data manipulation is in the industry, but I would not be surprised at all if other Edison International subsidiaries engage in this fraud.