Ontario’s Industrial Conservation Initiative program, which rewards large “Class A” consumers for lower consumption during periods of high demand from the system operator’s supplier, cost others $1.27 billion in past 12 months. I won’t review the history of the program today as I did 3 years ago in “Stakeholders” destroying the viability of Ontario’s electricity market, but I will note that since last March a Variance Account under the [un]Fair Hydro Plan – which shifts costs from ratepayers today to rubes sometime in the future – a debt of $1.2 billion accumulated with April’s total still to be posted.
Today the system operator (IESO) posted the top 5 peak hours for the adjustment period that ended April 30th, 2018 (it started May 1, 2017) – and Monday the IESO posted the final Global Adjustment figures for April. This post will contain:
a quick demonstration of cost shift calculations,
review of the ICI value proposition, and
another jab at the province’s time-of-use (TOU) billing experiment performed on residential consumers.
For the 12 months of the ICI adjustment period the cost shift can be calculated as the difference between what Class A (larger consumers and ICI participants) did pay and what they would have paid were there not a separate class:
The total global adjustment charge for the period was $11.821 billion dollars, and total consumption (both classes) 138.194 terawatt-hours (million MWh), so the average global adjustment rate was $85.54/MWh.
Class A consumers were allocated a $1.8529 billion of the global adjustment total on 36.503 TWh of consumption which works out to an average global adjustment rate of $50.76/MWh
The $35.78/MWh difference in that rate, on 36.503 million MWh, means $1.27 billion was avoided
Electricity prices, and costs are aspects of a project I’m trudging through working with electricity data from the United States. I’ve developed a Power BI report which probably deserves a lot slicker interface, but time is limited. This post offers directions on controlling the reporting, and adds some Ontario context to the graphics.
My primary intent was to create imagery of average monthly electricity cost, by state, for residential consumers. Rates get a lot of discussion, even more so in recent weeks, but I’m not convinced an isolated rate analysis is useful.
A recent Scientific American article featured a smart BI report by Abhilash Kantamneni ( @akantamn on Twitter ).
Due to an exchange on Twitter I’d had with Abhilash a couple of weeks ago, I wanted to build a view that showed both rates, and average monthly consumer costs – because it turns out these are much different things.
Ontario Power Generation Inc. (OPG or Company) today reported net income attributable to the Shareholder of $860 million for 2017, compared to $436 million in 2016.
That must be considered a great number in the context of the income history at OPG as it’s the highest they’ve ever accomplished. The apparently excellent results may leave some wondering what critics commenting on the sector have been braying on about. I, a critic, have reviewed the results and found some things to bray about.
A spreadsheet I regularly update with data on industrial wind turbine (IWT) generation in Ontario is cited in Parker Gallant’s recent, Wind: worst value for Ontario consumers. The same post cites the Canadian Wind Energy Association (CanWEA) commentary on Ontario’s recently released Long Term-Energy Plan 2017, which included:
New wind energy provides the best value for consumers to meet growing demand for affordable non-emitting electricity.
Let’s examine the “value” as electricity – as there is no market in Ontario for any subset of that commodity, including “affordable non-emitting”.
“The regard that something is held to deserve; the importance, worth, or usefulness of something.”
“The worth of something compared to the price paid or asked for it.”
By the first definition wind is clearly the least valued generation type in Ontario. Using only very basic hourly data sets of Hourly summary totals of grid-connected (Tx) generation by type, valued at the Hourly Ontario Energy Price (HOEP), value factor can be calculated. A value factor above 1 means more valuable than average, below 1 means less valuable, and the lowest number consistently means wind.
Geoff Zochodne, a reporter at the National Post, gleaned this message from the release:
“Ontario exported more power to the U.S. last year than it has in a decade, and at a relatively low value.”
This initiated some e-mailing, which drew me into the data quagmire again, but also reflecting on my history reporting on exports. Instead of putting my thoughts into private e-mails, I thought I’d make them the content of this public blog post.
I’ll return to the newly posted Statistics Canada data later, but for now I’ll declare my bias as printed in the Financial Post early in 2016: “…StatsCan data is awful. It can’t be the basis for anything.” The recent release has mostly meaningful data, but some big errors mean it’s far from the best data to serve in analyzing Ontario’s exports – or anything else.
Some background on my involvement reporting on exports – if only to satisfy my sudden nostalgia.
Reporting on losses of exports is what got my blogging noticed back in January 2011. I’d started writing a couple of months earlier – to maintain skills in data analysis and, hopefully, develop some writing ability. January 1st, 2011 was warm (for winter) and it was windy. I wrote of records:Read More »
I thought, presumably as most do when seeing a graphic such as this, I should reproduce this work, and extend it to the present time. Not being overly ambitious, I simply use Consumer Price Index data (from CANSIM Table 326-0020), so my graphics will omit data from industrial entities; not being without curiousity I also grabbed data for average annual residential electricity prices (from the U.S. Energy Information Administration (EIA) site).
A little math to reset the base years that will equal 100% and:
It’s not been a good 3 decades for Ontario electricity consumers.
I started receiving messages last night on a sorta report by Environmental Defence (ED), and as I am still receiving them, I thought I’d write some thoughts – if only to simply copy a link when again asked for my thoughts.
Here is how ED’s Keith Brooks begins a blog post on their latest “work”:
Electricity prices in Ontario have risen in recent years, putting the squeeze on some Ontario residents and businesses. There are many reasons for the increase in electricity prices and renewable energy is one of them. However, the role of renewables in diving up electricity bills has been vastly exaggerated.
I wrote on a poor 2014 ED work and noted their new backgrounder contains a graphic with the same information as Figure 1 of their 2014 work. Without acknowledging any level of competency in the compilation of data for either ED graphic, here’s the elements of residential electricity bills as they report them for 2016 and 2014:
Perhaps the “role of renewables in driving up electricity bills” is perceived as being significant because: