New EDF/CUB Smart Meter Data Report Shows Potential for Abuses of Power and Collusion
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On November 14, 2017 the Environmental Defense Fund and the Citizens Utility Board of Illinois released the results of a study “New Smart Meter Data Shows Potential of Real-Time Pricing to Lower Electric Bills.”
The report concluded that “Ninety-seven percent of a sample of Commonwealth Edison (ComEd) customers would have saved money in 2016—without changing their electricity use—had they participated in a ‘real-time pricing’ program in which power prices change hourly.”
Specifically, the paper finds real-time pricing would have trimmed bills for the average ComEd customer by $86.63 annually, or 13.2 percent less than they paid under the traditional flat-rate power pricing system. Moreover, real-time pricing would have generated savings for 97 percent of the households covered in the study, comprising total savings of $29.8 million.
If you identify yourself as an environmentalist and have become enamored with the idea of time-of-use billing, please don’t be deluded into thinking that the Illinois report proves that smart meters will offer environmental benefits, because the report states that 97% of the customers WOULD NOT need to change their consumption patterns to “save money.”
And please don’t be fooled into believing that time-of-use billing plans implemented by investor-owned utilities will save you money, because even as demand for electricity has decreased, in the real world, rates have increased. Some jurisdictions have implemented fixed minimal charges, so that when consumers conserve, they have to pay for electricity they are not even using.
Details about the bill impact on 3% of the population are not provided, but does this statistic potentially make a case for targeting the 3% if the purpose of time-of-use billing is to shift demand to non-peak times? Unless those customers are unable to shift their consumption, for example, if they work 3rd shift and are not even home during the reduced rate time periods? Other customers may not be able to “shed load” if they need power for medical devices. What percentage of the 97% of customers selected to be surveyed were simply not home during the peak pricing periods?
Had ratepayers not been surcharged for the installation of wireless utility meters in the CUB-EDF report, would ratepayers have saved MORE than the $83.63 annually?
And, what are the undisclosed costs for future maintenance, repair, and security of the wirelessly controlled grid? We can ask PPL customers about meter replacement costs.
The Allentown-based utility touted itself as a pioneer when it installed 1.3 million meters from 2002 through 2004. But those devices proved obsolete in just four years, failing to meet the minimum performance requirements of new state regulations. (Source)
The reported total savings of $29.8 million in Illinois is determined SOLELY by the price differential between flat rates and time-varying rates, which is subject to change. Industry research has indicated if the price differential is not punitive enough, results are diminished, fueling the entitlement by utilities and regulators for even higher surcharges.
And, pricing is subject to change after meter installation. If you want to learn more about how that works, research what happened to solar producers who accepted a wireless smart meter so that they could sell their electricity back to the grid. After meter installation, compensation formulas were altered in favor of utilities, Look also into caps on solar, the favoring of utility –scale solar over rooftop, and surcharges for solar producers to access the grid to understand the bigger picture.
But here is where the rubber really meets the road.
Does data lie? And, are human rights abuses acceptable? And, are we pursuing another wave of unsustainable economic growth under the guise of sustainability with an unsafe product?
Does data lie?
While the Illinois report recommends that other states adopt legislation to share anonymous energy-use data with researchers, the Illinois paper points to the dangers of outcome-oriented data interpretation by special interests.
In another example; Navigant reported that in Massachusetts, National Grid’s $45M 15,000-meter pilot program achieved a remarkable 98% retention rate. But the problem is that the pilot numbers dropped to 11,000 while the cost rose to $60M, making the math highly suspect and misleading, if not fraudulent. This scenario was compounded by the auto-enrollment program design that overran the process of community consent.
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