Following up a record setting demand level Thursday Alberta's electricity system operator (AESO) fell to issuing a supply alert Friday afternoon. One smaller gas unit went offline (but came back during the alert) - and wind dropped to near zero. In all the excitement the Premier issued a post on X, was needled for the mistakes in the tweet, and deleted the tweet.
It will live on in at least one institution. I think communication is a different skill than proper use of vocabulary, and statistics, so before I dissect the Premier's statement, give it a read and think of a single message it communicates.
Maybe that's an important thing.
"...wind power is only generating 8 MW of electricity... that's only enough to power less than 10 homes for one day."
Power is an instant measure, multiplied by time it is a unit of energy. 8 megawatts of output delivering constantly over an hour is 8 megawatt-hours (8 MWh). To power a home for a day one would need MWh - not MW. So the sentence is, from one standpoint, unintelligible.
But, it's common for reporting to be made hourly: 4 pm would mean 3-4 pm, 8 MW would mean 8 MWh - and all that is also not too specific as it's based on 5-minute dispatch periods made be the AESO: they may have dispatched that amount, but that doesn't mean more, or less, wasn't generated. Ignore that for a moment, and lets pretend the statement meant 8 MWh.
"that's only enough to power less than 10 homes for one day." Power again is an inappropriate term: 8 MW of power for a day would be 192 MWh, but why would wind turbines at one instance (instead of over an hour) translate to supply steady power over time?
The purpose of a political communication is not to bore the reader with precision, it's to communicate a point, and I think a rational read of the tweet would believe the energy produced in one hour by wind could only supply the energy needs of 10 houses over a 24 hour day. By my math that would mean an average rate of consumption at each house of 33 kWh each hour. That's about 25 times an average winter consumption, but an average house does not get all its energy from electricity - and the Premier's post did say "enough to power less than 10 homes" - not in addition to other energy sources such as natural gas and wood.
I've lived in 2 homes that were only serviced by electricity - and wood. 10 kWh isn't hard to get to in winter even in Ontario, where temperatures I've encountered have never approached the -40C's Alberta is seeing. So while 10 houses is a little low for consumption of 8 MWh over the course of a day, if you convert a home's gas and wood use to kWh you won't find an order of magnitude difference.
[note: Steve Aplin usefully noted on Linkedin, "[Alberta's] private dwellings are on average losing heat at the rate of about 10 kilowatts each".
But remember that thing I set aside - on the dispatch of electricity. When I looked at AESO data 4 wind facilities were dispatched, leaving about 40 other sites not being called to provide power. Last I check there were over 1300 industrial wind turbines (IWT) in Alberta, and that was over 800 MW of capacity ago, so let's say 1500 individual IWTs, all of which consume electricity when not producing it. Over a decade ago I tracked down consumption of one model of turbine at 50 kW. This was, apparently, high but that also wasn't keeping equipment maintained while temperatures were below -40C. If the average industrial wind turbine in Alberta consumes 25 kilowatts of power while not spinning in the cold, and 1200 turbines were stilled, the consumption of the non-productive wind fleet in Alberta was significantly negative (30 MW of consumption more than cancelling out 8 MW of supply).
The net 22 MW draw might only be enough to prevent energy being provided to 27.5 homes over the course of a day, by some questionable calculation, but it is still not good.
If you got the impression from the Premier's technically inept tweet that wind produced sweet fuck all during the very cold day while natural gas provided the vast majority of energy in the province, she communicated quite well, quite quickly.
Hi Scott, do you know the correlation to the IESO Demand Forecast vs actual Consumption/AQEW ? I.e at 4pm today, what is the correlation they can get the right actual for 4pm yesterday and so on and so on?
sorry - just noticing this. The IESO does release AQEW figures (after the fact), but that's not 'actual consumption' either. As far as I know the IESO neither knows nor estimates distributed generation, so their finest level of detail is the quantity of energy withdrawn from the system they control. One exception is 'high five' hours, but when they added those up back when I paid more attention it was through establishing the high 5 hours (then with AQEW) and then surveying all the local distribution companies to get the metered distributed supply for just those hours.
Hey Scott, Norm Rubin here. Are you aware of OH's original $2.5B estimate of Darlington's total cost (which got the government's initial approval to proceed), and OH's $3.5B "Release Estimate" that formed the basis of OH's Board's approval for Management to proceed? Do you really want to redefine their much later $7B estimate as the "original", just because some moron at the Star called it that? Really?
clearly I need to check around tumblr more Norm, as I'm just noticing this.
if I recall correctly I took a figure from around the 1980 Royal Commission release - but it was strange as it was given in future dollars instead of pegging it at the current (and known) currency.
