Here is a link to the Fraser Institute publication referenced in the title of this post authored by Ross McKitrick and myself.
All substantive comments on the report are welcome. Spitballers need not apply.
Figure 2, Units should be cost per GW.h not MW.h
Page 22 describes the Power Advisory/Environmental Defense study. They said at page 6 of their study that wind and solar added $5 each to a monthly residential bills (not to GA, as our study claims) in 2014.
Figure 4 horizontal axis units should be MW (not MWh) (Appreciation to Rick in the comments below for picking this up.)
All are items I should have caught earlier. Ouch! A rewrite of the top paragraph on p. 22 is noted below.
Post Script Nov 2 am: Thoughtful review of the report in Sunday’s Toronto Sun.
Revised paragraph for p. 22:
Our results contradict the claims of Chee-Aloy and Stevens (2014), who applied an accounting methodology and concluded that wind and solar energy each contributed only $5 to the commodity cost of the household bill. Their analysis, upon which the activist group Environmental Defence relied in a prominent recent pamphlet campaign, failed to take into account the way that interactions among the different generating types exacerbate the GA burden. Their methodology does not measure contributions to historical variance of the GA; whereas, the model we have presented herein explains close to 90 percent.
Here is a link to the National Post oped (October 30 print edition) Ross and I wrote to summarize our results.
Tom, your link is not working; I think you are missing a colon.
PS – “Stop the wind energy fraud!”
Please know that as soon as I began mowing down on your double-trouble feast (which was unsurprisingly doubly satisfying) – the a la carte portions that each of you had previously served kept coming back to mind.
Who knows why I never seem sufficiently prepared for such happy thoughts to return, when they do so intertwined with sickening recollections like those of a too-memorable speech delivered by Ontario’s then Minister of Health and Long-Term Care on May 5, 2004. Perhaps I’ll never be and Winston Churchill will forever be up-chucking in his grave?
Although the unanticipated return of such downers, including more associated with “demonize” and 2004, had made me feel as Green around the gills as re-reading that speech always does – my appetite (and hope) was restored at seeing this timely forewarning brought to the table:
“The province has erred badly in adding high-cost hydroelectric units to its current generating mix. At a time when we currently have surplus baseload and no viable storage system, these units are not needed, and they appear to have had a large effect on the GA.”
Thank you! Encore!
Enjoyed reading your report. A couple of questions about Figure 4.
The x-axis reads “Installed wind capacity (MWh)”. Of course, capacity is not measured in MWh, so this is possibly an errata or is it intended to reflect the output (in Mwh) of the capacity (in MW) indicated numerically in the x-axis?
Is the x-axis a reflection of “wind” in Table 3, “wind” in Table 4, “wind cap” in Table 4, or none of these?
On page 17, it reads: “If we include both wind capacity and wind output in the model, the results change in an interesting way, and show that wind capacity strongly influences the GA (table 4).”
Your report provides the following explanation for this phenomenon:
“This strongly suggests that side agreements and revenue guarantees, if not explicitly built into the FIT system, are implicitly present in other ways, and the GA has evolved in a manner highly consistent with a system in which wind farm operators are contracted for capacity rather than merely generation.”
Is it possible there are other less direct ways in which the addition of new wind capacity leads to increases in the GA?
I ask this because it would surprise me that wind generators are being contracted for capacity. There is no dependable capacity being provided, so why would this capacity be contracted or need to be contracted? Another plausible explanation is that additional wind capacity triggers several other actions that in turn drive up the GA indirectly. For example, you hint at one possible indirect effect on page 8:
“The OPA also has contracts with generators, including most gas-fired capacity, where the generator
receives a monthly revenue guarantee per unit of available generation, offset by calculated operating profits per unit of deemed output.”
In other words, for each MW of additional wind capacity, we must also contract additional gas capacity for times when wind is not operating.
One big problem in the study is to make the model work is that you have to look around for secret deals between gov. and this or that entity. It actually requires that you believe a conspiracy theory.
Conspiracy? These are big money deals and all you have to do is look up the information and who the involved parties are!
Tom and Ross did not, clearly.
Good question about why wind capacity sticks out like such a sore thumb.
We make a few brief comments at the end of the paper in section 4.7 on additional areas for research. In hindsight, we might have identified the very strong relationship between GA and wind capacity as an area for more investigation. I don’t have theory as to why the coefficient for windcap vs. GA is so high, but the narrow confidence interval around the high coefficient raises an alarm bell. The “Giant Talking Chicken From Toronto” (BigCityLib, MJ Murphy), thinks that we are floating a “conspiracy theory” but we think the model results speak louder than MJM’s chicken talk.
In Section 4.7, we point out that another area to explore is what makes new hydro-electric capacity appear to perform so miserably. The miserable showing for new hydro might be partly a knock-on effect of secret Hydroelectric Contracting Initiative deals with outfits like Brookfield and secret deals between the OPA and OPG over new hydros. Better official disclosure is a real barrier to knowledge there.
Section 4.7 also refers to investigating the operational impacts of fickle renewables generation. Our model looks at monthly cost impacts, which is too coarse to get a good view of operational impacts. Higher resolution modelling would really help.
Another area that strike me as important to check out in future, that we might have included in 4.7, was the need to get a better handle on the impact of solar. We know that direct payments to producers are vastly over market, that solar’s output arrives on peak only a few days per year, and the GA impact coefficient is very high. However, the confidence interval is still wide, perhaps reflecting the small production of solar to date. With a continuing massive solar build up ongoing, more data will be available for future research.
Thanks for your considered response. A few comments:
1. With respect to figure 4, I understand that is it “wind cap” in Table 4 that is being evaluated in this figure. I don’t have the data, but looking at the graph, it appears that the relationship between the GA and wind capacity (in MW) is basically linear. To the extent that the GA is a measure of the cumulative monetary effect of adding more wind resources to the grid at costs above market prices, I would normally expect each additional unit of wind capacity to have less cumulative effect. This would be the case since the development of new projects usually occurs adjacent to existing projects, resulting in wind hubs and marginally lower direct costs due to shared infrastructure before the point of interconnection (and for that matter after the POI, too, though that is not measured in the GA). It may be that this has not happened as there is not enough wind on the system to see that effect (recognizing that some people think there is already too much wind!), that projects are still being developed in new locations, that proponents are taking the lower costs in profits (i.e. no reduction in contract real dollar prices), or other reasons. There may also be a geographical distribution benefit to spreading out the wind resource. It will be interesting to see how this number changes with more wind capacity added to the grid. I expect a continued increase in the GA with more wind capacity but at a slower rate of increase.
2. I agree that there are likely to be similar reasons behind the contributions of wind and hydro to the GA, but do not share your more conspiratorial (for lack of a better term) views, lacking access to the contracts with the independent power producers. Though I have not checked the data, I would expect that newer hydroelectric facilities have less dependable capacity (i.e. less or no storage capability) than earlier facilities as the better sites have already been developed and current environmental regulations do not allow reservoir creation. So, much like wind, new hydro triggers the development of dependable capacity in the form of natural gas driving up the GA, though to a lesser extent than wind. This fits with my intuition since small hydro projects usually have a measurable amount of flow all year and never completely stop operating, unlike wind, so the dependable capacity of the former is not zero, whereas it is for the latter.
3. In regards to solar, I would be tempted to treat transmission connected solar (i.e. large-scale projects) differently from distribution connected solar as I suspect that your model would show different effects on the GA, since the latter operates much more like a DSM resource (i.e. net metering the requirements of LDCs) where as the former enters the market more like wind or hydro. With more solar resources on the system over time, you might be able to tease apart these effects.
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