Easter, as other holidays where we commune indoors, can be a super-spreader. This year I see mixed indicators: more immunity, and likely a less virulent variant, should blunt impact.
2 years into a pandemic Ontario data collection, and reporting of such, aren’t much improved. Some thoughts as we enter another super-spreader event (a.k.a. holiday).Hospitalizations are increasing – but not by so much as most think
With testing availability altered/restricted at the end of hospital statistics should be best, but only since January 10th do we have data to distinguish…
Alberta's shrinking electricity market already got a lot more costly
I've been looking at electricity in Alberta - as a healthy distraction to war in Ukraine and Europe trying to schedule an end to its addiction to Russia's energy,. That might seem a strange choice but it may allow an examination of how jurisdictions' decisions impact suppliers, how markets are manipulated or full-out faked (Ontario), and how market statistics need to be understood to provide meaningful information.
Most reports we see out of Alberta on electricity, such as recent reports on record demand, cite Alberta Internal Load (AIL) - which is strange as that number includes self-generation which isn't sold and bought on the provincial operator's market (AESO). Looking at annual summaries since 2006 AIL shows nearly 20% growth, but a far less frequently cited AESO figure, "System Load", has barely budged.
"System Load" also exaggerates the size of the actual market. Not only have certain categories of industrial, and MUSH sector, entities been self-generating, industrial and, to an extent, environmental strategies have encouraged cogeneration. As I understand it this means the grid needs to take whatever excess co-generators have.
Wind and solar facilities are also likely to operate in a manner that effectively shrinks the market. Alberta's regulations have long allowed for virtual power purchase agreements (vPPA). Perhaps the most famous of these was for Calgary's Ctrain: the regulations allow an entity to purchase supply over a long period of time from a particular, green, generator - and that generation is, at all times, accepted on the grid regardless of the instantaneous need for it by the purchaser, and at all times the purchaser is supplied by the grid, regardless of the current output at the contracted supplier.
The difference in simply viewing AIL trends or considering only the load that needs to be serviced by the generators on the grid without PPA's or cogeneration rights is significant: from 2006 to 2021 AIL rose 23%, but the non-PPA/cogeneration supply dropped 30%.
All good?
For the moment: lower emission supply and support for industry are good things. But there are signs of trouble that ought to have been anticipated. Prices shot up from an average of less than $20/MWh (cents/kWh) in 2016 to over $100/MWh in 2021. Little of that rate increase was related to the cost of fuel as the the AESO reports a large spark spread of $76.39/MWh in 2021, which is more than 10 times the spread in 2017.
"The main reason for the increase in the average pool price was driven by the change in offer behaviour of larger market participants following the expiration of the Power Purchase Agreements (PPAs) at the end of 2020."
Rates eased a little in the first quarter of 2022, compared to Q1 2021, but capacity issues may be looming. Coal-to-gas conversions have been abandoned at TransAlta's Keephills 1 and Sundance 4 generators, and the conversion of Sundance 5 was suspended by the company and shows no sign of being restarted. This removes 1,200 MW of capacity the AESO presented in its long-term Outlook of summer 2021. Combining the forecast for capacity from the AESO displays a quick drop in firm capacity as cogeneration, wind and solar rise - essentially further shrinking the market.
Alberta will gain a 900 MW combined-cycle natural gas power plant in the next few years, along with another 800 MW in cogeneration capacity which will act to reduce "system load". Wind and solar, neither of which has significant capacity value in winter-peaking Alberta's system, are on a growth streak too. The combination of must-take erratic wind and solar and must-take cogeneration is likely to further reduce the capacity factors of remaining traditional generators. The owners of those legacy assets are hiking their offer rates, lighting up the spark spread, and canceling plans to extend the life of their coal assets with further conversions to gas.
I’ve been asked to respond to a report from a lobby group on Ontario’s electricity system, one that utilizes a 2017 baseline to make claims on the growth of greenhouse gas emissions in the sector appear for more significant than deserved.
2017 is not a baseline year.
Not by the conventions of climate change base years.
The Kyoto Accords concluded late in 1997 had 1990 as a base year - because emissions were highest during the collapse of the coal-drenched USSR.
The Copenhagen Accord concluded late in 2009 treated 2005 as the base year because emissions had retreated due to the economic crisis of 2008-09.
The Paris Agreement had countries commit to producing Nationally Determined Contribution (NDC) plans, and Canada’s maintains 2005 as the base in promising “to reduce emissions by 40-45%.”
The electricity system operator’s (IESO) forecast for emission in its 2021 Annual Planning Outlook is 66% below 2005 levels (and 54% below 1990’s emissions).
2017 is the year Ontario had the lowest emissions of greenhouse gases from the generation of electricity: 54% below any year recorded previously and 34% below any recorded since or forecast to come. This was accomplished by a massive surplus of supply providing necessary flexibility in a system with abnormally low demand due to a warm winter and cool summer. The IESO reported 4.3 billion kilowatt-hours (kWh) of committed supply as curtailed, Ontario Power Generation (OPG) reported another 5.9 billion kWh of potential supply from publicly owned hydroelectric facilities foregone due to surplus, and in regulatory filings the IESO admitted the 14 billion kWh of surplus was sold on export markets at a fraction of what it paid to purchase it. In 2017 curtailed and dumped supply equated to 18% of total demand in Ontario for generation from the IESO-supplied grid.
2017 is a good baseline year for excess supply - not for emissions.
As 2005 served as the base year for the Copenhagen Accord and remains the base year in the Canada’s responses to its reporting commitments under the Paris Agreement I’d suggest it is the appropriate baseline year in discussing emissions.
On this issue the year 2000 is to Ontario as 1990 is to Germany: the high in annual emissions against which everything compares favourably. Between 2000 and 2005 four nuclear reactors returned to service (Bruce A units 3 and 4 as well as Pickering’s units 1 and 4), dropping emissions by over 8 megatons of carbon dioxide equivalence (Mt CO2e) as coal-fired generation was displaced. Emissions had spiked from 1994 (when Ontario’s final new-build reactor entered commercial operation at Darlington) to 2000, as the nuclear fleet was allowed to deteriorate and eight reactors eventually mothballed. Ontario did not consistently return to the low emission level of 1994 until 6 of those 8 reactors had returned to service (with refurbished Bruce units 1 and 2 re-entering operation in 2012).
"There is a myth out there that it's mild. We need to address this myth now" -Dr. Peter Jüni
I’ll show you a myth.
On December 16th the “Science Table: COVID-19 Advisory for Ontario” (the Table) released an “Update on COVID-19 Projections: Science Advisory and Modelling Consensus Tables” (the Update). If the mixture of “science” and “modelling consensus” didn’t alert you that this group might not be rigorously scientific, this key finding ought to have caught your attention:
“Although uncertainty persists, waiting for more information will eliminate the opportunity for action.”
I empathize with the desire to take action as cases skyrocket due to the omicron variant of COVID-19. This shouldn’t be surprising as I have an interest in politics - I even once received a degree in something called Political Science. However, in the ensuing decades, I took to working with data, and over the course of this pandemic have been more and more interested so many doctors find the time to murder data science while also setting policy.
The recent Update from the Table names “South Africa” 12 times, and “Denmark” 10. The omicron variant emerged to prominence in South Africa’s Gauteng region, and the Table provides some disconcerting graphs of increasing daily hospital statistics in that region, but only starting November 1st, 2021. If one looks more closely they’ll notice “Patients in ICU” and “Patients with Supplementary Oxygen” end about where they started, but deaths and hospitalization appear sharply up. On other graphs, separately, data for all of South Africa is shown but with the X-axis as “Days Since Beginning of the Wave”, with 4 waves shown: omicron is shown as increasing far more rapidly in cases, less so for hospital admission, and, only 28 days in, less quickly for deaths than previous variants’ waves.
I suggest a better visual guide to provide a more fulsome perspective is simply this: daily cases on the left Y-axis and daily deaths on the right - although clearly this would not currently be better at inciting fear.
The Update's graphics show the situation from wave to wave in South Africa is dissimilar, with the largest difference probably being explained by a level of immunity achieved through either vaccination or prior infection. The table (and even more so Dr. Jüni verbally in interviews on mainstream media) have sought to position South Africa as unlike Ontario in having a higher immunity in a younger population less at risk of severe outcomes. The Table’s latest update notes: “Median age in South Africa 28 years (Ontario 41 years), estimated percentage infected ~90% (Ontario ~10%), estimated percentage highly immune among adults ~32% (Ontario ~15%).” In the Table’s rush to claim Ontarians aren’t like South Africans they hurt the claim that the immunity bestowed by vaccines (Canada 81%, South Africa 31%) is as meaningful as that bestowed by prior infection - but I doubt they think anybody who reads their slides pays this much attention.
Denmark is named 10 times in the Update. Presumable the Table considers them more like us (in fairness I understand Danes also have superior testing allowing for easy recognition of the omicron variant). The most prominent claim, and again one Jüni leans on heavily in interviews, is illustrated in this slide:
Most of the graph doesn’t relate to omicron - like in other northern jurisdictions there was a growth in cases this fall before omicron, and there’s no growth in hospital occupancy since omicron’s began its rapid surge. The table data is what caught my attention because the Table makes a claim about virulence based on a small number of cases: "the percentage of cases requiring hospital admission is not lower with Omicron". I checked for updated data from the provided source and noted, on Twitter, it had changed significantly (even before the Table published its outlook). It has since changed again - with the latest version apparently having some revised methodology in calculations for “Other variants.”
Using the Table’s source and just having the discipline to monitor the figures show omicron cases are now less than half as likely to be in the hospital in Denmark as other variants' cases.
I have some sympathy for storytellers in building consensus for public action. Risk analysis is difficult at the best of times, and far more so in the case of spectacularly rapid rise in a new COVID variant. The table has quite obviously sought the few data points to support a narrative they wished to tell, but there’s no science to that.
When Dr. Peter Jüni stated, "There is a myth out there that it's mild" he went beyond storytelling. He deliberately uses his position to denigrate actual data analysis and real scientists to strengthen his narrative. Doctors, in my opinion, have a long history of not respecting other disciplines, and practitioners of the newer disciplines of data science and communications seem particularly prone to their work being negated by a Dr. Doctor opining.
Data is never perfect and in my opinion its too early to know what the outcomes of omicrom will be. I am optimistic about the evidence of a a less virulent form and choose positive story of it being a less virulent strain that'll escalate rapidly and ebb soon after. It’s a better supported theory than what the Table communicated in this week's update/myth.
Data journalism was becoming a thing about the time I started blogging a little over a decade ago. One format for what once-novel data-driven journalism was presenting a single powerful graphic accompanied by text explaining the graphic in depth. Jump ahead 10 years and we see data hasn’t sparked the interest some of us hoped. Instead of building a narrative to explain data, it’s far more common…
Parker Gallant has called for the Ontario government to “shutdown the intertie line with Michigan” – in an article that notes some of my work. I feel I should offer some support as Michigan is being a lousy neighbour and it would feel therapeutic, if nothing else, to respond.
I’ll try to stick to data.
The system operator in Ontario (IESO) data indicates the Michigan intertie is the most…
Despite my best efforts to avoid such things a story from the United States has caught my attention.
This seems innocent enough: Biden taps Ezekiel Emanuel to coronavirus task force. This Emanuel is a brother of Rahm.
Rahm Emanuel is famous for a few things, but his most famous quote is from a 2008 interview:
You never want a serious crisis to go to waste. And what I mean by that [is] it's an opportunity to do things that you think you could not before.
Ezekiel Emanuel, the new member of the new COVID-19 task force being assembled by President-Elect Biden, wrote a column in 2014 titled, Why I Hope to Die at 75. A taste:
...here is a simple truth that many of us seem to resist: living too long is also a loss. It renders many of us, if not disabled, then faltering and declining, a state that may not be worse than death but is nonetheless deprived. It robs us of our creativity and ability to contribute to work, society, the world. It transforms how people experience us, relate to us, and, most important, remember us. We are no longer remembered as vibrant and engaged but as feeble, ineffectual, even pathetic.
I’m not sure the exact average age of those dead with COVID-19 in my province of Ontario is, but I do know more than two-thirds have been over 80 and 87% have been over the age of 70. 64% of all deaths have been residents of long term care facilities.
Maybe Biden is trying the ‘red team, blue team’ approach defeated President Trump couldn’t quite bring himself to implement on a different, significant, topic.
Thee to WE: the foundations of Canada’s Green Stimulus – part 2
Thee to WE: the foundations of Canada’s Green Stimulus – part 2
The following is the second section of a work I’ve been preparing for my main site. As rumours of the federal government proceeding with the externally-developed policy framework I have been researching, and because of the length the work has grown to, I decided to post the work in parts here as sections are completed. (Part 1)
The May 19th announcement of the Task Force for a Resilient…
Thee to WE: the foundations of Canada's Green Stimulus - part 1
Thee to WE: the foundations of Canada’s Green Stimulus – part 1
The following is the beginning of a work I’ve been preparing for my main site. As rumours of the federal government proceeding with the externally-developed policy framework I have been researching, and because of the length the work has grown to, I’ve decided to post the work in parts here as sections are completed.
The Case for Near-term Commercial Demonstration of the Integral Fast Reactor
The Case for Near-term Commercial Demonstration of the Integral Fast Reactor
This is a 2012 post from Barry Brook’s Brave New Climate, which was a tremendous blog but one that is no longer maintained – and was left with a presentation scheme that is illegible.
I’m currently in Dubai at the 2012 World Energy Forum, as part of a delegation from the Science Council for Global Initiatives. Tomorrow (24 Oct) we will run symposium on “New Nuclear”, which will be chaired by…
Ontario Government manufactured the highest electricity demand in years.
Each day from July 7th to July 10th saw an IESO "Ontario Demand" peak higher than any day since July 2013, and July 6th saw the 7th highest peak since 2013's summer. The government had made some announcements that encouraged the higher peaks now experienced:
On Saturday, May 30th, the government announced the suspension of time-of-use (TOU) electricity pricing, replacing it with a flat rate until the end of October, and,
On the afternoon of Friday June 26th the government announced, "companies that participate in the Industrial Conservation Initiative (ICI) will not be required to reduce their electricity usage during peak hours"
The second of these announcements was the most impactful in spurring higher peak consumption.
A detailed study delivered to Ontario's system operator (IESO) over 3 years concluded there was little load shifting accomplished by TOU rates, and that the impact had declined the longer TOU was implemented:
For the province as a whole there was a statistically significant reduction in usage during the EM&V peak of 2.11 percent in the pre-2012 period, 1.89 percent in 2012, 0.82 percent in 2013, and 0.73 percent in 2014 relative to what usage would have been in the absence of TOU.
It would be very hard to spot a difference of a couple of gigawatt-hours in comparing demand profiles on different days of different years. It's also hard to spot a reason the government would reintroduce TOU rates as the default pricing option in November. Critical Peak Pricing - which would charge much higher rates only for hours where demand threatened to exceed supply - deserves more serious concern than TOU does.
It is very easy to spot the impact of suspending the requirement for Industrial Conservation Initiative consumers to reduce consumption during the five highest daily peak hours in order to reduce their future global adjustment charges. Two days with similar demand profiles from 6-11 am, and after 9 pm, are July 5th, 2018 and July 10th, 2020: on the day in 2018 Class A consumers enrolled in the Industrial Conservation Initiative were curtailing their demand from the grid to avoid global adjustment charges the following year, but that incentive was negated for those consumers two weeks before July 10th, 2020.
The demand reduction at peak appears to be, from this comparison, a little over 1500 megawatt-hours (MWh) at the usual peak hour, which should be expected due to claims made by the IESO in its Annual Planning Outlook:
In 2018, the ICI delivered an average demand reduction of approximately 1,600 MWh in the top 10 demand hours, and a maximum ICI reduction of 1,717 MW. The maximum ICI reduction on the peak demand day, and during the peak demand hour, was 1,347 MW and 1,330 MW, respectively.
The good news is there's evidence the ICI did reduce peak demand by what the system people said it did - but the system performing well without Class A consumers reducing consumption at peak should also be an indictment of the high cost of a program suddenly deemed unnecessary.
While "Ontario Demand" averaged 19,877 MW from July 6-10, the Hourly Ontario Energy Price (HOEP) averaged only $40.17 for megawatt-hour (approximately 4 cents/kWh), The highest the HOEP reached was $203.46, which is lower than time-of-use On-Peak rates would have been had TOU not been suspended for the summer.
No ICI. No problem.
So... how could one justify the $8 billion of cost transferred from Class A consumers to Class B consumers since the ICE was introduced?
The government is unlikely to justify anything - they'd just blame the previous government if they found the courage to design a new pricing system that protected trade-exposed industrial consumers from uncompetitive electricity pricing. A good design should recognize the actual capacity needs the Industrial Conservation Program provided - but also that it provided that capacity far more expensively than Class B consumers could have procured it elsewhere.
